BEGIN:VCALENDAR VERSION:2.0 PRODID:-//Business Development Institute (BDI) - ECPv6.15.20//NONSGML v1.0//EN CALSCALE:GREGORIAN METHOD:PUBLISH X-ORIGINAL-URL:https://bdionline.com X-WR-CALDESC:Events for Business Development Institute (BDI) REFRESH-INTERVAL;VALUE=DURATION:PT1H X-Robots-Tag:noindex X-PUBLISHED-TTL:PT1H BEGIN:VTIMEZONE TZID:America/New_York BEGIN:DAYLIGHT TZOFFSETFROM:-0500 TZOFFSETTO:-0400 TZNAME:EDT DTSTART:20240310T070000 END:DAYLIGHT BEGIN:STANDARD TZOFFSETFROM:-0400 TZOFFSETTO:-0500 TZNAME:EST DTSTART:20241103T060000 END:STANDARD BEGIN:DAYLIGHT TZOFFSETFROM:-0500 TZOFFSETTO:-0400 TZNAME:EDT DTSTART:20250309T070000 END:DAYLIGHT BEGIN:STANDARD TZOFFSETFROM:-0400 TZOFFSETTO:-0500 TZNAME:EST DTSTART:20251102T060000 END:STANDARD BEGIN:DAYLIGHT TZOFFSETFROM:-0500 TZOFFSETTO:-0400 TZNAME:EDT DTSTART:20260308T070000 END:DAYLIGHT BEGIN:STANDARD TZOFFSETFROM:-0400 TZOFFSETTO:-0500 TZNAME:EST DTSTART:20261101T060000 END:STANDARD END:VTIMEZONE BEGIN:VTIMEZONE TZID:America/Los_Angeles BEGIN:DAYLIGHT TZOFFSETFROM:-0800 TZOFFSETTO:-0700 TZNAME:PDT DTSTART:20240310T100000 END:DAYLIGHT BEGIN:STANDARD TZOFFSETFROM:-0700 TZOFFSETTO:-0800 TZNAME:PST DTSTART:20241103T090000 END:STANDARD BEGIN:DAYLIGHT TZOFFSETFROM:-0800 TZOFFSETTO:-0700 TZNAME:PDT DTSTART:20250309T100000 END:DAYLIGHT BEGIN:STANDARD TZOFFSETFROM:-0700 TZOFFSETTO:-0800 TZNAME:PST DTSTART:20251102T090000 END:STANDARD BEGIN:DAYLIGHT TZOFFSETFROM:-0800 TZOFFSETTO:-0700 TZNAME:PDT DTSTART:20260308T100000 END:DAYLIGHT BEGIN:STANDARD TZOFFSETFROM:-0700 TZOFFSETTO:-0800 TZNAME:PST DTSTART:20261101T090000 END:STANDARD END:VTIMEZONE BEGIN:VTIMEZONE TZID:America/Chicago BEGIN:DAYLIGHT TZOFFSETFROM:-0600 TZOFFSETTO:-0500 TZNAME:CDT DTSTART:20240310T080000 END:DAYLIGHT BEGIN:STANDARD TZOFFSETFROM:-0500 TZOFFSETTO:-0600 TZNAME:CST DTSTART:20241103T070000 END:STANDARD BEGIN:DAYLIGHT TZOFFSETFROM:-0600 TZOFFSETTO:-0500 TZNAME:CDT DTSTART:20250309T080000 END:DAYLIGHT BEGIN:STANDARD TZOFFSETFROM:-0500 TZOFFSETTO:-0600 TZNAME:CST DTSTART:20251102T070000 END:STANDARD BEGIN:DAYLIGHT TZOFFSETFROM:-0600 TZOFFSETTO:-0500 TZNAME:CDT DTSTART:20260308T080000 END:DAYLIGHT BEGIN:STANDARD TZOFFSETFROM:-0500 TZOFFSETTO:-0600 TZNAME:CST DTSTART:20261101T070000 END:STANDARD END:VTIMEZONE BEGIN:VEVENT DTSTART;TZID=America/New_York:20251028T173000 DTEND;TZID=America/New_York:20251028T200000 DTSTAMP:20260416T140750 CREATED:20250825T183226Z LAST-MODIFIED:20260203T172227Z UID:115265-1761672600-1761681600@bdionline.com SUMMARY:GenAI Roundtable for Enterprise Innovation - An Executive Dinner & Wine Tasting for Technology Leaders DESCRIPTION:Event Recap: From Disruption to Advantage: AI-Powered Resilience in Supply Chains \n \n \n \n Rosemont\, IL | Gibsons Rosemont | November 13\, 2025 \n \n \n \n \n \n \n \n \n \n \n \n Speakers \n \n \n \n \n \n \n \n \n \n \n \n \n Ron Gilson \n \n \n NTT DATA Business Solutions \n \n \n \n \n \n \n \n Executive Advisor and Principal - Consumer Products and Agribusiness \n \n \n \n \n \n LinkedIn \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n John Buckley \n \n \n SAP \n \n \n \n \n \n \n \n Consumer Products Industry Advisor - Midwest Region \n \n \n \n \n \n LinkedIn \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Sai Simhadri \n \n \n Pampered Chef \n \n \n \n \n \n \n \n Senior Data Architect Manager \n \n \n \n \n \n LinkedIn \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Jody McDonough \n \n \n Sub-Zero Group\, Inc. \n \n \n \n \n \n \n \n VP of IT / CIO \n \n \n \n \n \n LinkedIn \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Executive SummaryEnterprise leaders described a clear shift in how supply chains\, operations\, and core business processes are being managed in an era defined by constant disruption. Resilience is no longer treated as a one-time corrective response to global shocks; it is becoming a permanent design principle. Organizations are rebalancing long-standing cost-optimization models with the need for flexibility\, visibility\, and faster decision-making across suppliers\, manufacturing\, logistics\, and service networks. The discussion highlighted that disruptions—geopolitical\, regulatory\, labor-related\, or demand-driven—are now expected\, not exceptional. AI emerged as an enabler rather than a starting point. Executives consistently emphasized that value comes from applying AI to clearly defined business problems\, supported by digitized\, high-quality data and integrated processes. Rather than pursuing broad or experimental AI initiatives\, leaders are embedding intelligence directly into core workflows such as demand planning\, transportation optimization\, supplier collaboration\, and service operations. The organizations seeing results are those that treat AI as a practical extension of operational discipline\, not a replacement for it. Looking forward\, competitive advantage will come from execution speed and adaptability. Companies that can move to “Plan B” faster—through scenario planning\, data transparency\, and orchestrated decision-making—are better positioned to turn disruption into opportunity. AI\, when grounded in clean data and governed processes\, is becoming a force multiplier for cost control\, service consistency\, and supply chain resilience. \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Key Themes \n \n \n \n Key Themes \n \n \n \n \n\n\n \n \n Resilience as a core operating model.\n Supply chain disruptions are now continuous. Organizations are redesigning processes to absorb shocks and respond dynamically\, rather than optimizing solely for steady-state efficiency.\n \n\n \n Cost pressure returning to the forefront.\n After a period dominated by availability and service\, cost optimization is re-emerging as a priority due to inflation\, tariffs\, and consumer resistance to price increases.\n \n\n \n Data readiness before AI adoption.\n AI effectiveness depends on digitized\, accurate\, and integrated data. Many organizations are still focused on building reliable data pipelines before scaling advanced analytics or AI agents.\n \n\n \n Targeted\, use-case-driven AI.\n The most successful AI initiatives are narrowly scoped and tied to measurable outcomes—such as freight optimization\, packaging efficiency\, demand sensing\, or service-part prediction.\n \n\n \n From deterministic models to agent-based intelligence.\n Enterprises are evolving from rule-based and deterministic planning models toward multi-agent AI systems that collaborate across functions while retaining human oversight.\n \n \n\n Read more\n\n\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Actionable Takeaways for Enterprise Leaders\n \n \n \n \n Actionable Takeaways for Enterprise Leaders\n \n \n \n \n \n \n \n Design for disruption\, not stability.\n Assume supply chain shocks will continue. Build operating models that prioritize flexibility\, scenario planning\, and rapid reconfiguration.\n \n\n \n Refocus AI initiatives on core processes.\n Start with finance\, procurement\, supply planning\, logistics\, and service workflows where inefficiencies are well understood and ROI can be measured.\n \n\n \n Digitize end-to-end before scaling AI.\n Eliminate paper\, manual handoffs\, and siloed systems. AI delivers value only when underlying processes and data are fully digitized.\n \n\n \n Balance cost optimization with resilience.\n Evaluate sourcing\, manufacturing\, and logistics decisions through both cost and risk lenses to avoid trading short-term savings for long-term fragility.\n \n\n \n Adopt AI incrementally with governance.\n Deploy AI agents in constrained domains\, monitor performance\, and introduce human review where error tolerance is low.\n \n\n \n Strengthen supplier and partner integration.\n Increase real-time data sharing and visibility across supplier networks to detect quality\, capacity\, and delivery risks earlier.\n \n\n \n Use AI to accelerate decision speed\, not just insight.\n Prioritize applications that reduce manual effort and compress decision cycles\, enabling faster execution when conditions change.\n \n \n\n Read more\n\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n EVENT PHOTOS  \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Sponsors \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n NTT DATA is a $30+ billion trusted global innovator of business and technology services. We serve 75% of the Fortune Global 100 and are committed to helping clients innovate\, optimize and transform for long-term success. As a Global Top Employer\, we have experts in more than 50 countries and a robust partner ecosystem of established and startup companies. Our services include business and technology consulting\, data and artificial intelligence\, industry solutions\, as well as the development\, implementation and management of applications\, infrastructure and connectivity. We are also one of the leading providers of digital and AI infrastructure in the world. NTT DATA is part of NTT Group\, which invests over $3.6 billion each year in R&D to help organizations and society move confidently and sustainably into the digital future. Learn more at nttdata.com URL:https://bdionline.com/event/102825/ LOCATION:Butter\, 70 W 45th St\, New York\, NY\, 10036\, United States CATEGORIES:Event Calendar,No Header ATTACH;FMTTYPE=image/webp:https://bdionline.com/wp-content/uploads/2025/08/AMDNYCfeaturedimage.webp END:VEVENT BEGIN:VEVENT DTSTART;TZID=America/New_York:20251022T173000 DTEND;TZID=America/New_York:20251022T200000 DTSTAMP:20260416T140750 CREATED:20250828T160329Z LAST-MODIFIED:20260203T172231Z UID:115403-1761154200-1761163200@bdionline.com SUMMARY:Equinix Engage: Real-World Insights From Today’s Leaders in AI DESCRIPTION:Event Recap: From Disruption to Advantage: AI-Powered Resilience in Supply Chains \n \n \n \n Rosemont\, IL | Gibsons Rosemont | November 13\, 2025 \n \n \n \n \n \n \n \n \n \n \n \n Speakers \n \n \n \n \n \n \n \n \n \n \n \n \n Ron Gilson \n \n \n NTT DATA Business Solutions \n \n \n \n \n \n \n \n Executive Advisor and Principal - Consumer Products and Agribusiness \n \n \n \n \n \n LinkedIn \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n John Buckley \n \n \n SAP \n \n \n \n \n \n \n \n Consumer Products Industry Advisor - Midwest Region \n \n \n \n \n \n LinkedIn \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Sai Simhadri \n \n \n Pampered Chef \n \n \n \n \n \n \n \n Senior Data Architect Manager \n \n \n \n \n \n LinkedIn \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Jody McDonough \n \n \n Sub-Zero Group\, Inc. \n \n \n \n \n \n \n \n VP of IT / CIO \n \n \n \n \n \n LinkedIn \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Executive SummaryEnterprise leaders described a clear shift in how supply chains\, operations\, and core business processes are being managed in an era defined by constant disruption. Resilience is no longer treated as a one-time corrective response to global shocks; it is becoming a permanent design principle. Organizations are rebalancing long-standing cost-optimization models with the need for flexibility\, visibility\, and faster decision-making across suppliers\, manufacturing\, logistics\, and service networks. The discussion highlighted that disruptions—geopolitical\, regulatory\, labor-related\, or demand-driven—are now expected\, not exceptional. AI emerged as an enabler rather than a starting point. Executives consistently emphasized that value comes from applying AI to clearly defined business problems\, supported by digitized\, high-quality data and integrated processes. Rather than pursuing broad or experimental AI initiatives\, leaders are embedding intelligence directly into core workflows such as demand planning\, transportation optimization\, supplier collaboration\, and service operations. The organizations seeing results are those that treat AI as a practical extension of operational discipline\, not a replacement for it. Looking forward\, competitive advantage will come from execution speed and adaptability. Companies that can move to “Plan B” faster—through scenario planning\, data transparency\, and orchestrated decision-making—are better positioned to turn disruption into opportunity. AI\, when grounded in clean data and governed processes\, is becoming a force multiplier for cost control\, service consistency\, and supply chain resilience. \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Key Themes \n \n \n \n Key Themes \n \n \n \n \n\n\n \n \n Resilience as a core operating model.\n Supply chain disruptions are now continuous. Organizations are redesigning processes to absorb shocks and respond dynamically\, rather than optimizing solely for steady-state efficiency.\n \n\n \n Cost pressure returning to the forefront.\n After a period dominated by availability and service\, cost optimization is re-emerging as a priority due to inflation\, tariffs\, and consumer resistance to price increases.\n \n\n \n Data readiness before AI adoption.\n AI effectiveness depends on digitized\, accurate\, and integrated data. Many organizations are still focused on building reliable data pipelines before scaling advanced analytics or AI agents.\n \n\n \n Targeted\, use-case-driven AI.\n The most successful AI initiatives are narrowly scoped and tied to measurable outcomes—such as freight optimization\, packaging efficiency\, demand sensing\, or service-part prediction.\n \n\n \n From deterministic models to agent-based intelligence.\n Enterprises are evolving from rule-based and deterministic planning models toward multi-agent AI systems that collaborate across functions while retaining human oversight.\n \n \n\n Read more\n\n\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Actionable Takeaways for Enterprise Leaders\n \n \n \n \n Actionable Takeaways for Enterprise Leaders\n \n \n \n \n \n \n \n Design for disruption\, not stability.\n Assume supply chain shocks will continue. Build operating models that prioritize flexibility\, scenario planning\, and rapid reconfiguration.\n \n\n \n Refocus AI initiatives on core processes.\n Start with finance\, procurement\, supply planning\, logistics\, and service workflows where inefficiencies are well understood and ROI can be measured.\n \n\n \n Digitize end-to-end before scaling AI.\n Eliminate paper\, manual handoffs\, and siloed systems. AI delivers value only when underlying processes and data are fully digitized.\n \n\n \n Balance cost optimization with resilience.\n Evaluate sourcing\, manufacturing\, and logistics decisions through both cost and risk lenses to avoid trading short-term savings for long-term fragility.\n \n\n \n Adopt AI incrementally with governance.\n Deploy AI agents in constrained domains\, monitor performance\, and introduce human review where error tolerance is low.\n \n\n \n Strengthen supplier and partner integration.\n Increase real-time data sharing and visibility across supplier networks to detect quality\, capacity\, and delivery risks earlier.\n \n\n \n Use AI to accelerate decision speed\, not just insight.\n Prioritize applications that reduce manual effort and compress decision cycles\, enabling faster execution when conditions change.\n \n \n\n Read more\n\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n EVENT PHOTOS  \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Sponsors \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n NTT DATA is a $30+ billion trusted global innovator of business and technology services. We serve 75% of the Fortune Global 100 and are committed to helping clients innovate\, optimize and transform for long-term success. As a Global Top Employer\, we have experts in more than 50 countries and a robust partner ecosystem of established and startup companies. Our services include business and technology consulting\, data and artificial intelligence\, industry solutions\, as well as the development\, implementation and management of applications\, infrastructure and connectivity. We are also one of the leading providers of digital and AI infrastructure in the world. NTT DATA is part of NTT Group\, which invests over $3.6 billion each year in R&D to help organizations and society move confidently and sustainably into the digital future. Learn more at nttdata.com URL:https://bdionline.com/event/102225/ LOCATION:Fin & Fino\, 135 Levine Avenue of the Arts\, Charlotte\, NC\, 28202\, United States CATEGORIES:Event Calendar,No Header ATTACH;FMTTYPE=image/webp:https://bdionline.com/wp-content/uploads/2025/08/EquinixCharlotteFeaturedImage.webp END:VEVENT BEGIN:VEVENT DTSTART;TZID=America/New_York:20251021T173000 DTEND;TZID=America/New_York:20251021T200000 DTSTAMP:20260416T140750 CREATED:20260108T200720Z LAST-MODIFIED:20260127T193616Z UID:118393-1761067800-1761076800@bdionline.com SUMMARY:Event Recap : Finance & ERP Transformation in the Age of Gen AI: Driving Innovation\, Governance\, and Change DESCRIPTION:Event Recap: From Disruption to Advantage: AI-Powered Resilience in Supply Chains \n \n \n \n Rosemont\, IL | Gibsons Rosemont | November 13\, 2025 \n \n \n \n \n \n \n \n \n \n \n \n Speakers \n \n \n \n \n \n \n \n \n \n \n \n \n Ron Gilson \n \n \n NTT DATA Business Solutions \n \n \n \n \n \n \n \n Executive Advisor and Principal - Consumer Products and Agribusiness \n \n \n \n \n \n LinkedIn \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n John Buckley \n \n \n SAP \n \n \n \n \n \n \n \n Consumer Products Industry Advisor - Midwest Region \n \n \n \n \n \n LinkedIn \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Sai Simhadri \n \n \n Pampered Chef \n \n \n \n \n \n \n \n Senior Data Architect Manager \n \n \n \n \n \n LinkedIn \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Jody McDonough \n \n \n Sub-Zero Group\, Inc. \n \n \n \n \n \n \n \n VP of IT / CIO \n \n \n \n \n \n LinkedIn \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Executive SummaryEnterprise leaders described a clear shift in how supply chains\, operations\, and core business processes are being managed in an era defined by constant disruption. Resilience is no longer treated as a one-time corrective response to global shocks; it is becoming a permanent design principle. Organizations are rebalancing long-standing cost-optimization models with the need for flexibility\, visibility\, and faster decision-making across suppliers\, manufacturing\, logistics\, and service networks. The discussion highlighted that disruptions—geopolitical\, regulatory\, labor-related\, or demand-driven—are now expected\, not exceptional. AI emerged as an enabler rather than a starting point. Executives consistently emphasized that value comes from applying AI to clearly defined business problems\, supported by digitized\, high-quality data and integrated processes. Rather than pursuing broad or experimental AI initiatives\, leaders are embedding intelligence directly into core workflows such as demand planning\, transportation optimization\, supplier collaboration\, and service operations. The organizations seeing results are those that treat AI as a practical extension of operational discipline\, not a replacement for it. Looking forward\, competitive advantage will come from execution speed and adaptability. Companies that can move to “Plan B” faster—through scenario planning\, data transparency\, and orchestrated decision-making—are better positioned to turn disruption into opportunity. AI\, when grounded in clean data and governed processes\, is becoming a force multiplier for cost control\, service consistency\, and supply chain resilience. \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Key Themes \n \n \n \n Key Themes \n \n \n \n \n\n\n \n \n Resilience as a core operating model.\n Supply chain disruptions are now continuous. Organizations are redesigning processes to absorb shocks and respond dynamically\, rather than optimizing solely for steady-state efficiency.\n \n\n \n Cost pressure returning to the forefront.\n After a period dominated by availability and service\, cost optimization is re-emerging as a priority due to inflation\, tariffs\, and consumer resistance to price increases.\n \n\n \n Data readiness before AI adoption.\n AI effectiveness depends on digitized\, accurate\, and integrated data. Many organizations are still focused on building reliable data pipelines before scaling advanced analytics or AI agents.\n \n\n \n Targeted\, use-case-driven AI.\n The most successful AI initiatives are narrowly scoped and tied to measurable outcomes—such as freight optimization\, packaging efficiency\, demand sensing\, or service-part prediction.\n \n\n \n From deterministic models to agent-based intelligence.\n Enterprises are evolving from rule-based and deterministic planning models toward multi-agent AI systems that collaborate across functions while retaining human oversight.\n \n \n\n Read more\n\n\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Actionable Takeaways for Enterprise Leaders\n \n \n \n \n Actionable Takeaways for Enterprise Leaders\n \n \n \n \n \n \n \n Design for disruption\, not stability.\n Assume supply chain shocks will continue. Build operating models that prioritize flexibility\, scenario planning\, and rapid reconfiguration.\n \n\n \n Refocus AI initiatives on core processes.\n Start with finance\, procurement\, supply planning\, logistics\, and service workflows where inefficiencies are well understood and ROI can be measured.\n \n\n \n Digitize end-to-end before scaling AI.\n Eliminate paper\, manual handoffs\, and siloed systems. AI delivers value only when underlying processes and data are fully digitized.\n \n\n \n Balance cost optimization with resilience.\n Evaluate sourcing\, manufacturing\, and logistics decisions through both cost and risk lenses to avoid trading short-term savings for long-term fragility.\n \n\n \n Adopt AI incrementally with governance.\n Deploy AI agents in constrained domains\, monitor performance\, and introduce human review where error tolerance is low.\n \n\n \n Strengthen supplier and partner integration.\n Increase real-time data sharing and visibility across supplier networks to detect quality\, capacity\, and delivery risks earlier.\n \n\n \n Use AI to accelerate decision speed\, not just insight.\n Prioritize applications that reduce manual effort and compress decision cycles\, enabling faster execution when conditions change.\n \n \n\n Read more\n\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n EVENT PHOTOS  \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Sponsors \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n NTT DATA is a $30+ billion trusted global innovator of business and technology services. We serve 75% of the Fortune Global 100 and are committed to helping clients innovate\, optimize and transform for long-term success. As a Global Top Employer\, we have experts in more than 50 countries and a robust partner ecosystem of established and startup companies. Our services include business and technology consulting\, data and artificial intelligence\, industry solutions\, as well as the development\, implementation and management of applications\, infrastructure and connectivity. We are also one of the leading providers of digital and AI infrastructure in the world. NTT DATA is part of NTT Group\, which invests over $3.6 billion each year in R&D to help organizations and society move confidently and sustainably into the digital future. Learn more at nttdata.com URL:https://bdionline.com/event/102125_sap_protiviti_event_recap/ LOCATION:Oceana\, 120 W 49th St\, New York\, NY\, 10020\, United States CATEGORIES:Event Recap,No Header ATTACH;FMTTYPE=image/png:https://bdionline.com/wp-content/uploads/2025/08/protiviti-flipped.png END:VEVENT BEGIN:VEVENT DTSTART;TZID=America/New_York:20251021T173000 DTEND;TZID=America/New_York:20251021T200000 DTSTAMP:20260416T140750 CREATED:20250825T182434Z LAST-MODIFIED:20260203T172344Z UID:115243-1761067800-1761076800@bdionline.com SUMMARY:GenAI Roundtable for Enterprise Innovation - An Executive Dinner & Wine Tasting for Technology Leaders DESCRIPTION:Event Recap: From Disruption to Advantage: AI-Powered Resilience in Supply Chains \n \n \n \n Rosemont\, IL | Gibsons Rosemont | November 13\, 2025 \n \n \n \n \n \n \n \n \n \n \n \n Speakers \n \n \n \n \n \n \n \n \n \n \n \n \n Ron Gilson \n \n \n NTT DATA Business Solutions \n \n \n \n \n \n \n \n Executive Advisor and Principal - Consumer Products and Agribusiness \n \n \n \n \n \n LinkedIn \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n John Buckley \n \n \n SAP \n \n \n \n \n \n \n \n Consumer Products Industry Advisor - Midwest Region \n \n \n \n \n \n LinkedIn \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Sai Simhadri \n \n \n Pampered Chef \n \n \n \n \n \n \n \n Senior Data Architect Manager \n \n \n \n \n \n LinkedIn \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Jody McDonough \n \n \n Sub-Zero Group\, Inc. \n \n \n \n \n \n \n \n VP of IT / CIO \n \n \n \n \n \n LinkedIn \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Executive SummaryEnterprise leaders described a clear shift in how supply chains\, operations\, and core business processes are being managed in an era defined by constant disruption. Resilience is no longer treated as a one-time corrective response to global shocks; it is becoming a permanent design principle. Organizations are rebalancing long-standing cost-optimization models with the need for flexibility\, visibility\, and faster decision-making across suppliers\, manufacturing\, logistics\, and service networks. The discussion highlighted that disruptions—geopolitical\, regulatory\, labor-related\, or demand-driven—are now expected\, not exceptional. AI emerged as an enabler rather than a starting point. Executives consistently emphasized that value comes from applying AI to clearly defined business problems\, supported by digitized\, high-quality data and integrated processes. Rather than pursuing broad or experimental AI initiatives\, leaders are embedding intelligence directly into core workflows such as demand planning\, transportation optimization\, supplier collaboration\, and service operations. The organizations seeing results are those that treat AI as a practical extension of operational discipline\, not a replacement for it. Looking forward\, competitive advantage will come from execution speed and adaptability. Companies that can move to “Plan B” faster—through scenario planning\, data transparency\, and orchestrated decision-making—are better positioned to turn disruption into opportunity. AI\, when grounded in clean data and governed processes\, is becoming a force multiplier for cost control\, service consistency\, and supply chain resilience. \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Key Themes \n \n \n \n Key Themes \n \n \n \n \n\n\n \n \n Resilience as a core operating model.\n Supply chain disruptions are now continuous. Organizations are redesigning processes to absorb shocks and respond dynamically\, rather than optimizing solely for steady-state efficiency.\n \n\n \n Cost pressure returning to the forefront.\n After a period dominated by availability and service\, cost optimization is re-emerging as a priority due to inflation\, tariffs\, and consumer resistance to price increases.\n \n\n \n Data readiness before AI adoption.\n AI effectiveness depends on digitized\, accurate\, and integrated data. Many organizations are still focused on building reliable data pipelines before scaling advanced analytics or AI agents.\n \n\n \n Targeted\, use-case-driven AI.\n The most successful AI initiatives are narrowly scoped and tied to measurable outcomes—such as freight optimization\, packaging efficiency\, demand sensing\, or service-part prediction.\n \n\n \n From deterministic models to agent-based intelligence.\n Enterprises are evolving from rule-based and deterministic planning models toward multi-agent AI systems that collaborate across functions while retaining human oversight.\n \n \n\n Read more\n\n\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Actionable Takeaways for Enterprise Leaders\n \n \n \n \n Actionable Takeaways for Enterprise Leaders\n \n \n \n \n \n \n \n Design for disruption\, not stability.\n Assume supply chain shocks will continue. Build operating models that prioritize flexibility\, scenario planning\, and rapid reconfiguration.\n \n\n \n Refocus AI initiatives on core processes.\n Start with finance\, procurement\, supply planning\, logistics\, and service workflows where inefficiencies are well understood and ROI can be measured.\n \n\n \n Digitize end-to-end before scaling AI.\n Eliminate paper\, manual handoffs\, and siloed systems. AI delivers value only when underlying processes and data are fully digitized.\n \n\n \n Balance cost optimization with resilience.\n Evaluate sourcing\, manufacturing\, and logistics decisions through both cost and risk lenses to avoid trading short-term savings for long-term fragility.\n \n\n \n Adopt AI incrementally with governance.\n Deploy AI agents in constrained domains\, monitor performance\, and introduce human review where error tolerance is low.\n \n\n \n Strengthen supplier and partner integration.\n Increase real-time data sharing and visibility across supplier networks to detect quality\, capacity\, and delivery risks earlier.\n \n\n \n Use AI to accelerate decision speed\, not just insight.\n Prioritize applications that reduce manual effort and compress decision cycles\, enabling faster execution when conditions change.\n \n \n\n Read more\n\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n EVENT PHOTOS  \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Sponsors \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n NTT DATA is a $30+ billion trusted global innovator of business and technology services. We serve 75% of the Fortune Global 100 and are committed to helping clients innovate\, optimize and transform for long-term success. As a Global Top Employer\, we have experts in more than 50 countries and a robust partner ecosystem of established and startup companies. Our services include business and technology consulting\, data and artificial intelligence\, industry solutions\, as well as the development\, implementation and management of applications\, infrastructure and connectivity. We are also one of the leading providers of digital and AI infrastructure in the world. NTT DATA is part of NTT Group\, which invests over $3.6 billion each year in R&D to help organizations and society move confidently and sustainably into the digital future. Learn more at nttdata.com URL:https://bdionline.com/event/102125amd/ LOCATION:Black & Blue\, 130 King St W\, Toronto\, ON M5X 2A2\, Canada\, Toronto\, ON\, Canada CATEGORIES:Event Calendar,No Header ATTACH;FMTTYPE=image/webp:https://bdionline.com/wp-content/uploads/2025/08/AMDTORONTOfeaturedimage2.webp END:VEVENT BEGIN:VEVENT DTSTART;TZID=America/New_York:20251021T173000 DTEND;TZID=America/New_York:20251021T200000 DTSTAMP:20260416T140750 CREATED:20250818T181707Z LAST-MODIFIED:20260203T172347Z UID:114752-1761067800-1761076800@bdionline.com SUMMARY:Finance & ERP Transformation in the Age of Gen AI: Driving Innovation\, Governance\, and Change DESCRIPTION:Event Recap: From Disruption to Advantage: AI-Powered Resilience in Supply Chains \n \n \n \n Rosemont\, IL | Gibsons Rosemont | November 13\, 2025 \n \n \n \n \n \n \n \n \n \n \n \n Speakers \n \n \n \n \n \n \n \n \n \n \n \n \n Ron Gilson \n \n \n NTT DATA Business Solutions \n \n \n \n \n \n \n \n Executive Advisor and Principal - Consumer Products and Agribusiness \n \n \n \n \n \n LinkedIn \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n John Buckley \n \n \n SAP \n \n \n \n \n \n \n \n Consumer Products Industry Advisor - Midwest Region \n \n \n \n \n \n LinkedIn \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Sai Simhadri \n \n \n Pampered Chef \n \n \n \n \n \n \n \n Senior Data Architect Manager \n \n \n \n \n \n LinkedIn \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Jody McDonough \n \n \n Sub-Zero Group\, Inc. \n \n \n \n \n \n \n \n VP of IT / CIO \n \n \n \n \n \n LinkedIn \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Executive SummaryEnterprise leaders described a clear shift in how supply chains\, operations\, and core business processes are being managed in an era defined by constant disruption. Resilience is no longer treated as a one-time corrective response to global shocks; it is becoming a permanent design principle. Organizations are rebalancing long-standing cost-optimization models with the need for flexibility\, visibility\, and faster decision-making across suppliers\, manufacturing\, logistics\, and service networks. The discussion highlighted that disruptions—geopolitical\, regulatory\, labor-related\, or demand-driven—are now expected\, not exceptional. AI emerged as an enabler rather than a starting point. Executives consistently emphasized that value comes from applying AI to clearly defined business problems\, supported by digitized\, high-quality data and integrated processes. Rather than pursuing broad or experimental AI initiatives\, leaders are embedding intelligence directly into core workflows such as demand planning\, transportation optimization\, supplier collaboration\, and service operations. The organizations seeing results are those that treat AI as a practical extension of operational discipline\, not a replacement for it. Looking forward\, competitive advantage will come from execution speed and adaptability. Companies that can move to “Plan B” faster—through scenario planning\, data transparency\, and orchestrated decision-making—are better positioned to turn disruption into opportunity. AI\, when grounded in clean data and governed processes\, is becoming a force multiplier for cost control\, service consistency\, and supply chain resilience. \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Key Themes \n \n \n \n Key Themes \n \n \n \n \n\n\n \n \n Resilience as a core operating model.\n Supply chain disruptions are now continuous. Organizations are redesigning processes to absorb shocks and respond dynamically\, rather than optimizing solely for steady-state efficiency.\n \n\n \n Cost pressure returning to the forefront.\n After a period dominated by availability and service\, cost optimization is re-emerging as a priority due to inflation\, tariffs\, and consumer resistance to price increases.\n \n\n \n Data readiness before AI adoption.\n AI effectiveness depends on digitized\, accurate\, and integrated data. Many organizations are still focused on building reliable data pipelines before scaling advanced analytics or AI agents.\n \n\n \n Targeted\, use-case-driven AI.\n The most successful AI initiatives are narrowly scoped and tied to measurable outcomes—such as freight optimization\, packaging efficiency\, demand sensing\, or service-part prediction.\n \n\n \n From deterministic models to agent-based intelligence.\n Enterprises are evolving from rule-based and deterministic planning models toward multi-agent AI systems that collaborate across functions while retaining human oversight.\n \n \n\n Read more\n\n\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Actionable Takeaways for Enterprise Leaders\n \n \n \n \n Actionable Takeaways for Enterprise Leaders\n \n \n \n \n \n \n \n Design for disruption\, not stability.\n Assume supply chain shocks will continue. Build operating models that prioritize flexibility\, scenario planning\, and rapid reconfiguration.\n \n\n \n Refocus AI initiatives on core processes.\n Start with finance\, procurement\, supply planning\, logistics\, and service workflows where inefficiencies are well understood and ROI can be measured.\n \n\n \n Digitize end-to-end before scaling AI.\n Eliminate paper\, manual handoffs\, and siloed systems. AI delivers value only when underlying processes and data are fully digitized.\n \n\n \n Balance cost optimization with resilience.\n Evaluate sourcing\, manufacturing\, and logistics decisions through both cost and risk lenses to avoid trading short-term savings for long-term fragility.\n \n\n \n Adopt AI incrementally with governance.\n Deploy AI agents in constrained domains\, monitor performance\, and introduce human review where error tolerance is low.\n \n\n \n Strengthen supplier and partner integration.\n Increase real-time data sharing and visibility across supplier networks to detect quality\, capacity\, and delivery risks earlier.\n \n\n \n Use AI to accelerate decision speed\, not just insight.\n Prioritize applications that reduce manual effort and compress decision cycles\, enabling faster execution when conditions change.\n \n \n\n Read more\n\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n EVENT PHOTOS  \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Sponsors \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n NTT DATA is a $30+ billion trusted global innovator of business and technology services. We serve 75% of the Fortune Global 100 and are committed to helping clients innovate\, optimize and transform for long-term success. As a Global Top Employer\, we have experts in more than 50 countries and a robust partner ecosystem of established and startup companies. Our services include business and technology consulting\, data and artificial intelligence\, industry solutions\, as well as the development\, implementation and management of applications\, infrastructure and connectivity. We are also one of the leading providers of digital and AI infrastructure in the world. NTT DATA is part of NTT Group\, which invests over $3.6 billion each year in R&D to help organizations and society move confidently and sustainably into the digital future. Learn more at nttdata.com URL:https://bdionline.com/event/102125/ LOCATION:Oceana\, 120 W 49th St\, New York\, NY\, 10020\, United States CATEGORIES:Event Calendar,No Header ATTACH;FMTTYPE=image/png:https://bdionline.com/wp-content/uploads/2025/08/protiviti-flipped.png END:VEVENT BEGIN:VEVENT DTSTART;TZID=America/Los_Angeles:20251016T120000 DTEND;TZID=America/Los_Angeles:20251016T140000 DTSTAMP:20260416T140750 CREATED:20260112T184810Z LAST-MODIFIED:20260127T190638Z UID:118685-1760616000-1760623200@bdionline.com SUMMARY:Event Recap: The Enterprise Compute Advantage: Enabling Agentic AI DESCRIPTION:Event Recap: From Disruption to Advantage: AI-Powered Resilience in Supply Chains \n \n \n \n Rosemont\, IL | Gibsons Rosemont | November 13\, 2025 \n \n \n \n \n \n \n \n \n \n \n \n Speakers \n \n \n \n \n \n \n \n \n \n \n \n \n Ron Gilson \n \n \n NTT DATA Business Solutions \n \n \n \n \n \n \n \n Executive Advisor and Principal - Consumer Products and Agribusiness \n \n \n \n \n \n LinkedIn \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n John Buckley \n \n \n SAP \n \n \n \n \n \n \n \n Consumer Products Industry Advisor - Midwest Region \n \n \n \n \n \n LinkedIn \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Sai Simhadri \n \n \n Pampered Chef \n \n \n \n \n \n \n \n Senior Data Architect Manager \n \n \n \n \n \n LinkedIn \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Jody McDonough \n \n \n Sub-Zero Group\, Inc. \n \n \n \n \n \n \n \n VP of IT / CIO \n \n \n \n \n \n LinkedIn \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Executive SummaryEnterprise leaders described a clear shift in how supply chains\, operations\, and core business processes are being managed in an era defined by constant disruption. Resilience is no longer treated as a one-time corrective response to global shocks; it is becoming a permanent design principle. Organizations are rebalancing long-standing cost-optimization models with the need for flexibility\, visibility\, and faster decision-making across suppliers\, manufacturing\, logistics\, and service networks. The discussion highlighted that disruptions—geopolitical\, regulatory\, labor-related\, or demand-driven—are now expected\, not exceptional. AI emerged as an enabler rather than a starting point. Executives consistently emphasized that value comes from applying AI to clearly defined business problems\, supported by digitized\, high-quality data and integrated processes. Rather than pursuing broad or experimental AI initiatives\, leaders are embedding intelligence directly into core workflows such as demand planning\, transportation optimization\, supplier collaboration\, and service operations. The organizations seeing results are those that treat AI as a practical extension of operational discipline\, not a replacement for it. Looking forward\, competitive advantage will come from execution speed and adaptability. Companies that can move to “Plan B” faster—through scenario planning\, data transparency\, and orchestrated decision-making—are better positioned to turn disruption into opportunity. AI\, when grounded in clean data and governed processes\, is becoming a force multiplier for cost control\, service consistency\, and supply chain resilience. \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Key Themes \n \n \n \n Key Themes \n \n \n \n \n\n\n \n \n Resilience as a core operating model.\n Supply chain disruptions are now continuous. Organizations are redesigning processes to absorb shocks and respond dynamically\, rather than optimizing solely for steady-state efficiency.\n \n\n \n Cost pressure returning to the forefront.\n After a period dominated by availability and service\, cost optimization is re-emerging as a priority due to inflation\, tariffs\, and consumer resistance to price increases.\n \n\n \n Data readiness before AI adoption.\n AI effectiveness depends on digitized\, accurate\, and integrated data. Many organizations are still focused on building reliable data pipelines before scaling advanced analytics or AI agents.\n \n\n \n Targeted\, use-case-driven AI.\n The most successful AI initiatives are narrowly scoped and tied to measurable outcomes—such as freight optimization\, packaging efficiency\, demand sensing\, or service-part prediction.\n \n\n \n From deterministic models to agent-based intelligence.\n Enterprises are evolving from rule-based and deterministic planning models toward multi-agent AI systems that collaborate across functions while retaining human oversight.\n \n \n\n Read more\n\n\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Actionable Takeaways for Enterprise Leaders\n \n \n \n \n Actionable Takeaways for Enterprise Leaders\n \n \n \n \n \n \n \n Design for disruption\, not stability.\n Assume supply chain shocks will continue. Build operating models that prioritize flexibility\, scenario planning\, and rapid reconfiguration.\n \n\n \n Refocus AI initiatives on core processes.\n Start with finance\, procurement\, supply planning\, logistics\, and service workflows where inefficiencies are well understood and ROI can be measured.\n \n\n \n Digitize end-to-end before scaling AI.\n Eliminate paper\, manual handoffs\, and siloed systems. AI delivers value only when underlying processes and data are fully digitized.\n \n\n \n Balance cost optimization with resilience.\n Evaluate sourcing\, manufacturing\, and logistics decisions through both cost and risk lenses to avoid trading short-term savings for long-term fragility.\n \n\n \n Adopt AI incrementally with governance.\n Deploy AI agents in constrained domains\, monitor performance\, and introduce human review where error tolerance is low.\n \n\n \n Strengthen supplier and partner integration.\n Increase real-time data sharing and visibility across supplier networks to detect quality\, capacity\, and delivery risks earlier.\n \n\n \n Use AI to accelerate decision speed\, not just insight.\n Prioritize applications that reduce manual effort and compress decision cycles\, enabling faster execution when conditions change.\n \n \n\n Read more\n\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n EVENT PHOTOS  \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Sponsors \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n NTT DATA is a $30+ billion trusted global innovator of business and technology services. We serve 75% of the Fortune Global 100 and are committed to helping clients innovate\, optimize and transform for long-term success. As a Global Top Employer\, we have experts in more than 50 countries and a robust partner ecosystem of established and startup companies. Our services include business and technology consulting\, data and artificial intelligence\, industry solutions\, as well as the development\, implementation and management of applications\, infrastructure and connectivity. We are also one of the leading providers of digital and AI infrastructure in the world. NTT DATA is part of NTT Group\, which invests over $3.6 billion each year in R&D to help organizations and society move confidently and sustainably into the digital future. Learn more at nttdata.com URL:https://bdionline.com/event/101625_hpe_event_recap/ LOCATION:Taverna\, 800 Emerson St\, Palo Alto\, CA\, 94301\, United States CATEGORIES:Event Recap,No Header ATTACH;FMTTYPE=image/png:https://bdionline.com/wp-content/uploads/2025/08/Untitled-1.png END:VEVENT BEGIN:VEVENT DTSTART;TZID=America/New_York:20251016T120000 DTEND;TZID=America/New_York:20251016T140000 DTSTAMP:20260416T140750 CREATED:20250820T192739Z LAST-MODIFIED:20260203T172348Z UID:115002-1760616000-1760623200@bdionline.com SUMMARY:The Enterprise Compute Advantage: Enabling Agentic AI DESCRIPTION:Event Recap: From Disruption to Advantage: AI-Powered Resilience in Supply Chains \n \n \n \n Rosemont\, IL | Gibsons Rosemont | November 13\, 2025 \n \n \n \n \n \n \n \n \n \n \n \n Speakers \n \n \n \n \n \n \n \n \n \n \n \n \n Ron Gilson \n \n \n NTT DATA Business Solutions \n \n \n \n \n \n \n \n Executive Advisor and Principal - Consumer Products and Agribusiness \n \n \n \n \n \n LinkedIn \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n John Buckley \n \n \n SAP \n \n \n \n \n \n \n \n Consumer Products Industry Advisor - Midwest Region \n \n \n \n \n \n LinkedIn \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Sai Simhadri \n \n \n Pampered Chef \n \n \n \n \n \n \n \n Senior Data Architect Manager \n \n \n \n \n \n LinkedIn \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Jody McDonough \n \n \n Sub-Zero Group\, Inc. \n \n \n \n \n \n \n \n VP of IT / CIO \n \n \n \n \n \n LinkedIn \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Executive SummaryEnterprise leaders described a clear shift in how supply chains\, operations\, and core business processes are being managed in an era defined by constant disruption. Resilience is no longer treated as a one-time corrective response to global shocks; it is becoming a permanent design principle. Organizations are rebalancing long-standing cost-optimization models with the need for flexibility\, visibility\, and faster decision-making across suppliers\, manufacturing\, logistics\, and service networks. The discussion highlighted that disruptions—geopolitical\, regulatory\, labor-related\, or demand-driven—are now expected\, not exceptional. AI emerged as an enabler rather than a starting point. Executives consistently emphasized that value comes from applying AI to clearly defined business problems\, supported by digitized\, high-quality data and integrated processes. Rather than pursuing broad or experimental AI initiatives\, leaders are embedding intelligence directly into core workflows such as demand planning\, transportation optimization\, supplier collaboration\, and service operations. The organizations seeing results are those that treat AI as a practical extension of operational discipline\, not a replacement for it. Looking forward\, competitive advantage will come from execution speed and adaptability. Companies that can move to “Plan B” faster—through scenario planning\, data transparency\, and orchestrated decision-making—are better positioned to turn disruption into opportunity. AI\, when grounded in clean data and governed processes\, is becoming a force multiplier for cost control\, service consistency\, and supply chain resilience. \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Key Themes \n \n \n \n Key Themes \n \n \n \n \n\n\n \n \n Resilience as a core operating model.\n Supply chain disruptions are now continuous. Organizations are redesigning processes to absorb shocks and respond dynamically\, rather than optimizing solely for steady-state efficiency.\n \n\n \n Cost pressure returning to the forefront.\n After a period dominated by availability and service\, cost optimization is re-emerging as a priority due to inflation\, tariffs\, and consumer resistance to price increases.\n \n\n \n Data readiness before AI adoption.\n AI effectiveness depends on digitized\, accurate\, and integrated data. Many organizations are still focused on building reliable data pipelines before scaling advanced analytics or AI agents.\n \n\n \n Targeted\, use-case-driven AI.\n The most successful AI initiatives are narrowly scoped and tied to measurable outcomes—such as freight optimization\, packaging efficiency\, demand sensing\, or service-part prediction.\n \n\n \n From deterministic models to agent-based intelligence.\n Enterprises are evolving from rule-based and deterministic planning models toward multi-agent AI systems that collaborate across functions while retaining human oversight.\n \n \n\n Read more\n\n\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Actionable Takeaways for Enterprise Leaders\n \n \n \n \n Actionable Takeaways for Enterprise Leaders\n \n \n \n \n \n \n \n Design for disruption\, not stability.\n Assume supply chain shocks will continue. Build operating models that prioritize flexibility\, scenario planning\, and rapid reconfiguration.\n \n\n \n Refocus AI initiatives on core processes.\n Start with finance\, procurement\, supply planning\, logistics\, and service workflows where inefficiencies are well understood and ROI can be measured.\n \n\n \n Digitize end-to-end before scaling AI.\n Eliminate paper\, manual handoffs\, and siloed systems. AI delivers value only when underlying processes and data are fully digitized.\n \n\n \n Balance cost optimization with resilience.\n Evaluate sourcing\, manufacturing\, and logistics decisions through both cost and risk lenses to avoid trading short-term savings for long-term fragility.\n \n\n \n Adopt AI incrementally with governance.\n Deploy AI agents in constrained domains\, monitor performance\, and introduce human review where error tolerance is low.\n \n\n \n Strengthen supplier and partner integration.\n Increase real-time data sharing and visibility across supplier networks to detect quality\, capacity\, and delivery risks earlier.\n \n\n \n Use AI to accelerate decision speed\, not just insight.\n Prioritize applications that reduce manual effort and compress decision cycles\, enabling faster execution when conditions change.\n \n \n\n Read more\n\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n EVENT PHOTOS  \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Sponsors \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n NTT DATA is a $30+ billion trusted global innovator of business and technology services. We serve 75% of the Fortune Global 100 and are committed to helping clients innovate\, optimize and transform for long-term success. As a Global Top Employer\, we have experts in more than 50 countries and a robust partner ecosystem of established and startup companies. Our services include business and technology consulting\, data and artificial intelligence\, industry solutions\, as well as the development\, implementation and management of applications\, infrastructure and connectivity. We are also one of the leading providers of digital and AI infrastructure in the world. NTT DATA is part of NTT Group\, which invests over $3.6 billion each year in R&D to help organizations and society move confidently and sustainably into the digital future. Learn more at nttdata.com URL:https://bdionline.com/event/101625/ LOCATION:Taverna\, 800 Emerson St\, Palo Alto\, CA\, 94301\, United States CATEGORIES:Event Calendar,No Header ATTACH;FMTTYPE=image/png:https://bdionline.com/wp-content/uploads/2025/08/Untitled-1.png END:VEVENT BEGIN:VEVENT DTSTART;TZID=America/New_York:20251015T173000 DTEND;TZID=America/New_York:20251015T200000 DTSTAMP:20260416T140751 CREATED:20250813T204444Z LAST-MODIFIED:20260203T172349Z UID:114672-1760549400-1760558400@bdionline.com SUMMARY:GenAI Roundtable For Enterprise Innovation - An Executive Dinner & Wine Tasting For Technology Leaders DESCRIPTION:Event Recap: From Disruption to Advantage: AI-Powered Resilience in Supply Chains \n \n \n \n Rosemont\, IL | Gibsons Rosemont | November 13\, 2025 \n \n \n \n \n \n \n \n \n \n \n \n Speakers \n \n \n \n \n \n \n \n \n \n \n \n \n Ron Gilson \n \n \n NTT DATA Business Solutions \n \n \n \n \n \n \n \n Executive Advisor and Principal - Consumer Products and Agribusiness \n \n \n \n \n \n LinkedIn \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n John Buckley \n \n \n SAP \n \n \n \n \n \n \n \n Consumer Products Industry Advisor - Midwest Region \n \n \n \n \n \n LinkedIn \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Sai Simhadri \n \n \n Pampered Chef \n \n \n \n \n \n \n \n Senior Data Architect Manager \n \n \n \n \n \n LinkedIn \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Jody McDonough \n \n \n Sub-Zero Group\, Inc. \n \n \n \n \n \n \n \n VP of IT / CIO \n \n \n \n \n \n LinkedIn \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Executive SummaryEnterprise leaders described a clear shift in how supply chains\, operations\, and core business processes are being managed in an era defined by constant disruption. Resilience is no longer treated as a one-time corrective response to global shocks; it is becoming a permanent design principle. Organizations are rebalancing long-standing cost-optimization models with the need for flexibility\, visibility\, and faster decision-making across suppliers\, manufacturing\, logistics\, and service networks. The discussion highlighted that disruptions—geopolitical\, regulatory\, labor-related\, or demand-driven—are now expected\, not exceptional. AI emerged as an enabler rather than a starting point. Executives consistently emphasized that value comes from applying AI to clearly defined business problems\, supported by digitized\, high-quality data and integrated processes. Rather than pursuing broad or experimental AI initiatives\, leaders are embedding intelligence directly into core workflows such as demand planning\, transportation optimization\, supplier collaboration\, and service operations. The organizations seeing results are those that treat AI as a practical extension of operational discipline\, not a replacement for it. Looking forward\, competitive advantage will come from execution speed and adaptability. Companies that can move to “Plan B” faster—through scenario planning\, data transparency\, and orchestrated decision-making—are better positioned to turn disruption into opportunity. AI\, when grounded in clean data and governed processes\, is becoming a force multiplier for cost control\, service consistency\, and supply chain resilience. \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Key Themes \n \n \n \n Key Themes \n \n \n \n \n\n\n \n \n Resilience as a core operating model.\n Supply chain disruptions are now continuous. Organizations are redesigning processes to absorb shocks and respond dynamically\, rather than optimizing solely for steady-state efficiency.\n \n\n \n Cost pressure returning to the forefront.\n After a period dominated by availability and service\, cost optimization is re-emerging as a priority due to inflation\, tariffs\, and consumer resistance to price increases.\n \n\n \n Data readiness before AI adoption.\n AI effectiveness depends on digitized\, accurate\, and integrated data. Many organizations are still focused on building reliable data pipelines before scaling advanced analytics or AI agents.\n \n\n \n Targeted\, use-case-driven AI.\n The most successful AI initiatives are narrowly scoped and tied to measurable outcomes—such as freight optimization\, packaging efficiency\, demand sensing\, or service-part prediction.\n \n\n \n From deterministic models to agent-based intelligence.\n Enterprises are evolving from rule-based and deterministic planning models toward multi-agent AI systems that collaborate across functions while retaining human oversight.\n \n \n\n Read more\n\n\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Actionable Takeaways for Enterprise Leaders\n \n \n \n \n Actionable Takeaways for Enterprise Leaders\n \n \n \n \n \n \n \n Design for disruption\, not stability.\n Assume supply chain shocks will continue. Build operating models that prioritize flexibility\, scenario planning\, and rapid reconfiguration.\n \n\n \n Refocus AI initiatives on core processes.\n Start with finance\, procurement\, supply planning\, logistics\, and service workflows where inefficiencies are well understood and ROI can be measured.\n \n\n \n Digitize end-to-end before scaling AI.\n Eliminate paper\, manual handoffs\, and siloed systems. AI delivers value only when underlying processes and data are fully digitized.\n \n\n \n Balance cost optimization with resilience.\n Evaluate sourcing\, manufacturing\, and logistics decisions through both cost and risk lenses to avoid trading short-term savings for long-term fragility.\n \n\n \n Adopt AI incrementally with governance.\n Deploy AI agents in constrained domains\, monitor performance\, and introduce human review where error tolerance is low.\n \n\n \n Strengthen supplier and partner integration.\n Increase real-time data sharing and visibility across supplier networks to detect quality\, capacity\, and delivery risks earlier.\n \n\n \n Use AI to accelerate decision speed\, not just insight.\n Prioritize applications that reduce manual effort and compress decision cycles\, enabling faster execution when conditions change.\n \n \n\n Read more\n\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n EVENT PHOTOS  \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Sponsors \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n NTT DATA is a $30+ billion trusted global innovator of business and technology services. We serve 75% of the Fortune Global 100 and are committed to helping clients innovate\, optimize and transform for long-term success. As a Global Top Employer\, we have experts in more than 50 countries and a robust partner ecosystem of established and startup companies. Our services include business and technology consulting\, data and artificial intelligence\, industry solutions\, as well as the development\, implementation and management of applications\, infrastructure and connectivity. We are also one of the leading providers of digital and AI infrastructure in the world. NTT DATA is part of NTT Group\, which invests over $3.6 billion each year in R&D to help organizations and society move confidently and sustainably into the digital future. Learn more at nttdata.com URL:https://bdionline.com/event/101525/ LOCATION:Fleming’s Prime Steakhouse – Plano\, 7250 Dallas Pkwy Suite 110\, Plano\, TX 75024\, Plano\, TX\, 75024\, United States CATEGORIES:Event Calendar,No Header ATTACH;FMTTYPE=image/png:https://bdionline.com/wp-content/uploads/2025/08/AMD-DALLAS.png END:VEVENT BEGIN:VEVENT DTSTART;TZID=America/Chicago:20251014T173000 DTEND;TZID=America/Chicago:20251014T200000 DTSTAMP:20260416T140751 CREATED:20260112T171910Z LAST-MODIFIED:20260127T200217Z UID:118653-1760463000-1760472000@bdionline.com SUMMARY:Event Recap: The Enterprise Compute Advantage: Enabling Agentic AI DESCRIPTION:Event Recap: From Disruption to Advantage: AI-Powered Resilience in Supply Chains \n \n \n \n Rosemont\, IL | Gibsons Rosemont | November 13\, 2025 \n \n \n \n \n \n \n \n \n \n \n \n Speakers \n \n \n \n \n \n \n \n \n \n \n \n \n Ron Gilson \n \n \n NTT DATA Business Solutions \n \n \n \n \n \n \n \n Executive Advisor and Principal - Consumer Products and Agribusiness \n \n \n \n \n \n LinkedIn \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n John Buckley \n \n \n SAP \n \n \n \n \n \n \n \n Consumer Products Industry Advisor - Midwest Region \n \n \n \n \n \n LinkedIn \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Sai Simhadri \n \n \n Pampered Chef \n \n \n \n \n \n \n \n Senior Data Architect Manager \n \n \n \n \n \n LinkedIn \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Jody McDonough \n \n \n Sub-Zero Group\, Inc. \n \n \n \n \n \n \n \n VP of IT / CIO \n \n \n \n \n \n LinkedIn \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Executive SummaryEnterprise leaders described a clear shift in how supply chains\, operations\, and core business processes are being managed in an era defined by constant disruption. Resilience is no longer treated as a one-time corrective response to global shocks; it is becoming a permanent design principle. Organizations are rebalancing long-standing cost-optimization models with the need for flexibility\, visibility\, and faster decision-making across suppliers\, manufacturing\, logistics\, and service networks. The discussion highlighted that disruptions—geopolitical\, regulatory\, labor-related\, or demand-driven—are now expected\, not exceptional. AI emerged as an enabler rather than a starting point. Executives consistently emphasized that value comes from applying AI to clearly defined business problems\, supported by digitized\, high-quality data and integrated processes. Rather than pursuing broad or experimental AI initiatives\, leaders are embedding intelligence directly into core workflows such as demand planning\, transportation optimization\, supplier collaboration\, and service operations. The organizations seeing results are those that treat AI as a practical extension of operational discipline\, not a replacement for it. Looking forward\, competitive advantage will come from execution speed and adaptability. Companies that can move to “Plan B” faster—through scenario planning\, data transparency\, and orchestrated decision-making—are better positioned to turn disruption into opportunity. AI\, when grounded in clean data and governed processes\, is becoming a force multiplier for cost control\, service consistency\, and supply chain resilience. \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Key Themes \n \n \n \n Key Themes \n \n \n \n \n\n\n \n \n Resilience as a core operating model.\n Supply chain disruptions are now continuous. Organizations are redesigning processes to absorb shocks and respond dynamically\, rather than optimizing solely for steady-state efficiency.\n \n\n \n Cost pressure returning to the forefront.\n After a period dominated by availability and service\, cost optimization is re-emerging as a priority due to inflation\, tariffs\, and consumer resistance to price increases.\n \n\n \n Data readiness before AI adoption.\n AI effectiveness depends on digitized\, accurate\, and integrated data. Many organizations are still focused on building reliable data pipelines before scaling advanced analytics or AI agents.\n \n\n \n Targeted\, use-case-driven AI.\n The most successful AI initiatives are narrowly scoped and tied to measurable outcomes—such as freight optimization\, packaging efficiency\, demand sensing\, or service-part prediction.\n \n\n \n From deterministic models to agent-based intelligence.\n Enterprises are evolving from rule-based and deterministic planning models toward multi-agent AI systems that collaborate across functions while retaining human oversight.\n \n \n\n Read more\n\n\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Actionable Takeaways for Enterprise Leaders\n \n \n \n \n Actionable Takeaways for Enterprise Leaders\n \n \n \n \n \n \n \n Design for disruption\, not stability.\n Assume supply chain shocks will continue. Build operating models that prioritize flexibility\, scenario planning\, and rapid reconfiguration.\n \n\n \n Refocus AI initiatives on core processes.\n Start with finance\, procurement\, supply planning\, logistics\, and service workflows where inefficiencies are well understood and ROI can be measured.\n \n\n \n Digitize end-to-end before scaling AI.\n Eliminate paper\, manual handoffs\, and siloed systems. AI delivers value only when underlying processes and data are fully digitized.\n \n\n \n Balance cost optimization with resilience.\n Evaluate sourcing\, manufacturing\, and logistics decisions through both cost and risk lenses to avoid trading short-term savings for long-term fragility.\n \n\n \n Adopt AI incrementally with governance.\n Deploy AI agents in constrained domains\, monitor performance\, and introduce human review where error tolerance is low.\n \n\n \n Strengthen supplier and partner integration.\n Increase real-time data sharing and visibility across supplier networks to detect quality\, capacity\, and delivery risks earlier.\n \n\n \n Use AI to accelerate decision speed\, not just insight.\n Prioritize applications that reduce manual effort and compress decision cycles\, enabling faster execution when conditions change.\n \n \n\n Read more\n\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n EVENT PHOTOS  \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Sponsors \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n NTT DATA is a $30+ billion trusted global innovator of business and technology services. We serve 75% of the Fortune Global 100 and are committed to helping clients innovate\, optimize and transform for long-term success. As a Global Top Employer\, we have experts in more than 50 countries and a robust partner ecosystem of established and startup companies. Our services include business and technology consulting\, data and artificial intelligence\, industry solutions\, as well as the development\, implementation and management of applications\, infrastructure and connectivity. We are also one of the leading providers of digital and AI infrastructure in the world. NTT DATA is part of NTT Group\, which invests over $3.6 billion each year in R&D to help organizations and society move confidently and sustainably into the digital future. Learn more at nttdata.com URL:https://bdionline.com/event/101425_hpe_event_recap/ LOCATION:Gibsons Rosemont\, 5464 N River Rd\, Rosemont\, IL\, 60018\, United States CATEGORIES:Event Recap,No Header ATTACH;FMTTYPE=image/png:https://bdionline.com/wp-content/uploads/2025/08/chicago.png END:VEVENT BEGIN:VEVENT DTSTART;TZID=America/New_York:20251014T173000 DTEND;TZID=America/New_York:20251014T200000 DTSTAMP:20260416T140751 CREATED:20250820T190322Z LAST-MODIFIED:20260203T172350Z UID:114944-1760463000-1760472000@bdionline.com SUMMARY:The Enterprise Compute Advantage: Enabling Agentic AI DESCRIPTION:Event Recap: From Disruption to Advantage: AI-Powered Resilience in Supply Chains \n \n \n \n Rosemont\, IL | Gibsons Rosemont | November 13\, 2025 \n \n \n \n \n \n \n \n \n \n \n \n Speakers \n \n \n \n \n \n \n \n \n \n \n \n \n Ron Gilson \n \n \n NTT DATA Business Solutions \n \n \n \n \n \n \n \n Executive Advisor and Principal - Consumer Products and Agribusiness \n \n \n \n \n \n LinkedIn \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n John Buckley \n \n \n SAP \n \n \n \n \n \n \n \n Consumer Products Industry Advisor - Midwest Region \n \n \n \n \n \n LinkedIn \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Sai Simhadri \n \n \n Pampered Chef \n \n \n \n \n \n \n \n Senior Data Architect Manager \n \n \n \n \n \n LinkedIn \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Jody McDonough \n \n \n Sub-Zero Group\, Inc. \n \n \n \n \n \n \n \n VP of IT / CIO \n \n \n \n \n \n LinkedIn \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Executive SummaryEnterprise leaders described a clear shift in how supply chains\, operations\, and core business processes are being managed in an era defined by constant disruption. Resilience is no longer treated as a one-time corrective response to global shocks; it is becoming a permanent design principle. Organizations are rebalancing long-standing cost-optimization models with the need for flexibility\, visibility\, and faster decision-making across suppliers\, manufacturing\, logistics\, and service networks. The discussion highlighted that disruptions—geopolitical\, regulatory\, labor-related\, or demand-driven—are now expected\, not exceptional. AI emerged as an enabler rather than a starting point. Executives consistently emphasized that value comes from applying AI to clearly defined business problems\, supported by digitized\, high-quality data and integrated processes. Rather than pursuing broad or experimental AI initiatives\, leaders are embedding intelligence directly into core workflows such as demand planning\, transportation optimization\, supplier collaboration\, and service operations. The organizations seeing results are those that treat AI as a practical extension of operational discipline\, not a replacement for it. Looking forward\, competitive advantage will come from execution speed and adaptability. Companies that can move to “Plan B” faster—through scenario planning\, data transparency\, and orchestrated decision-making—are better positioned to turn disruption into opportunity. AI\, when grounded in clean data and governed processes\, is becoming a force multiplier for cost control\, service consistency\, and supply chain resilience. \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Key Themes \n \n \n \n Key Themes \n \n \n \n \n\n\n \n \n Resilience as a core operating model.\n Supply chain disruptions are now continuous. Organizations are redesigning processes to absorb shocks and respond dynamically\, rather than optimizing solely for steady-state efficiency.\n \n\n \n Cost pressure returning to the forefront.\n After a period dominated by availability and service\, cost optimization is re-emerging as a priority due to inflation\, tariffs\, and consumer resistance to price increases.\n \n\n \n Data readiness before AI adoption.\n AI effectiveness depends on digitized\, accurate\, and integrated data. Many organizations are still focused on building reliable data pipelines before scaling advanced analytics or AI agents.\n \n\n \n Targeted\, use-case-driven AI.\n The most successful AI initiatives are narrowly scoped and tied to measurable outcomes—such as freight optimization\, packaging efficiency\, demand sensing\, or service-part prediction.\n \n\n \n From deterministic models to agent-based intelligence.\n Enterprises are evolving from rule-based and deterministic planning models toward multi-agent AI systems that collaborate across functions while retaining human oversight.\n \n \n\n Read more\n\n\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Actionable Takeaways for Enterprise Leaders\n \n \n \n \n Actionable Takeaways for Enterprise Leaders\n \n \n \n \n \n \n \n Design for disruption\, not stability.\n Assume supply chain shocks will continue. Build operating models that prioritize flexibility\, scenario planning\, and rapid reconfiguration.\n \n\n \n Refocus AI initiatives on core processes.\n Start with finance\, procurement\, supply planning\, logistics\, and service workflows where inefficiencies are well understood and ROI can be measured.\n \n\n \n Digitize end-to-end before scaling AI.\n Eliminate paper\, manual handoffs\, and siloed systems. AI delivers value only when underlying processes and data are fully digitized.\n \n\n \n Balance cost optimization with resilience.\n Evaluate sourcing\, manufacturing\, and logistics decisions through both cost and risk lenses to avoid trading short-term savings for long-term fragility.\n \n\n \n Adopt AI incrementally with governance.\n Deploy AI agents in constrained domains\, monitor performance\, and introduce human review where error tolerance is low.\n \n\n \n Strengthen supplier and partner integration.\n Increase real-time data sharing and visibility across supplier networks to detect quality\, capacity\, and delivery risks earlier.\n \n\n \n Use AI to accelerate decision speed\, not just insight.\n Prioritize applications that reduce manual effort and compress decision cycles\, enabling faster execution when conditions change.\n \n \n\n Read more\n\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n EVENT PHOTOS  \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Sponsors \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n NTT DATA is a $30+ billion trusted global innovator of business and technology services. We serve 75% of the Fortune Global 100 and are committed to helping clients innovate\, optimize and transform for long-term success. As a Global Top Employer\, we have experts in more than 50 countries and a robust partner ecosystem of established and startup companies. Our services include business and technology consulting\, data and artificial intelligence\, industry solutions\, as well as the development\, implementation and management of applications\, infrastructure and connectivity. We are also one of the leading providers of digital and AI infrastructure in the world. NTT DATA is part of NTT Group\, which invests over $3.6 billion each year in R&D to help organizations and society move confidently and sustainably into the digital future. Learn more at nttdata.com URL:https://bdionline.com/event/101425/ LOCATION:Gibsons Rosemont\, 5464 N River Rd\, Rosemont\, IL\, 60018\, United States CATEGORIES:Event Calendar,No Header ATTACH;FMTTYPE=image/png:https://bdionline.com/wp-content/uploads/2025/08/chicago.png END:VEVENT BEGIN:VEVENT DTSTART;TZID=America/New_York:20251009T173000 DTEND;TZID=America/New_York:20251009T200000 DTSTAMP:20260416T140751 CREATED:20250806T192019Z LAST-MODIFIED:20260203T172352Z UID:114529-1760031000-1760040000@bdionline.com SUMMARY:AI at the Core: Powering the Future of Drug Discovery & Manufacturing DESCRIPTION:Event Recap: From Disruption to Advantage: AI-Powered Resilience in Supply Chains \n \n \n \n Rosemont\, IL | Gibsons Rosemont | November 13\, 2025 \n \n \n \n \n \n \n \n \n \n \n \n Speakers \n \n \n \n \n \n \n \n \n \n \n \n \n Ron Gilson \n \n \n NTT DATA Business Solutions \n \n \n \n \n \n \n \n Executive Advisor and Principal - Consumer Products and Agribusiness \n \n \n \n \n \n LinkedIn \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n John Buckley \n \n \n SAP \n \n \n \n \n \n \n \n Consumer Products Industry Advisor - Midwest Region \n \n \n \n \n \n LinkedIn \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Sai Simhadri \n \n \n Pampered Chef \n \n \n \n \n \n \n \n Senior Data Architect Manager \n \n \n \n \n \n LinkedIn \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Jody McDonough \n \n \n Sub-Zero Group\, Inc. \n \n \n \n \n \n \n \n VP of IT / CIO \n \n \n \n \n \n LinkedIn \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Executive SummaryEnterprise leaders described a clear shift in how supply chains\, operations\, and core business processes are being managed in an era defined by constant disruption. Resilience is no longer treated as a one-time corrective response to global shocks; it is becoming a permanent design principle. Organizations are rebalancing long-standing cost-optimization models with the need for flexibility\, visibility\, and faster decision-making across suppliers\, manufacturing\, logistics\, and service networks. The discussion highlighted that disruptions—geopolitical\, regulatory\, labor-related\, or demand-driven—are now expected\, not exceptional. AI emerged as an enabler rather than a starting point. Executives consistently emphasized that value comes from applying AI to clearly defined business problems\, supported by digitized\, high-quality data and integrated processes. Rather than pursuing broad or experimental AI initiatives\, leaders are embedding intelligence directly into core workflows such as demand planning\, transportation optimization\, supplier collaboration\, and service operations. The organizations seeing results are those that treat AI as a practical extension of operational discipline\, not a replacement for it. Looking forward\, competitive advantage will come from execution speed and adaptability. Companies that can move to “Plan B” faster—through scenario planning\, data transparency\, and orchestrated decision-making—are better positioned to turn disruption into opportunity. AI\, when grounded in clean data and governed processes\, is becoming a force multiplier for cost control\, service consistency\, and supply chain resilience. \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Key Themes \n \n \n \n Key Themes \n \n \n \n \n\n\n \n \n Resilience as a core operating model.\n Supply chain disruptions are now continuous. Organizations are redesigning processes to absorb shocks and respond dynamically\, rather than optimizing solely for steady-state efficiency.\n \n\n \n Cost pressure returning to the forefront.\n After a period dominated by availability and service\, cost optimization is re-emerging as a priority due to inflation\, tariffs\, and consumer resistance to price increases.\n \n\n \n Data readiness before AI adoption.\n AI effectiveness depends on digitized\, accurate\, and integrated data. Many organizations are still focused on building reliable data pipelines before scaling advanced analytics or AI agents.\n \n\n \n Targeted\, use-case-driven AI.\n The most successful AI initiatives are narrowly scoped and tied to measurable outcomes—such as freight optimization\, packaging efficiency\, demand sensing\, or service-part prediction.\n \n\n \n From deterministic models to agent-based intelligence.\n Enterprises are evolving from rule-based and deterministic planning models toward multi-agent AI systems that collaborate across functions while retaining human oversight.\n \n \n\n Read more\n\n\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Actionable Takeaways for Enterprise Leaders\n \n \n \n \n Actionable Takeaways for Enterprise Leaders\n \n \n \n \n \n \n \n Design for disruption\, not stability.\n Assume supply chain shocks will continue. Build operating models that prioritize flexibility\, scenario planning\, and rapid reconfiguration.\n \n\n \n Refocus AI initiatives on core processes.\n Start with finance\, procurement\, supply planning\, logistics\, and service workflows where inefficiencies are well understood and ROI can be measured.\n \n\n \n Digitize end-to-end before scaling AI.\n Eliminate paper\, manual handoffs\, and siloed systems. AI delivers value only when underlying processes and data are fully digitized.\n \n\n \n Balance cost optimization with resilience.\n Evaluate sourcing\, manufacturing\, and logistics decisions through both cost and risk lenses to avoid trading short-term savings for long-term fragility.\n \n\n \n Adopt AI incrementally with governance.\n Deploy AI agents in constrained domains\, monitor performance\, and introduce human review where error tolerance is low.\n \n\n \n Strengthen supplier and partner integration.\n Increase real-time data sharing and visibility across supplier networks to detect quality\, capacity\, and delivery risks earlier.\n \n\n \n Use AI to accelerate decision speed\, not just insight.\n Prioritize applications that reduce manual effort and compress decision cycles\, enabling faster execution when conditions change.\n \n \n\n Read more\n\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n EVENT PHOTOS  \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Sponsors \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n NTT DATA is a $30+ billion trusted global innovator of business and technology services. We serve 75% of the Fortune Global 100 and are committed to helping clients innovate\, optimize and transform for long-term success. As a Global Top Employer\, we have experts in more than 50 countries and a robust partner ecosystem of established and startup companies. Our services include business and technology consulting\, data and artificial intelligence\, industry solutions\, as well as the development\, implementation and management of applications\, infrastructure and connectivity. We are also one of the leading providers of digital and AI infrastructure in the world. NTT DATA is part of NTT Group\, which invests over $3.6 billion each year in R&D to help organizations and society move confidently and sustainably into the digital future. Learn more at nttdata.com URL:https://bdionline.com/event/100925/ LOCATION:Toca Vez\, 95 Morristown Rd\, Basking Ridge\, NJ\, 07920\, United States CATEGORIES:Event Calendar,No Header ATTACH;FMTTYPE=image/webp:https://bdionline.com/wp-content/uploads/2025/08/HPE-AMDfeaturedimage.webp END:VEVENT BEGIN:VEVENT DTSTART;TZID=America/New_York:20251008T173000 DTEND;TZID=America/New_York:20251008T200000 DTSTAMP:20260416T140751 CREATED:20250714T164446Z LAST-MODIFIED:20260203T172353Z UID:113757-1759944600-1759953600@bdionline.com SUMMARY:The Future of Enterprise Data Security in the Age of AI DESCRIPTION:Event Recap: From Disruption to Advantage: AI-Powered Resilience in Supply Chains \n \n \n \n Rosemont\, IL | Gibsons Rosemont | November 13\, 2025 \n \n \n \n \n \n \n \n \n \n \n \n Speakers \n \n \n \n \n \n \n \n \n \n \n \n \n Ron Gilson \n \n \n NTT DATA Business Solutions \n \n \n \n \n \n \n \n Executive Advisor and Principal - Consumer Products and Agribusiness \n \n \n \n \n \n LinkedIn \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n John Buckley \n \n \n SAP \n \n \n \n \n \n \n \n Consumer Products Industry Advisor - Midwest Region \n \n \n \n \n \n LinkedIn \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Sai Simhadri \n \n \n Pampered Chef \n \n \n \n \n \n \n \n Senior Data Architect Manager \n \n \n \n \n \n LinkedIn \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Jody McDonough \n \n \n Sub-Zero Group\, Inc. \n \n \n \n \n \n \n \n VP of IT / CIO \n \n \n \n \n \n LinkedIn \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Executive SummaryEnterprise leaders described a clear shift in how supply chains\, operations\, and core business processes are being managed in an era defined by constant disruption. Resilience is no longer treated as a one-time corrective response to global shocks; it is becoming a permanent design principle. Organizations are rebalancing long-standing cost-optimization models with the need for flexibility\, visibility\, and faster decision-making across suppliers\, manufacturing\, logistics\, and service networks. The discussion highlighted that disruptions—geopolitical\, regulatory\, labor-related\, or demand-driven—are now expected\, not exceptional. AI emerged as an enabler rather than a starting point. Executives consistently emphasized that value comes from applying AI to clearly defined business problems\, supported by digitized\, high-quality data and integrated processes. Rather than pursuing broad or experimental AI initiatives\, leaders are embedding intelligence directly into core workflows such as demand planning\, transportation optimization\, supplier collaboration\, and service operations. The organizations seeing results are those that treat AI as a practical extension of operational discipline\, not a replacement for it. Looking forward\, competitive advantage will come from execution speed and adaptability. Companies that can move to “Plan B” faster—through scenario planning\, data transparency\, and orchestrated decision-making—are better positioned to turn disruption into opportunity. AI\, when grounded in clean data and governed processes\, is becoming a force multiplier for cost control\, service consistency\, and supply chain resilience. \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Key Themes \n \n \n \n Key Themes \n \n \n \n \n\n\n \n \n Resilience as a core operating model.\n Supply chain disruptions are now continuous. Organizations are redesigning processes to absorb shocks and respond dynamically\, rather than optimizing solely for steady-state efficiency.\n \n\n \n Cost pressure returning to the forefront.\n After a period dominated by availability and service\, cost optimization is re-emerging as a priority due to inflation\, tariffs\, and consumer resistance to price increases.\n \n\n \n Data readiness before AI adoption.\n AI effectiveness depends on digitized\, accurate\, and integrated data. Many organizations are still focused on building reliable data pipelines before scaling advanced analytics or AI agents.\n \n\n \n Targeted\, use-case-driven AI.\n The most successful AI initiatives are narrowly scoped and tied to measurable outcomes—such as freight optimization\, packaging efficiency\, demand sensing\, or service-part prediction.\n \n\n \n From deterministic models to agent-based intelligence.\n Enterprises are evolving from rule-based and deterministic planning models toward multi-agent AI systems that collaborate across functions while retaining human oversight.\n \n \n\n Read more\n\n\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Actionable Takeaways for Enterprise Leaders\n \n \n \n \n Actionable Takeaways for Enterprise Leaders\n \n \n \n \n \n \n \n Design for disruption\, not stability.\n Assume supply chain shocks will continue. Build operating models that prioritize flexibility\, scenario planning\, and rapid reconfiguration.\n \n\n \n Refocus AI initiatives on core processes.\n Start with finance\, procurement\, supply planning\, logistics\, and service workflows where inefficiencies are well understood and ROI can be measured.\n \n\n \n Digitize end-to-end before scaling AI.\n Eliminate paper\, manual handoffs\, and siloed systems. AI delivers value only when underlying processes and data are fully digitized.\n \n\n \n Balance cost optimization with resilience.\n Evaluate sourcing\, manufacturing\, and logistics decisions through both cost and risk lenses to avoid trading short-term savings for long-term fragility.\n \n\n \n Adopt AI incrementally with governance.\n Deploy AI agents in constrained domains\, monitor performance\, and introduce human review where error tolerance is low.\n \n\n \n Strengthen supplier and partner integration.\n Increase real-time data sharing and visibility across supplier networks to detect quality\, capacity\, and delivery risks earlier.\n \n\n \n Use AI to accelerate decision speed\, not just insight.\n Prioritize applications that reduce manual effort and compress decision cycles\, enabling faster execution when conditions change.\n \n \n\n Read more\n\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n EVENT PHOTOS  \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Sponsors \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n NTT DATA is a $30+ billion trusted global innovator of business and technology services. We serve 75% of the Fortune Global 100 and are committed to helping clients innovate\, optimize and transform for long-term success. As a Global Top Employer\, we have experts in more than 50 countries and a robust partner ecosystem of established and startup companies. Our services include business and technology consulting\, data and artificial intelligence\, industry solutions\, as well as the development\, implementation and management of applications\, infrastructure and connectivity. We are also one of the leading providers of digital and AI infrastructure in the world. NTT DATA is part of NTT Group\, which invests over $3.6 billion each year in R&D to help organizations and society move confidently and sustainably into the digital future. Learn more at nttdata.com URL:https://bdionline.com/event/100825/ LOCATION:Butter\, 70 W 45th St\, New York\, NY\, 10036\, United States CATEGORIES:Event Calendar,No Header ATTACH;FMTTYPE=image/webp:https://bdionline.com/wp-content/uploads/2025/07/HPEVEEAMNYCfeaturedimage.webp END:VEVENT BEGIN:VEVENT DTSTART;TZID=America/New_York:20250918T120000 DTEND;TZID=America/New_York:20250918T140000 DTSTAMP:20260416T140751 CREATED:20250730T185009Z LAST-MODIFIED:20260203T172358Z UID:114200-1758196800-1758204000@bdionline.com SUMMARY:Strategic AI Workload Placement: Infrastructure Decisions for Performance\, Scale\, and Trust DESCRIPTION:Event Recap: From Disruption to Advantage: AI-Powered Resilience in Supply Chains \n \n \n \n Rosemont\, IL | Gibsons Rosemont | November 13\, 2025 \n \n \n \n \n \n \n \n \n \n \n \n Speakers \n \n \n \n \n \n \n \n \n \n \n \n \n Ron Gilson \n \n \n NTT DATA Business Solutions \n \n \n \n \n \n \n \n Executive Advisor and Principal - Consumer Products and Agribusiness \n \n \n \n \n \n LinkedIn \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n John Buckley \n \n \n SAP \n \n \n \n \n \n \n \n Consumer Products Industry Advisor - Midwest Region \n \n \n \n \n \n LinkedIn \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Sai Simhadri \n \n \n Pampered Chef \n \n \n \n \n \n \n \n Senior Data Architect Manager \n \n \n \n \n \n LinkedIn \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Jody McDonough \n \n \n Sub-Zero Group\, Inc. \n \n \n \n \n \n \n \n VP of IT / CIO \n \n \n \n \n \n LinkedIn \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Executive SummaryEnterprise leaders described a clear shift in how supply chains\, operations\, and core business processes are being managed in an era defined by constant disruption. Resilience is no longer treated as a one-time corrective response to global shocks; it is becoming a permanent design principle. Organizations are rebalancing long-standing cost-optimization models with the need for flexibility\, visibility\, and faster decision-making across suppliers\, manufacturing\, logistics\, and service networks. The discussion highlighted that disruptions—geopolitical\, regulatory\, labor-related\, or demand-driven—are now expected\, not exceptional. AI emerged as an enabler rather than a starting point. Executives consistently emphasized that value comes from applying AI to clearly defined business problems\, supported by digitized\, high-quality data and integrated processes. Rather than pursuing broad or experimental AI initiatives\, leaders are embedding intelligence directly into core workflows such as demand planning\, transportation optimization\, supplier collaboration\, and service operations. The organizations seeing results are those that treat AI as a practical extension of operational discipline\, not a replacement for it. Looking forward\, competitive advantage will come from execution speed and adaptability. Companies that can move to “Plan B” faster—through scenario planning\, data transparency\, and orchestrated decision-making—are better positioned to turn disruption into opportunity. AI\, when grounded in clean data and governed processes\, is becoming a force multiplier for cost control\, service consistency\, and supply chain resilience. \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Key Themes \n \n \n \n Key Themes \n \n \n \n \n\n\n \n \n Resilience as a core operating model.\n Supply chain disruptions are now continuous. Organizations are redesigning processes to absorb shocks and respond dynamically\, rather than optimizing solely for steady-state efficiency.\n \n\n \n Cost pressure returning to the forefront.\n After a period dominated by availability and service\, cost optimization is re-emerging as a priority due to inflation\, tariffs\, and consumer resistance to price increases.\n \n\n \n Data readiness before AI adoption.\n AI effectiveness depends on digitized\, accurate\, and integrated data. Many organizations are still focused on building reliable data pipelines before scaling advanced analytics or AI agents.\n \n\n \n Targeted\, use-case-driven AI.\n The most successful AI initiatives are narrowly scoped and tied to measurable outcomes—such as freight optimization\, packaging efficiency\, demand sensing\, or service-part prediction.\n \n\n \n From deterministic models to agent-based intelligence.\n Enterprises are evolving from rule-based and deterministic planning models toward multi-agent AI systems that collaborate across functions while retaining human oversight.\n \n \n\n Read more\n\n\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Actionable Takeaways for Enterprise Leaders\n \n \n \n \n Actionable Takeaways for Enterprise Leaders\n \n \n \n \n \n \n \n Design for disruption\, not stability.\n Assume supply chain shocks will continue. Build operating models that prioritize flexibility\, scenario planning\, and rapid reconfiguration.\n \n\n \n Refocus AI initiatives on core processes.\n Start with finance\, procurement\, supply planning\, logistics\, and service workflows where inefficiencies are well understood and ROI can be measured.\n \n\n \n Digitize end-to-end before scaling AI.\n Eliminate paper\, manual handoffs\, and siloed systems. AI delivers value only when underlying processes and data are fully digitized.\n \n\n \n Balance cost optimization with resilience.\n Evaluate sourcing\, manufacturing\, and logistics decisions through both cost and risk lenses to avoid trading short-term savings for long-term fragility.\n \n\n \n Adopt AI incrementally with governance.\n Deploy AI agents in constrained domains\, monitor performance\, and introduce human review where error tolerance is low.\n \n\n \n Strengthen supplier and partner integration.\n Increase real-time data sharing and visibility across supplier networks to detect quality\, capacity\, and delivery risks earlier.\n \n\n \n Use AI to accelerate decision speed\, not just insight.\n Prioritize applications that reduce manual effort and compress decision cycles\, enabling faster execution when conditions change.\n \n \n\n Read more\n\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n EVENT PHOTOS  \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Sponsors \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n NTT DATA is a $30+ billion trusted global innovator of business and technology services. We serve 75% of the Fortune Global 100 and are committed to helping clients innovate\, optimize and transform for long-term success. As a Global Top Employer\, we have experts in more than 50 countries and a robust partner ecosystem of established and startup companies. Our services include business and technology consulting\, data and artificial intelligence\, industry solutions\, as well as the development\, implementation and management of applications\, infrastructure and connectivity. We are also one of the leading providers of digital and AI infrastructure in the world. NTT DATA is part of NTT Group\, which invests over $3.6 billion each year in R&D to help organizations and society move confidently and sustainably into the digital future. Learn more at nttdata.com URL:https://bdionline.com/event/091825/ LOCATION:Oceana\, 120 W 49th St\, New York\, NY\, 10020\, United States CATEGORIES:Event Calendar,No Header ATTACH;FMTTYPE=image/png:https://bdionline.com/wp-content/uploads/2025/07/DR-NYVUntitled-1.png END:VEVENT BEGIN:VEVENT DTSTART;TZID=America/New_York:20250917T120000 DTEND;TZID=America/New_York:20250917T140000 DTSTAMP:20260416T140751 CREATED:20250716T150603Z LAST-MODIFIED:20260203T172402Z UID:113891-1758110400-1758117600@bdionline.com SUMMARY:Reimagining Product Innovation with AI: Driving Speed\, Precision & Creativity DESCRIPTION:Event Recap: From Disruption to Advantage: AI-Powered Resilience in Supply Chains \n \n \n \n Rosemont\, IL | Gibsons Rosemont | November 13\, 2025 \n \n \n \n \n \n \n \n \n \n \n \n Speakers \n \n \n \n \n \n \n \n \n \n \n \n \n Ron Gilson \n \n \n NTT DATA Business Solutions \n \n \n \n \n \n \n \n Executive Advisor and Principal - Consumer Products and Agribusiness \n \n \n \n \n \n LinkedIn \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n John Buckley \n \n \n SAP \n \n \n \n \n \n \n \n Consumer Products Industry Advisor - Midwest Region \n \n \n \n \n \n LinkedIn \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Sai Simhadri \n \n \n Pampered Chef \n \n \n \n \n \n \n \n Senior Data Architect Manager \n \n \n \n \n \n LinkedIn \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Jody McDonough \n \n \n Sub-Zero Group\, Inc. \n \n \n \n \n \n \n \n VP of IT / CIO \n \n \n \n \n \n LinkedIn \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Executive SummaryEnterprise leaders described a clear shift in how supply chains\, operations\, and core business processes are being managed in an era defined by constant disruption. Resilience is no longer treated as a one-time corrective response to global shocks; it is becoming a permanent design principle. Organizations are rebalancing long-standing cost-optimization models with the need for flexibility\, visibility\, and faster decision-making across suppliers\, manufacturing\, logistics\, and service networks. The discussion highlighted that disruptions—geopolitical\, regulatory\, labor-related\, or demand-driven—are now expected\, not exceptional. AI emerged as an enabler rather than a starting point. Executives consistently emphasized that value comes from applying AI to clearly defined business problems\, supported by digitized\, high-quality data and integrated processes. Rather than pursuing broad or experimental AI initiatives\, leaders are embedding intelligence directly into core workflows such as demand planning\, transportation optimization\, supplier collaboration\, and service operations. The organizations seeing results are those that treat AI as a practical extension of operational discipline\, not a replacement for it. Looking forward\, competitive advantage will come from execution speed and adaptability. Companies that can move to “Plan B” faster—through scenario planning\, data transparency\, and orchestrated decision-making—are better positioned to turn disruption into opportunity. AI\, when grounded in clean data and governed processes\, is becoming a force multiplier for cost control\, service consistency\, and supply chain resilience. \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Key Themes \n \n \n \n Key Themes \n \n \n \n \n\n\n \n \n Resilience as a core operating model.\n Supply chain disruptions are now continuous. Organizations are redesigning processes to absorb shocks and respond dynamically\, rather than optimizing solely for steady-state efficiency.\n \n\n \n Cost pressure returning to the forefront.\n After a period dominated by availability and service\, cost optimization is re-emerging as a priority due to inflation\, tariffs\, and consumer resistance to price increases.\n \n\n \n Data readiness before AI adoption.\n AI effectiveness depends on digitized\, accurate\, and integrated data. Many organizations are still focused on building reliable data pipelines before scaling advanced analytics or AI agents.\n \n\n \n Targeted\, use-case-driven AI.\n The most successful AI initiatives are narrowly scoped and tied to measurable outcomes—such as freight optimization\, packaging efficiency\, demand sensing\, or service-part prediction.\n \n\n \n From deterministic models to agent-based intelligence.\n Enterprises are evolving from rule-based and deterministic planning models toward multi-agent AI systems that collaborate across functions while retaining human oversight.\n \n \n\n Read more\n\n\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Actionable Takeaways for Enterprise Leaders\n \n \n \n \n Actionable Takeaways for Enterprise Leaders\n \n \n \n \n \n \n \n Design for disruption\, not stability.\n Assume supply chain shocks will continue. Build operating models that prioritize flexibility\, scenario planning\, and rapid reconfiguration.\n \n\n \n Refocus AI initiatives on core processes.\n Start with finance\, procurement\, supply planning\, logistics\, and service workflows where inefficiencies are well understood and ROI can be measured.\n \n\n \n Digitize end-to-end before scaling AI.\n Eliminate paper\, manual handoffs\, and siloed systems. AI delivers value only when underlying processes and data are fully digitized.\n \n\n \n Balance cost optimization with resilience.\n Evaluate sourcing\, manufacturing\, and logistics decisions through both cost and risk lenses to avoid trading short-term savings for long-term fragility.\n \n\n \n Adopt AI incrementally with governance.\n Deploy AI agents in constrained domains\, monitor performance\, and introduce human review where error tolerance is low.\n \n\n \n Strengthen supplier and partner integration.\n Increase real-time data sharing and visibility across supplier networks to detect quality\, capacity\, and delivery risks earlier.\n \n\n \n Use AI to accelerate decision speed\, not just insight.\n Prioritize applications that reduce manual effort and compress decision cycles\, enabling faster execution when conditions change.\n \n \n\n Read more\n\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n EVENT PHOTOS  \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Sponsors \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n NTT DATA is a $30+ billion trusted global innovator of business and technology services. We serve 75% of the Fortune Global 100 and are committed to helping clients innovate\, optimize and transform for long-term success. As a Global Top Employer\, we have experts in more than 50 countries and a robust partner ecosystem of established and startup companies. Our services include business and technology consulting\, data and artificial intelligence\, industry solutions\, as well as the development\, implementation and management of applications\, infrastructure and connectivity. We are also one of the leading providers of digital and AI infrastructure in the world. NTT DATA is part of NTT Group\, which invests over $3.6 billion each year in R&D to help organizations and society move confidently and sustainably into the digital future. Learn more at nttdata.com URL:https://bdionline.com/event/091725/ LOCATION:Oceana\, 120 W 49th St\, New York\, NY\, 10020\, United States CATEGORIES:Event Calendar,No Header ATTACH;FMTTYPE=image/webp:https://bdionline.com/wp-content/uploads/2025/07/centricsoftwareNYCfeaturedimage.webp END:VEVENT BEGIN:VEVENT DTSTART;TZID=America/Los_Angeles:20250916T173000 DTEND;TZID=America/Los_Angeles:20250916T203000 DTSTAMP:20260416T140751 CREATED:20250723T202030Z LAST-MODIFIED:20260203T172403Z UID:114085-1758043800-1758054600@bdionline.com SUMMARY:GenAI Roundtable for Enterprise Innovation - An Executive Dinner & Wine Tasting for Technology Leaders DESCRIPTION:Event Recap: From Disruption to Advantage: AI-Powered Resilience in Supply Chains \n \n \n \n Rosemont\, IL | Gibsons Rosemont | November 13\, 2025 \n \n \n \n \n \n \n \n \n \n \n \n Speakers \n \n \n \n \n \n \n \n \n \n \n \n \n Ron Gilson \n \n \n NTT DATA Business Solutions \n \n \n \n \n \n \n \n Executive Advisor and Principal - Consumer Products and Agribusiness \n \n \n \n \n \n LinkedIn \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n John Buckley \n \n \n SAP \n \n \n \n \n \n \n \n Consumer Products Industry Advisor - Midwest Region \n \n \n \n \n \n LinkedIn \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Sai Simhadri \n \n \n Pampered Chef \n \n \n \n \n \n \n \n Senior Data Architect Manager \n \n \n \n \n \n LinkedIn \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Jody McDonough \n \n \n Sub-Zero Group\, Inc. \n \n \n \n \n \n \n \n VP of IT / CIO \n \n \n \n \n \n LinkedIn \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Executive SummaryEnterprise leaders described a clear shift in how supply chains\, operations\, and core business processes are being managed in an era defined by constant disruption. Resilience is no longer treated as a one-time corrective response to global shocks; it is becoming a permanent design principle. Organizations are rebalancing long-standing cost-optimization models with the need for flexibility\, visibility\, and faster decision-making across suppliers\, manufacturing\, logistics\, and service networks. The discussion highlighted that disruptions—geopolitical\, regulatory\, labor-related\, or demand-driven—are now expected\, not exceptional. AI emerged as an enabler rather than a starting point. Executives consistently emphasized that value comes from applying AI to clearly defined business problems\, supported by digitized\, high-quality data and integrated processes. Rather than pursuing broad or experimental AI initiatives\, leaders are embedding intelligence directly into core workflows such as demand planning\, transportation optimization\, supplier collaboration\, and service operations. The organizations seeing results are those that treat AI as a practical extension of operational discipline\, not a replacement for it. Looking forward\, competitive advantage will come from execution speed and adaptability. Companies that can move to “Plan B” faster—through scenario planning\, data transparency\, and orchestrated decision-making—are better positioned to turn disruption into opportunity. AI\, when grounded in clean data and governed processes\, is becoming a force multiplier for cost control\, service consistency\, and supply chain resilience. \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Key Themes \n \n \n \n Key Themes \n \n \n \n \n\n\n \n \n Resilience as a core operating model.\n Supply chain disruptions are now continuous. Organizations are redesigning processes to absorb shocks and respond dynamically\, rather than optimizing solely for steady-state efficiency.\n \n\n \n Cost pressure returning to the forefront.\n After a period dominated by availability and service\, cost optimization is re-emerging as a priority due to inflation\, tariffs\, and consumer resistance to price increases.\n \n\n \n Data readiness before AI adoption.\n AI effectiveness depends on digitized\, accurate\, and integrated data. Many organizations are still focused on building reliable data pipelines before scaling advanced analytics or AI agents.\n \n\n \n Targeted\, use-case-driven AI.\n The most successful AI initiatives are narrowly scoped and tied to measurable outcomes—such as freight optimization\, packaging efficiency\, demand sensing\, or service-part prediction.\n \n\n \n From deterministic models to agent-based intelligence.\n Enterprises are evolving from rule-based and deterministic planning models toward multi-agent AI systems that collaborate across functions while retaining human oversight.\n \n \n\n Read more\n\n\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Actionable Takeaways for Enterprise Leaders\n \n \n \n \n Actionable Takeaways for Enterprise Leaders\n \n \n \n \n \n \n \n Design for disruption\, not stability.\n Assume supply chain shocks will continue. Build operating models that prioritize flexibility\, scenario planning\, and rapid reconfiguration.\n \n\n \n Refocus AI initiatives on core processes.\n Start with finance\, procurement\, supply planning\, logistics\, and service workflows where inefficiencies are well understood and ROI can be measured.\n \n\n \n Digitize end-to-end before scaling AI.\n Eliminate paper\, manual handoffs\, and siloed systems. AI delivers value only when underlying processes and data are fully digitized.\n \n\n \n Balance cost optimization with resilience.\n Evaluate sourcing\, manufacturing\, and logistics decisions through both cost and risk lenses to avoid trading short-term savings for long-term fragility.\n \n\n \n Adopt AI incrementally with governance.\n Deploy AI agents in constrained domains\, monitor performance\, and introduce human review where error tolerance is low.\n \n\n \n Strengthen supplier and partner integration.\n Increase real-time data sharing and visibility across supplier networks to detect quality\, capacity\, and delivery risks earlier.\n \n\n \n Use AI to accelerate decision speed\, not just insight.\n Prioritize applications that reduce manual effort and compress decision cycles\, enabling faster execution when conditions change.\n \n \n\n Read more\n\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n EVENT PHOTOS  \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Sponsors \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n NTT DATA is a $30+ billion trusted global innovator of business and technology services. We serve 75% of the Fortune Global 100 and are committed to helping clients innovate\, optimize and transform for long-term success. As a Global Top Employer\, we have experts in more than 50 countries and a robust partner ecosystem of established and startup companies. Our services include business and technology consulting\, data and artificial intelligence\, industry solutions\, as well as the development\, implementation and management of applications\, infrastructure and connectivity. We are also one of the leading providers of digital and AI infrastructure in the world. NTT DATA is part of NTT Group\, which invests over $3.6 billion each year in R&D to help organizations and society move confidently and sustainably into the digital future. Learn more at nttdata.com URL:https://bdionline.com/event/091625/ LOCATION:Taverna\, 800 Emerson St\, Palo Alto\, CA\, 94301\, United States CATEGORIES:Event Calendar,No Header ATTACH;FMTTYPE=image/webp:https://bdionline.com/wp-content/uploads/2025/07/AMDfeaturedimage.webp END:VEVENT BEGIN:VEVENT DTSTART;TZID=America/New_York:20250911T120000 DTEND;TZID=America/New_York:20250911T140000 DTSTAMP:20260416T140751 CREATED:20250715T140914Z LAST-MODIFIED:20260203T172404Z UID:113795-1757592000-1757599200@bdionline.com SUMMARY:Leading Through Disruption: AI & Social Shifts in Pharma DESCRIPTION:Event Recap: From Disruption to Advantage: AI-Powered Resilience in Supply Chains \n \n \n \n Rosemont\, IL | Gibsons Rosemont | November 13\, 2025 \n \n \n \n \n \n \n \n \n \n \n \n Speakers \n \n \n \n \n \n \n \n \n \n \n \n \n Ron Gilson \n \n \n NTT DATA Business Solutions \n \n \n \n \n \n \n \n Executive Advisor and Principal - Consumer Products and Agribusiness \n \n \n \n \n \n LinkedIn \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n John Buckley \n \n \n SAP \n \n \n \n \n \n \n \n Consumer Products Industry Advisor - Midwest Region \n \n \n \n \n \n LinkedIn \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Sai Simhadri \n \n \n Pampered Chef \n \n \n \n \n \n \n \n Senior Data Architect Manager \n \n \n \n \n \n LinkedIn \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Jody McDonough \n \n \n Sub-Zero Group\, Inc. \n \n \n \n \n \n \n \n VP of IT / CIO \n \n \n \n \n \n LinkedIn \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Executive SummaryEnterprise leaders described a clear shift in how supply chains\, operations\, and core business processes are being managed in an era defined by constant disruption. Resilience is no longer treated as a one-time corrective response to global shocks; it is becoming a permanent design principle. Organizations are rebalancing long-standing cost-optimization models with the need for flexibility\, visibility\, and faster decision-making across suppliers\, manufacturing\, logistics\, and service networks. The discussion highlighted that disruptions—geopolitical\, regulatory\, labor-related\, or demand-driven—are now expected\, not exceptional. AI emerged as an enabler rather than a starting point. Executives consistently emphasized that value comes from applying AI to clearly defined business problems\, supported by digitized\, high-quality data and integrated processes. Rather than pursuing broad or experimental AI initiatives\, leaders are embedding intelligence directly into core workflows such as demand planning\, transportation optimization\, supplier collaboration\, and service operations. The organizations seeing results are those that treat AI as a practical extension of operational discipline\, not a replacement for it. Looking forward\, competitive advantage will come from execution speed and adaptability. Companies that can move to “Plan B” faster—through scenario planning\, data transparency\, and orchestrated decision-making—are better positioned to turn disruption into opportunity. AI\, when grounded in clean data and governed processes\, is becoming a force multiplier for cost control\, service consistency\, and supply chain resilience. \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Key Themes \n \n \n \n Key Themes \n \n \n \n \n\n\n \n \n Resilience as a core operating model.\n Supply chain disruptions are now continuous. Organizations are redesigning processes to absorb shocks and respond dynamically\, rather than optimizing solely for steady-state efficiency.\n \n\n \n Cost pressure returning to the forefront.\n After a period dominated by availability and service\, cost optimization is re-emerging as a priority due to inflation\, tariffs\, and consumer resistance to price increases.\n \n\n \n Data readiness before AI adoption.\n AI effectiveness depends on digitized\, accurate\, and integrated data. Many organizations are still focused on building reliable data pipelines before scaling advanced analytics or AI agents.\n \n\n \n Targeted\, use-case-driven AI.\n The most successful AI initiatives are narrowly scoped and tied to measurable outcomes—such as freight optimization\, packaging efficiency\, demand sensing\, or service-part prediction.\n \n\n \n From deterministic models to agent-based intelligence.\n Enterprises are evolving from rule-based and deterministic planning models toward multi-agent AI systems that collaborate across functions while retaining human oversight.\n \n \n\n Read more\n\n\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Actionable Takeaways for Enterprise Leaders\n \n \n \n \n Actionable Takeaways for Enterprise Leaders\n \n \n \n \n \n \n \n Design for disruption\, not stability.\n Assume supply chain shocks will continue. Build operating models that prioritize flexibility\, scenario planning\, and rapid reconfiguration.\n \n\n \n Refocus AI initiatives on core processes.\n Start with finance\, procurement\, supply planning\, logistics\, and service workflows where inefficiencies are well understood and ROI can be measured.\n \n\n \n Digitize end-to-end before scaling AI.\n Eliminate paper\, manual handoffs\, and siloed systems. AI delivers value only when underlying processes and data are fully digitized.\n \n\n \n Balance cost optimization with resilience.\n Evaluate sourcing\, manufacturing\, and logistics decisions through both cost and risk lenses to avoid trading short-term savings for long-term fragility.\n \n\n \n Adopt AI incrementally with governance.\n Deploy AI agents in constrained domains\, monitor performance\, and introduce human review where error tolerance is low.\n \n\n \n Strengthen supplier and partner integration.\n Increase real-time data sharing and visibility across supplier networks to detect quality\, capacity\, and delivery risks earlier.\n \n\n \n Use AI to accelerate decision speed\, not just insight.\n Prioritize applications that reduce manual effort and compress decision cycles\, enabling faster execution when conditions change.\n \n \n\n Read more\n\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n EVENT PHOTOS  \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Sponsors \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n NTT DATA is a $30+ billion trusted global innovator of business and technology services. We serve 75% of the Fortune Global 100 and are committed to helping clients innovate\, optimize and transform for long-term success. As a Global Top Employer\, we have experts in more than 50 countries and a robust partner ecosystem of established and startup companies. Our services include business and technology consulting\, data and artificial intelligence\, industry solutions\, as well as the development\, implementation and management of applications\, infrastructure and connectivity. We are also one of the leading providers of digital and AI infrastructure in the world. NTT DATA is part of NTT Group\, which invests over $3.6 billion each year in R&D to help organizations and society move confidently and sustainably into the digital future. Learn more at nttdata.com URL:https://bdionline.com/event/091125/ LOCATION:IL CATEGORIES:Event Calendar,No Header ATTACH;FMTTYPE=image/png:https://bdionline.com/wp-content/uploads/2024/01/Liveworld-Preview-image.png END:VEVENT BEGIN:VEVENT DTSTART;TZID=America/Chicago:20250909T120000 DTEND;TZID=America/Chicago:20250911T140000 DTSTAMP:20260416T140751 CREATED:20250715T193859Z LAST-MODIFIED:20260203T172405Z UID:113824-1757419200-1757599200@bdionline.com SUMMARY:Reimagining Product Innovation with AI: Driving Speed\, Precision & Creativity DESCRIPTION:Event Recap: From Disruption to Advantage: AI-Powered Resilience in Supply Chains \n \n \n \n Rosemont\, IL | Gibsons Rosemont | November 13\, 2025 \n \n \n \n \n \n \n \n \n \n \n \n Speakers \n \n \n \n \n \n \n \n \n \n \n \n \n Ron Gilson \n \n \n NTT DATA Business Solutions \n \n \n \n \n \n \n \n Executive Advisor and Principal - Consumer Products and Agribusiness \n \n \n \n \n \n LinkedIn \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n John Buckley \n \n \n SAP \n \n \n \n \n \n \n \n Consumer Products Industry Advisor - Midwest Region \n \n \n \n \n \n LinkedIn \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Sai Simhadri \n \n \n Pampered Chef \n \n \n \n \n \n \n \n Senior Data Architect Manager \n \n \n \n \n \n LinkedIn \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Jody McDonough \n \n \n Sub-Zero Group\, Inc. \n \n \n \n \n \n \n \n VP of IT / CIO \n \n \n \n \n \n LinkedIn \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Executive SummaryEnterprise leaders described a clear shift in how supply chains\, operations\, and core business processes are being managed in an era defined by constant disruption. Resilience is no longer treated as a one-time corrective response to global shocks; it is becoming a permanent design principle. Organizations are rebalancing long-standing cost-optimization models with the need for flexibility\, visibility\, and faster decision-making across suppliers\, manufacturing\, logistics\, and service networks. The discussion highlighted that disruptions—geopolitical\, regulatory\, labor-related\, or demand-driven—are now expected\, not exceptional. AI emerged as an enabler rather than a starting point. Executives consistently emphasized that value comes from applying AI to clearly defined business problems\, supported by digitized\, high-quality data and integrated processes. Rather than pursuing broad or experimental AI initiatives\, leaders are embedding intelligence directly into core workflows such as demand planning\, transportation optimization\, supplier collaboration\, and service operations. The organizations seeing results are those that treat AI as a practical extension of operational discipline\, not a replacement for it. Looking forward\, competitive advantage will come from execution speed and adaptability. Companies that can move to “Plan B” faster—through scenario planning\, data transparency\, and orchestrated decision-making—are better positioned to turn disruption into opportunity. AI\, when grounded in clean data and governed processes\, is becoming a force multiplier for cost control\, service consistency\, and supply chain resilience. \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Key Themes \n \n \n \n Key Themes \n \n \n \n \n\n\n \n \n Resilience as a core operating model.\n Supply chain disruptions are now continuous. Organizations are redesigning processes to absorb shocks and respond dynamically\, rather than optimizing solely for steady-state efficiency.\n \n\n \n Cost pressure returning to the forefront.\n After a period dominated by availability and service\, cost optimization is re-emerging as a priority due to inflation\, tariffs\, and consumer resistance to price increases.\n \n\n \n Data readiness before AI adoption.\n AI effectiveness depends on digitized\, accurate\, and integrated data. Many organizations are still focused on building reliable data pipelines before scaling advanced analytics or AI agents.\n \n\n \n Targeted\, use-case-driven AI.\n The most successful AI initiatives are narrowly scoped and tied to measurable outcomes—such as freight optimization\, packaging efficiency\, demand sensing\, or service-part prediction.\n \n\n \n From deterministic models to agent-based intelligence.\n Enterprises are evolving from rule-based and deterministic planning models toward multi-agent AI systems that collaborate across functions while retaining human oversight.\n \n \n\n Read more\n\n\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Actionable Takeaways for Enterprise Leaders\n \n \n \n \n Actionable Takeaways for Enterprise Leaders\n \n \n \n \n \n \n \n Design for disruption\, not stability.\n Assume supply chain shocks will continue. Build operating models that prioritize flexibility\, scenario planning\, and rapid reconfiguration.\n \n\n \n Refocus AI initiatives on core processes.\n Start with finance\, procurement\, supply planning\, logistics\, and service workflows where inefficiencies are well understood and ROI can be measured.\n \n\n \n Digitize end-to-end before scaling AI.\n Eliminate paper\, manual handoffs\, and siloed systems. AI delivers value only when underlying processes and data are fully digitized.\n \n\n \n Balance cost optimization with resilience.\n Evaluate sourcing\, manufacturing\, and logistics decisions through both cost and risk lenses to avoid trading short-term savings for long-term fragility.\n \n\n \n Adopt AI incrementally with governance.\n Deploy AI agents in constrained domains\, monitor performance\, and introduce human review where error tolerance is low.\n \n\n \n Strengthen supplier and partner integration.\n Increase real-time data sharing and visibility across supplier networks to detect quality\, capacity\, and delivery risks earlier.\n \n\n \n Use AI to accelerate decision speed\, not just insight.\n Prioritize applications that reduce manual effort and compress decision cycles\, enabling faster execution when conditions change.\n \n \n\n Read more\n\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n EVENT PHOTOS  \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Sponsors \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n NTT DATA is a $30+ billion trusted global innovator of business and technology services. We serve 75% of the Fortune Global 100 and are committed to helping clients innovate\, optimize and transform for long-term success. As a Global Top Employer\, we have experts in more than 50 countries and a robust partner ecosystem of established and startup companies. Our services include business and technology consulting\, data and artificial intelligence\, industry solutions\, as well as the development\, implementation and management of applications\, infrastructure and connectivity. We are also one of the leading providers of digital and AI infrastructure in the world. NTT DATA is part of NTT Group\, which invests over $3.6 billion each year in R&D to help organizations and society move confidently and sustainably into the digital future. Learn more at nttdata.com URL:https://bdionline.com/event/091125_centric_software/ LOCATION:IL CATEGORIES:Event Calendar,No Header ATTACH;FMTTYPE=image/webp:https://bdionline.com/wp-content/uploads/2025/07/centricsoftwarechiagofeaturedimage.webp END:VEVENT BEGIN:VEVENT DTSTART;TZID=America/Los_Angeles:20250827T173000 DTEND;TZID=America/Los_Angeles:20250827T200000 DTSTAMP:20260416T140751 CREATED:20250711T103507Z LAST-MODIFIED:20260203T172407Z UID:113666-1756315800-1756324800@bdionline.com SUMMARY:Enabling AI-Powered Innovation at Scale: An API-First Future DESCRIPTION:Event Recap: From Disruption to Advantage: AI-Powered Resilience in Supply Chains \n \n \n \n Rosemont\, IL | Gibsons Rosemont | November 13\, 2025 \n \n \n \n \n \n \n \n \n \n \n \n Speakers \n \n \n \n \n \n \n \n \n \n \n \n \n Ron Gilson \n \n \n NTT DATA Business Solutions \n \n \n \n \n \n \n \n Executive Advisor and Principal - Consumer Products and Agribusiness \n \n \n \n \n \n LinkedIn \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n John Buckley \n \n \n SAP \n \n \n \n \n \n \n \n Consumer Products Industry Advisor - Midwest Region \n \n \n \n \n \n LinkedIn \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Sai Simhadri \n \n \n Pampered Chef \n \n \n \n \n \n \n \n Senior Data Architect Manager \n \n \n \n \n \n LinkedIn \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Jody McDonough \n \n \n Sub-Zero Group\, Inc. \n \n \n \n \n \n \n \n VP of IT / CIO \n \n \n \n \n \n LinkedIn \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Executive SummaryEnterprise leaders described a clear shift in how supply chains\, operations\, and core business processes are being managed in an era defined by constant disruption. Resilience is no longer treated as a one-time corrective response to global shocks; it is becoming a permanent design principle. Organizations are rebalancing long-standing cost-optimization models with the need for flexibility\, visibility\, and faster decision-making across suppliers\, manufacturing\, logistics\, and service networks. The discussion highlighted that disruptions—geopolitical\, regulatory\, labor-related\, or demand-driven—are now expected\, not exceptional. AI emerged as an enabler rather than a starting point. Executives consistently emphasized that value comes from applying AI to clearly defined business problems\, supported by digitized\, high-quality data and integrated processes. Rather than pursuing broad or experimental AI initiatives\, leaders are embedding intelligence directly into core workflows such as demand planning\, transportation optimization\, supplier collaboration\, and service operations. The organizations seeing results are those that treat AI as a practical extension of operational discipline\, not a replacement for it. Looking forward\, competitive advantage will come from execution speed and adaptability. Companies that can move to “Plan B” faster—through scenario planning\, data transparency\, and orchestrated decision-making—are better positioned to turn disruption into opportunity. AI\, when grounded in clean data and governed processes\, is becoming a force multiplier for cost control\, service consistency\, and supply chain resilience. \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Key Themes \n \n \n \n Key Themes \n \n \n \n \n\n\n \n \n Resilience as a core operating model.\n Supply chain disruptions are now continuous. Organizations are redesigning processes to absorb shocks and respond dynamically\, rather than optimizing solely for steady-state efficiency.\n \n\n \n Cost pressure returning to the forefront.\n After a period dominated by availability and service\, cost optimization is re-emerging as a priority due to inflation\, tariffs\, and consumer resistance to price increases.\n \n\n \n Data readiness before AI adoption.\n AI effectiveness depends on digitized\, accurate\, and integrated data. Many organizations are still focused on building reliable data pipelines before scaling advanced analytics or AI agents.\n \n\n \n Targeted\, use-case-driven AI.\n The most successful AI initiatives are narrowly scoped and tied to measurable outcomes—such as freight optimization\, packaging efficiency\, demand sensing\, or service-part prediction.\n \n\n \n From deterministic models to agent-based intelligence.\n Enterprises are evolving from rule-based and deterministic planning models toward multi-agent AI systems that collaborate across functions while retaining human oversight.\n \n \n\n Read more\n\n\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Actionable Takeaways for Enterprise Leaders\n \n \n \n \n Actionable Takeaways for Enterprise Leaders\n \n \n \n \n \n \n \n Design for disruption\, not stability.\n Assume supply chain shocks will continue. Build operating models that prioritize flexibility\, scenario planning\, and rapid reconfiguration.\n \n\n \n Refocus AI initiatives on core processes.\n Start with finance\, procurement\, supply planning\, logistics\, and service workflows where inefficiencies are well understood and ROI can be measured.\n \n\n \n Digitize end-to-end before scaling AI.\n Eliminate paper\, manual handoffs\, and siloed systems. AI delivers value only when underlying processes and data are fully digitized.\n \n\n \n Balance cost optimization with resilience.\n Evaluate sourcing\, manufacturing\, and logistics decisions through both cost and risk lenses to avoid trading short-term savings for long-term fragility.\n \n\n \n Adopt AI incrementally with governance.\n Deploy AI agents in constrained domains\, monitor performance\, and introduce human review where error tolerance is low.\n \n\n \n Strengthen supplier and partner integration.\n Increase real-time data sharing and visibility across supplier networks to detect quality\, capacity\, and delivery risks earlier.\n \n\n \n Use AI to accelerate decision speed\, not just insight.\n Prioritize applications that reduce manual effort and compress decision cycles\, enabling faster execution when conditions change.\n \n \n\n Read more\n\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n EVENT PHOTOS  \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Sponsors \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n NTT DATA is a $30+ billion trusted global innovator of business and technology services. We serve 75% of the Fortune Global 100 and are committed to helping clients innovate\, optimize and transform for long-term success. As a Global Top Employer\, we have experts in more than 50 countries and a robust partner ecosystem of established and startup companies. Our services include business and technology consulting\, data and artificial intelligence\, industry solutions\, as well as the development\, implementation and management of applications\, infrastructure and connectivity. We are also one of the leading providers of digital and AI infrastructure in the world. NTT DATA is part of NTT Group\, which invests over $3.6 billion each year in R&D to help organizations and society move confidently and sustainably into the digital future. Learn more at nttdata.com URL:https://bdionline.com/event/082725/ LOCATION:Taverna\, 800 Emerson St\, Palo Alto\, CA\, 94301\, United States CATEGORIES:Event Calendar,No Header ATTACH;FMTTYPE=image/webp:https://bdionline.com/wp-content/uploads/2025/07/0827KongPaloAlto.webp END:VEVENT BEGIN:VEVENT DTSTART;TZID=America/New_York:20250730T173000 DTEND;TZID=America/New_York:20250730T200000 DTSTAMP:20260416T140751 CREATED:20250602T194222Z LAST-MODIFIED:20260203T172410Z UID:113240-1753896600-1753905600@bdionline.com SUMMARY:Executive Wine Tasting & Dinner - Scalable AI in the Enterprise: Accelerating Innovation Through Infrastructure & Partnership DESCRIPTION:Event Recap: From Disruption to Advantage: AI-Powered Resilience in Supply Chains \n \n \n \n Rosemont\, IL | Gibsons Rosemont | November 13\, 2025 \n \n \n \n \n \n \n \n \n \n \n \n Speakers \n \n \n \n \n \n \n \n \n \n \n \n \n Ron Gilson \n \n \n NTT DATA Business Solutions \n \n \n \n \n \n \n \n Executive Advisor and Principal - Consumer Products and Agribusiness \n \n \n \n \n \n LinkedIn \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n John Buckley \n \n \n SAP \n \n \n \n \n \n \n \n Consumer Products Industry Advisor - Midwest Region \n \n \n \n \n \n LinkedIn \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Sai Simhadri \n \n \n Pampered Chef \n \n \n \n \n \n \n \n Senior Data Architect Manager \n \n \n \n \n \n LinkedIn \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Jody McDonough \n \n \n Sub-Zero Group\, Inc. \n \n \n \n \n \n \n \n VP of IT / CIO \n \n \n \n \n \n LinkedIn \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Executive SummaryEnterprise leaders described a clear shift in how supply chains\, operations\, and core business processes are being managed in an era defined by constant disruption. Resilience is no longer treated as a one-time corrective response to global shocks; it is becoming a permanent design principle. Organizations are rebalancing long-standing cost-optimization models with the need for flexibility\, visibility\, and faster decision-making across suppliers\, manufacturing\, logistics\, and service networks. The discussion highlighted that disruptions—geopolitical\, regulatory\, labor-related\, or demand-driven—are now expected\, not exceptional. AI emerged as an enabler rather than a starting point. Executives consistently emphasized that value comes from applying AI to clearly defined business problems\, supported by digitized\, high-quality data and integrated processes. Rather than pursuing broad or experimental AI initiatives\, leaders are embedding intelligence directly into core workflows such as demand planning\, transportation optimization\, supplier collaboration\, and service operations. The organizations seeing results are those that treat AI as a practical extension of operational discipline\, not a replacement for it. Looking forward\, competitive advantage will come from execution speed and adaptability. Companies that can move to “Plan B” faster—through scenario planning\, data transparency\, and orchestrated decision-making—are better positioned to turn disruption into opportunity. AI\, when grounded in clean data and governed processes\, is becoming a force multiplier for cost control\, service consistency\, and supply chain resilience. \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Key Themes \n \n \n \n Key Themes \n \n \n \n \n\n\n \n \n Resilience as a core operating model.\n Supply chain disruptions are now continuous. Organizations are redesigning processes to absorb shocks and respond dynamically\, rather than optimizing solely for steady-state efficiency.\n \n\n \n Cost pressure returning to the forefront.\n After a period dominated by availability and service\, cost optimization is re-emerging as a priority due to inflation\, tariffs\, and consumer resistance to price increases.\n \n\n \n Data readiness before AI adoption.\n AI effectiveness depends on digitized\, accurate\, and integrated data. Many organizations are still focused on building reliable data pipelines before scaling advanced analytics or AI agents.\n \n\n \n Targeted\, use-case-driven AI.\n The most successful AI initiatives are narrowly scoped and tied to measurable outcomes—such as freight optimization\, packaging efficiency\, demand sensing\, or service-part prediction.\n \n\n \n From deterministic models to agent-based intelligence.\n Enterprises are evolving from rule-based and deterministic planning models toward multi-agent AI systems that collaborate across functions while retaining human oversight.\n \n \n\n Read more\n\n\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Actionable Takeaways for Enterprise Leaders\n \n \n \n \n Actionable Takeaways for Enterprise Leaders\n \n \n \n \n \n \n \n Design for disruption\, not stability.\n Assume supply chain shocks will continue. Build operating models that prioritize flexibility\, scenario planning\, and rapid reconfiguration.\n \n\n \n Refocus AI initiatives on core processes.\n Start with finance\, procurement\, supply planning\, logistics\, and service workflows where inefficiencies are well understood and ROI can be measured.\n \n\n \n Digitize end-to-end before scaling AI.\n Eliminate paper\, manual handoffs\, and siloed systems. AI delivers value only when underlying processes and data are fully digitized.\n \n\n \n Balance cost optimization with resilience.\n Evaluate sourcing\, manufacturing\, and logistics decisions through both cost and risk lenses to avoid trading short-term savings for long-term fragility.\n \n\n \n Adopt AI incrementally with governance.\n Deploy AI agents in constrained domains\, monitor performance\, and introduce human review where error tolerance is low.\n \n\n \n Strengthen supplier and partner integration.\n Increase real-time data sharing and visibility across supplier networks to detect quality\, capacity\, and delivery risks earlier.\n \n\n \n Use AI to accelerate decision speed\, not just insight.\n Prioritize applications that reduce manual effort and compress decision cycles\, enabling faster execution when conditions change.\n \n \n\n Read more\n\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n EVENT PHOTOS  \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Sponsors \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n NTT DATA is a $30+ billion trusted global innovator of business and technology services. We serve 75% of the Fortune Global 100 and are committed to helping clients innovate\, optimize and transform for long-term success. As a Global Top Employer\, we have experts in more than 50 countries and a robust partner ecosystem of established and startup companies. Our services include business and technology consulting\, data and artificial intelligence\, industry solutions\, as well as the development\, implementation and management of applications\, infrastructure and connectivity. We are also one of the leading providers of digital and AI infrastructure in the world. NTT DATA is part of NTT Group\, which invests over $3.6 billion each year in R&D to help organizations and society move confidently and sustainably into the digital future. Learn more at nttdata.com URL:https://bdionline.com/event/073025/ LOCATION:Butter\, 70 W 45th St\, New York\, NY\, 10036\, United States CATEGORIES:Event Calendar,No Header ATTACH;FMTTYPE=image/webp:https://bdionline.com/wp-content/uploads/2025/06/hpecnycfeaturedimage-1.webp END:VEVENT BEGIN:VEVENT DTSTART;TZID=America/Chicago:20250723T173000 DTEND;TZID=America/Chicago:20250723T210000 DTSTAMP:20260416T140751 CREATED:20250602T190239Z LAST-MODIFIED:20260203T172412Z UID:113218-1753291800-1753304400@bdionline.com SUMMARY:Executive Wine Tasting & Dinner - Scalable AI in the Enterprise: Accelerating Innovation Through Infrastructure & Partnership DESCRIPTION:Event Recap: From Disruption to Advantage: AI-Powered Resilience in Supply Chains \n \n \n \n Rosemont\, IL | Gibsons Rosemont | November 13\, 2025 \n \n \n \n \n \n \n \n \n \n \n \n Speakers \n \n \n \n \n \n \n \n \n \n \n \n \n Ron Gilson \n \n \n NTT DATA Business Solutions \n \n \n \n \n \n \n \n Executive Advisor and Principal - Consumer Products and Agribusiness \n \n \n \n \n \n LinkedIn \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n John Buckley \n \n \n SAP \n \n \n \n \n \n \n \n Consumer Products Industry Advisor - Midwest Region \n \n \n \n \n \n LinkedIn \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Sai Simhadri \n \n \n Pampered Chef \n \n \n \n \n \n \n \n Senior Data Architect Manager \n \n \n \n \n \n LinkedIn \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Jody McDonough \n \n \n Sub-Zero Group\, Inc. \n \n \n \n \n \n \n \n VP of IT / CIO \n \n \n \n \n \n LinkedIn \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Executive SummaryEnterprise leaders described a clear shift in how supply chains\, operations\, and core business processes are being managed in an era defined by constant disruption. Resilience is no longer treated as a one-time corrective response to global shocks; it is becoming a permanent design principle. Organizations are rebalancing long-standing cost-optimization models with the need for flexibility\, visibility\, and faster decision-making across suppliers\, manufacturing\, logistics\, and service networks. The discussion highlighted that disruptions—geopolitical\, regulatory\, labor-related\, or demand-driven—are now expected\, not exceptional. AI emerged as an enabler rather than a starting point. Executives consistently emphasized that value comes from applying AI to clearly defined business problems\, supported by digitized\, high-quality data and integrated processes. Rather than pursuing broad or experimental AI initiatives\, leaders are embedding intelligence directly into core workflows such as demand planning\, transportation optimization\, supplier collaboration\, and service operations. The organizations seeing results are those that treat AI as a practical extension of operational discipline\, not a replacement for it. Looking forward\, competitive advantage will come from execution speed and adaptability. Companies that can move to “Plan B” faster—through scenario planning\, data transparency\, and orchestrated decision-making—are better positioned to turn disruption into opportunity. AI\, when grounded in clean data and governed processes\, is becoming a force multiplier for cost control\, service consistency\, and supply chain resilience. \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Key Themes \n \n \n \n Key Themes \n \n \n \n \n\n\n \n \n Resilience as a core operating model.\n Supply chain disruptions are now continuous. Organizations are redesigning processes to absorb shocks and respond dynamically\, rather than optimizing solely for steady-state efficiency.\n \n\n \n Cost pressure returning to the forefront.\n After a period dominated by availability and service\, cost optimization is re-emerging as a priority due to inflation\, tariffs\, and consumer resistance to price increases.\n \n\n \n Data readiness before AI adoption.\n AI effectiveness depends on digitized\, accurate\, and integrated data. Many organizations are still focused on building reliable data pipelines before scaling advanced analytics or AI agents.\n \n\n \n Targeted\, use-case-driven AI.\n The most successful AI initiatives are narrowly scoped and tied to measurable outcomes—such as freight optimization\, packaging efficiency\, demand sensing\, or service-part prediction.\n \n\n \n From deterministic models to agent-based intelligence.\n Enterprises are evolving from rule-based and deterministic planning models toward multi-agent AI systems that collaborate across functions while retaining human oversight.\n \n \n\n Read more\n\n\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Actionable Takeaways for Enterprise Leaders\n \n \n \n \n Actionable Takeaways for Enterprise Leaders\n \n \n \n \n \n \n \n Design for disruption\, not stability.\n Assume supply chain shocks will continue. Build operating models that prioritize flexibility\, scenario planning\, and rapid reconfiguration.\n \n\n \n Refocus AI initiatives on core processes.\n Start with finance\, procurement\, supply planning\, logistics\, and service workflows where inefficiencies are well understood and ROI can be measured.\n \n\n \n Digitize end-to-end before scaling AI.\n Eliminate paper\, manual handoffs\, and siloed systems. AI delivers value only when underlying processes and data are fully digitized.\n \n\n \n Balance cost optimization with resilience.\n Evaluate sourcing\, manufacturing\, and logistics decisions through both cost and risk lenses to avoid trading short-term savings for long-term fragility.\n \n\n \n Adopt AI incrementally with governance.\n Deploy AI agents in constrained domains\, monitor performance\, and introduce human review where error tolerance is low.\n \n\n \n Strengthen supplier and partner integration.\n Increase real-time data sharing and visibility across supplier networks to detect quality\, capacity\, and delivery risks earlier.\n \n\n \n Use AI to accelerate decision speed\, not just insight.\n Prioritize applications that reduce manual effort and compress decision cycles\, enabling faster execution when conditions change.\n \n \n\n Read more\n\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n EVENT PHOTOS  \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Sponsors \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n NTT DATA is a $30+ billion trusted global innovator of business and technology services. We serve 75% of the Fortune Global 100 and are committed to helping clients innovate\, optimize and transform for long-term success. As a Global Top Employer\, we have experts in more than 50 countries and a robust partner ecosystem of established and startup companies. Our services include business and technology consulting\, data and artificial intelligence\, industry solutions\, as well as the development\, implementation and management of applications\, infrastructure and connectivity. We are also one of the leading providers of digital and AI infrastructure in the world. NTT DATA is part of NTT Group\, which invests over $3.6 billion each year in R&D to help organizations and society move confidently and sustainably into the digital future. Learn more at nttdata.com URL:https://bdionline.com/event/072325/ LOCATION:Gibsons Rosemont\, 5464 N River Rd\, Rosemont\, IL\, 60018\, United States CATEGORIES:Event Calendar,No Header ATTACH;FMTTYPE=image/webp:https://bdionline.com/wp-content/uploads/2025/06/hpechiagofeaturedimage-1.webp END:VEVENT BEGIN:VEVENT DTSTART;TZID=America/New_York:20250722T173000 DTEND;TZID=America/New_York:20250722T200000 DTSTAMP:20260416T140751 CREATED:20250523T170237Z LAST-MODIFIED:20260203T172414Z UID:112964-1753205400-1753214400@bdionline.com SUMMARY:Unlocking Agility And Scale In Marketing With AI DESCRIPTION:Event Recap: From Disruption to Advantage: AI-Powered Resilience in Supply Chains \n \n \n \n Rosemont\, IL | Gibsons Rosemont | November 13\, 2025 \n \n \n \n \n \n \n \n \n \n \n \n Speakers \n \n \n \n \n \n \n \n \n \n \n \n \n Ron Gilson \n \n \n NTT DATA Business Solutions \n \n \n \n \n \n \n \n Executive Advisor and Principal - Consumer Products and Agribusiness \n \n \n \n \n \n LinkedIn \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n John Buckley \n \n \n SAP \n \n \n \n \n \n \n \n Consumer Products Industry Advisor - Midwest Region \n \n \n \n \n \n LinkedIn \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Sai Simhadri \n \n \n Pampered Chef \n \n \n \n \n \n \n \n Senior Data Architect Manager \n \n \n \n \n \n LinkedIn \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Jody McDonough \n \n \n Sub-Zero Group\, Inc. \n \n \n \n \n \n \n \n VP of IT / CIO \n \n \n \n \n \n LinkedIn \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Executive SummaryEnterprise leaders described a clear shift in how supply chains\, operations\, and core business processes are being managed in an era defined by constant disruption. Resilience is no longer treated as a one-time corrective response to global shocks; it is becoming a permanent design principle. Organizations are rebalancing long-standing cost-optimization models with the need for flexibility\, visibility\, and faster decision-making across suppliers\, manufacturing\, logistics\, and service networks. The discussion highlighted that disruptions—geopolitical\, regulatory\, labor-related\, or demand-driven—are now expected\, not exceptional. AI emerged as an enabler rather than a starting point. Executives consistently emphasized that value comes from applying AI to clearly defined business problems\, supported by digitized\, high-quality data and integrated processes. Rather than pursuing broad or experimental AI initiatives\, leaders are embedding intelligence directly into core workflows such as demand planning\, transportation optimization\, supplier collaboration\, and service operations. The organizations seeing results are those that treat AI as a practical extension of operational discipline\, not a replacement for it. Looking forward\, competitive advantage will come from execution speed and adaptability. Companies that can move to “Plan B” faster—through scenario planning\, data transparency\, and orchestrated decision-making—are better positioned to turn disruption into opportunity. AI\, when grounded in clean data and governed processes\, is becoming a force multiplier for cost control\, service consistency\, and supply chain resilience. \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Key Themes \n \n \n \n Key Themes \n \n \n \n \n\n\n \n \n Resilience as a core operating model.\n Supply chain disruptions are now continuous. Organizations are redesigning processes to absorb shocks and respond dynamically\, rather than optimizing solely for steady-state efficiency.\n \n\n \n Cost pressure returning to the forefront.\n After a period dominated by availability and service\, cost optimization is re-emerging as a priority due to inflation\, tariffs\, and consumer resistance to price increases.\n \n\n \n Data readiness before AI adoption.\n AI effectiveness depends on digitized\, accurate\, and integrated data. Many organizations are still focused on building reliable data pipelines before scaling advanced analytics or AI agents.\n \n\n \n Targeted\, use-case-driven AI.\n The most successful AI initiatives are narrowly scoped and tied to measurable outcomes—such as freight optimization\, packaging efficiency\, demand sensing\, or service-part prediction.\n \n\n \n From deterministic models to agent-based intelligence.\n Enterprises are evolving from rule-based and deterministic planning models toward multi-agent AI systems that collaborate across functions while retaining human oversight.\n \n \n\n Read more\n\n\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Actionable Takeaways for Enterprise Leaders\n \n \n \n \n Actionable Takeaways for Enterprise Leaders\n \n \n \n \n \n \n \n Design for disruption\, not stability.\n Assume supply chain shocks will continue. Build operating models that prioritize flexibility\, scenario planning\, and rapid reconfiguration.\n \n\n \n Refocus AI initiatives on core processes.\n Start with finance\, procurement\, supply planning\, logistics\, and service workflows where inefficiencies are well understood and ROI can be measured.\n \n\n \n Digitize end-to-end before scaling AI.\n Eliminate paper\, manual handoffs\, and siloed systems. AI delivers value only when underlying processes and data are fully digitized.\n \n\n \n Balance cost optimization with resilience.\n Evaluate sourcing\, manufacturing\, and logistics decisions through both cost and risk lenses to avoid trading short-term savings for long-term fragility.\n \n\n \n Adopt AI incrementally with governance.\n Deploy AI agents in constrained domains\, monitor performance\, and introduce human review where error tolerance is low.\n \n\n \n Strengthen supplier and partner integration.\n Increase real-time data sharing and visibility across supplier networks to detect quality\, capacity\, and delivery risks earlier.\n \n\n \n Use AI to accelerate decision speed\, not just insight.\n Prioritize applications that reduce manual effort and compress decision cycles\, enabling faster execution when conditions change.\n \n \n\n Read more\n\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n EVENT PHOTOS  \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Sponsors \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n NTT DATA is a $30+ billion trusted global innovator of business and technology services. We serve 75% of the Fortune Global 100 and are committed to helping clients innovate\, optimize and transform for long-term success. As a Global Top Employer\, we have experts in more than 50 countries and a robust partner ecosystem of established and startup companies. Our services include business and technology consulting\, data and artificial intelligence\, industry solutions\, as well as the development\, implementation and management of applications\, infrastructure and connectivity. We are also one of the leading providers of digital and AI infrastructure in the world. NTT DATA is part of NTT Group\, which invests over $3.6 billion each year in R&D to help organizations and society move confidently and sustainably into the digital future. Learn more at nttdata.com URL:https://bdionline.com/event/072225/ LOCATION:Gibsons Italia\, 233 N Canal St\, Chicago\, 60606\, United States CATEGORIES:Event Calendar,No Header ATTACH;FMTTYPE=image/png:https://bdionline.com/wp-content/uploads/2025/05/ADOBE-CHICAGO.png END:VEVENT BEGIN:VEVENT DTSTART;TZID=America/New_York:20250717T173000 DTEND;TZID=America/New_York:20250717T200000 DTSTAMP:20260416T140751 CREATED:20250528T185520Z LAST-MODIFIED:20260203T172442Z UID:113046-1752773400-1752782400@bdionline.com SUMMARY:Executive Wine Tasting & Dinner -  Scalable AI in the Enterprise: Accelerating Innovation Through Infrastructure & Partnership DESCRIPTION:Event Recap: From Disruption to Advantage: AI-Powered Resilience in Supply Chains \n \n \n \n Rosemont\, IL | Gibsons Rosemont | November 13\, 2025 \n \n \n \n \n \n \n \n \n \n \n \n Speakers \n \n \n \n \n \n \n \n \n \n \n \n \n Ron Gilson \n \n \n NTT DATA Business Solutions \n \n \n \n \n \n \n \n Executive Advisor and Principal - Consumer Products and Agribusiness \n \n \n \n \n \n LinkedIn \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n John Buckley \n \n \n SAP \n \n \n \n \n \n \n \n Consumer Products Industry Advisor - Midwest Region \n \n \n \n \n \n LinkedIn \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Sai Simhadri \n \n \n Pampered Chef \n \n \n \n \n \n \n \n Senior Data Architect Manager \n \n \n \n \n \n LinkedIn \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Jody McDonough \n \n \n Sub-Zero Group\, Inc. \n \n \n \n \n \n \n \n VP of IT / CIO \n \n \n \n \n \n LinkedIn \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Executive SummaryEnterprise leaders described a clear shift in how supply chains\, operations\, and core business processes are being managed in an era defined by constant disruption. Resilience is no longer treated as a one-time corrective response to global shocks; it is becoming a permanent design principle. Organizations are rebalancing long-standing cost-optimization models with the need for flexibility\, visibility\, and faster decision-making across suppliers\, manufacturing\, logistics\, and service networks. The discussion highlighted that disruptions—geopolitical\, regulatory\, labor-related\, or demand-driven—are now expected\, not exceptional. AI emerged as an enabler rather than a starting point. Executives consistently emphasized that value comes from applying AI to clearly defined business problems\, supported by digitized\, high-quality data and integrated processes. Rather than pursuing broad or experimental AI initiatives\, leaders are embedding intelligence directly into core workflows such as demand planning\, transportation optimization\, supplier collaboration\, and service operations. The organizations seeing results are those that treat AI as a practical extension of operational discipline\, not a replacement for it. Looking forward\, competitive advantage will come from execution speed and adaptability. Companies that can move to “Plan B” faster—through scenario planning\, data transparency\, and orchestrated decision-making—are better positioned to turn disruption into opportunity. AI\, when grounded in clean data and governed processes\, is becoming a force multiplier for cost control\, service consistency\, and supply chain resilience. \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Key Themes \n \n \n \n Key Themes \n \n \n \n \n\n\n \n \n Resilience as a core operating model.\n Supply chain disruptions are now continuous. Organizations are redesigning processes to absorb shocks and respond dynamically\, rather than optimizing solely for steady-state efficiency.\n \n\n \n Cost pressure returning to the forefront.\n After a period dominated by availability and service\, cost optimization is re-emerging as a priority due to inflation\, tariffs\, and consumer resistance to price increases.\n \n\n \n Data readiness before AI adoption.\n AI effectiveness depends on digitized\, accurate\, and integrated data. Many organizations are still focused on building reliable data pipelines before scaling advanced analytics or AI agents.\n \n\n \n Targeted\, use-case-driven AI.\n The most successful AI initiatives are narrowly scoped and tied to measurable outcomes—such as freight optimization\, packaging efficiency\, demand sensing\, or service-part prediction.\n \n\n \n From deterministic models to agent-based intelligence.\n Enterprises are evolving from rule-based and deterministic planning models toward multi-agent AI systems that collaborate across functions while retaining human oversight.\n \n \n\n Read more\n\n\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Actionable Takeaways for Enterprise Leaders\n \n \n \n \n Actionable Takeaways for Enterprise Leaders\n \n \n \n \n \n \n \n Design for disruption\, not stability.\n Assume supply chain shocks will continue. Build operating models that prioritize flexibility\, scenario planning\, and rapid reconfiguration.\n \n\n \n Refocus AI initiatives on core processes.\n Start with finance\, procurement\, supply planning\, logistics\, and service workflows where inefficiencies are well understood and ROI can be measured.\n \n\n \n Digitize end-to-end before scaling AI.\n Eliminate paper\, manual handoffs\, and siloed systems. AI delivers value only when underlying processes and data are fully digitized.\n \n\n \n Balance cost optimization with resilience.\n Evaluate sourcing\, manufacturing\, and logistics decisions through both cost and risk lenses to avoid trading short-term savings for long-term fragility.\n \n\n \n Adopt AI incrementally with governance.\n Deploy AI agents in constrained domains\, monitor performance\, and introduce human review where error tolerance is low.\n \n\n \n Strengthen supplier and partner integration.\n Increase real-time data sharing and visibility across supplier networks to detect quality\, capacity\, and delivery risks earlier.\n \n\n \n Use AI to accelerate decision speed\, not just insight.\n Prioritize applications that reduce manual effort and compress decision cycles\, enabling faster execution when conditions change.\n \n \n\n Read more\n\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n EVENT PHOTOS  \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Sponsors \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n NTT DATA is a $30+ billion trusted global innovator of business and technology services. We serve 75% of the Fortune Global 100 and are committed to helping clients innovate\, optimize and transform for long-term success. As a Global Top Employer\, we have experts in more than 50 countries and a robust partner ecosystem of established and startup companies. Our services include business and technology consulting\, data and artificial intelligence\, industry solutions\, as well as the development\, implementation and management of applications\, infrastructure and connectivity. We are also one of the leading providers of digital and AI infrastructure in the world. NTT DATA is part of NTT Group\, which invests over $3.6 billion each year in R&D to help organizations and society move confidently and sustainably into the digital future. Learn more at nttdata.com URL:https://bdionline.com/event/071725/ LOCATION:Davio’s Boston Seaport\, 26 Fan Pier Boulevard\, Boston\, MA\, 02210\, United States CATEGORIES:Event Calendar,No Header ATTACH;FMTTYPE=image/png:https://bdionline.com/wp-content/uploads/2025/05/HPE-NVIDIA-EQUINIX-PREVIEW-IMAGE.png END:VEVENT BEGIN:VEVENT DTSTART;TZID=America/Los_Angeles:20250612T173000 DTEND;TZID=America/Los_Angeles:20250612T200000 DTSTAMP:20260416T140751 CREATED:20250409T130041Z LAST-MODIFIED:20260203T172445Z UID:111353-1749749400-1749758400@bdionline.com SUMMARY:Equinix Engage: Real-World Insights From Today’s Leaders in AI DESCRIPTION:Event Recap: From Disruption to Advantage: AI-Powered Resilience in Supply Chains \n \n \n \n Rosemont\, IL | Gibsons Rosemont | November 13\, 2025 \n \n \n \n \n \n \n \n \n \n \n \n Speakers \n \n \n \n \n \n \n \n \n \n \n \n \n Ron Gilson \n \n \n NTT DATA Business Solutions \n \n \n \n \n \n \n \n Executive Advisor and Principal - Consumer Products and Agribusiness \n \n \n \n \n \n LinkedIn \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n John Buckley \n \n \n SAP \n \n \n \n \n \n \n \n Consumer Products Industry Advisor - Midwest Region \n \n \n \n \n \n LinkedIn \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Sai Simhadri \n \n \n Pampered Chef \n \n \n \n \n \n \n \n Senior Data Architect Manager \n \n \n \n \n \n LinkedIn \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Jody McDonough \n \n \n Sub-Zero Group\, Inc. \n \n \n \n \n \n \n \n VP of IT / CIO \n \n \n \n \n \n LinkedIn \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Executive SummaryEnterprise leaders described a clear shift in how supply chains\, operations\, and core business processes are being managed in an era defined by constant disruption. Resilience is no longer treated as a one-time corrective response to global shocks; it is becoming a permanent design principle. Organizations are rebalancing long-standing cost-optimization models with the need for flexibility\, visibility\, and faster decision-making across suppliers\, manufacturing\, logistics\, and service networks. The discussion highlighted that disruptions—geopolitical\, regulatory\, labor-related\, or demand-driven—are now expected\, not exceptional. AI emerged as an enabler rather than a starting point. Executives consistently emphasized that value comes from applying AI to clearly defined business problems\, supported by digitized\, high-quality data and integrated processes. Rather than pursuing broad or experimental AI initiatives\, leaders are embedding intelligence directly into core workflows such as demand planning\, transportation optimization\, supplier collaboration\, and service operations. The organizations seeing results are those that treat AI as a practical extension of operational discipline\, not a replacement for it. Looking forward\, competitive advantage will come from execution speed and adaptability. Companies that can move to “Plan B” faster—through scenario planning\, data transparency\, and orchestrated decision-making—are better positioned to turn disruption into opportunity. AI\, when grounded in clean data and governed processes\, is becoming a force multiplier for cost control\, service consistency\, and supply chain resilience. \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Key Themes \n \n \n \n Key Themes \n \n \n \n \n\n\n \n \n Resilience as a core operating model.\n Supply chain disruptions are now continuous. Organizations are redesigning processes to absorb shocks and respond dynamically\, rather than optimizing solely for steady-state efficiency.\n \n\n \n Cost pressure returning to the forefront.\n After a period dominated by availability and service\, cost optimization is re-emerging as a priority due to inflation\, tariffs\, and consumer resistance to price increases.\n \n\n \n Data readiness before AI adoption.\n AI effectiveness depends on digitized\, accurate\, and integrated data. Many organizations are still focused on building reliable data pipelines before scaling advanced analytics or AI agents.\n \n\n \n Targeted\, use-case-driven AI.\n The most successful AI initiatives are narrowly scoped and tied to measurable outcomes—such as freight optimization\, packaging efficiency\, demand sensing\, or service-part prediction.\n \n\n \n From deterministic models to agent-based intelligence.\n Enterprises are evolving from rule-based and deterministic planning models toward multi-agent AI systems that collaborate across functions while retaining human oversight.\n \n \n\n Read more\n\n\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Actionable Takeaways for Enterprise Leaders\n \n \n \n \n Actionable Takeaways for Enterprise Leaders\n \n \n \n \n \n \n \n Design for disruption\, not stability.\n Assume supply chain shocks will continue. Build operating models that prioritize flexibility\, scenario planning\, and rapid reconfiguration.\n \n\n \n Refocus AI initiatives on core processes.\n Start with finance\, procurement\, supply planning\, logistics\, and service workflows where inefficiencies are well understood and ROI can be measured.\n \n\n \n Digitize end-to-end before scaling AI.\n Eliminate paper\, manual handoffs\, and siloed systems. AI delivers value only when underlying processes and data are fully digitized.\n \n\n \n Balance cost optimization with resilience.\n Evaluate sourcing\, manufacturing\, and logistics decisions through both cost and risk lenses to avoid trading short-term savings for long-term fragility.\n \n\n \n Adopt AI incrementally with governance.\n Deploy AI agents in constrained domains\, monitor performance\, and introduce human review where error tolerance is low.\n \n\n \n Strengthen supplier and partner integration.\n Increase real-time data sharing and visibility across supplier networks to detect quality\, capacity\, and delivery risks earlier.\n \n\n \n Use AI to accelerate decision speed\, not just insight.\n Prioritize applications that reduce manual effort and compress decision cycles\, enabling faster execution when conditions change.\n \n \n\n Read more\n\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n EVENT PHOTOS  \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Sponsors \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n NTT DATA is a $30+ billion trusted global innovator of business and technology services. We serve 75% of the Fortune Global 100 and are committed to helping clients innovate\, optimize and transform for long-term success. As a Global Top Employer\, we have experts in more than 50 countries and a robust partner ecosystem of established and startup companies. Our services include business and technology consulting\, data and artificial intelligence\, industry solutions\, as well as the development\, implementation and management of applications\, infrastructure and connectivity. We are also one of the leading providers of digital and AI infrastructure in the world. NTT DATA is part of NTT Group\, which invests over $3.6 billion each year in R&D to help organizations and society move confidently and sustainably into the digital future. Learn more at nttdata.com URL:https://bdionline.com/event/061225/ LOCATION:Spago\, 176 N Canon Dr\, Beverly Hills\, CA\, 90210\, United States CATEGORIES:Event Calendar,No Header ATTACH;FMTTYPE=image/webp:https://bdionline.com/wp-content/uploads/2025/04/equinix_losangeles.webp END:VEVENT BEGIN:VEVENT DTSTART;TZID=America/New_York:20250611T180000 DTEND;TZID=America/New_York:20250611T210000 DTSTAMP:20260416T140751 CREATED:20250512T193203Z LAST-MODIFIED:20260203T172448Z UID:112581-1749664800-1749675600@bdionline.com SUMMARY:Advancing AI Executive Dinner & Winetasting: Building the Future of Enterprise Innovation DESCRIPTION:Event Recap: From Disruption to Advantage: AI-Powered Resilience in Supply Chains \n \n \n \n Rosemont\, IL | Gibsons Rosemont | November 13\, 2025 \n \n \n \n \n \n \n \n \n \n \n \n Speakers \n \n \n \n \n \n \n \n \n \n \n \n \n Ron Gilson \n \n \n NTT DATA Business Solutions \n \n \n \n \n \n \n \n Executive Advisor and Principal - Consumer Products and Agribusiness \n \n \n \n \n \n LinkedIn \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n John Buckley \n \n \n SAP \n \n \n \n \n \n \n \n Consumer Products Industry Advisor - Midwest Region \n \n \n \n \n \n LinkedIn \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Sai Simhadri \n \n \n Pampered Chef \n \n \n \n \n \n \n \n Senior Data Architect Manager \n \n \n \n \n \n LinkedIn \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Jody McDonough \n \n \n Sub-Zero Group\, Inc. \n \n \n \n \n \n \n \n VP of IT / CIO \n \n \n \n \n \n LinkedIn \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Executive SummaryEnterprise leaders described a clear shift in how supply chains\, operations\, and core business processes are being managed in an era defined by constant disruption. Resilience is no longer treated as a one-time corrective response to global shocks; it is becoming a permanent design principle. Organizations are rebalancing long-standing cost-optimization models with the need for flexibility\, visibility\, and faster decision-making across suppliers\, manufacturing\, logistics\, and service networks. The discussion highlighted that disruptions—geopolitical\, regulatory\, labor-related\, or demand-driven—are now expected\, not exceptional. AI emerged as an enabler rather than a starting point. Executives consistently emphasized that value comes from applying AI to clearly defined business problems\, supported by digitized\, high-quality data and integrated processes. Rather than pursuing broad or experimental AI initiatives\, leaders are embedding intelligence directly into core workflows such as demand planning\, transportation optimization\, supplier collaboration\, and service operations. The organizations seeing results are those that treat AI as a practical extension of operational discipline\, not a replacement for it. Looking forward\, competitive advantage will come from execution speed and adaptability. Companies that can move to “Plan B” faster—through scenario planning\, data transparency\, and orchestrated decision-making—are better positioned to turn disruption into opportunity. AI\, when grounded in clean data and governed processes\, is becoming a force multiplier for cost control\, service consistency\, and supply chain resilience. \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Key Themes \n \n \n \n Key Themes \n \n \n \n \n\n\n \n \n Resilience as a core operating model.\n Supply chain disruptions are now continuous. Organizations are redesigning processes to absorb shocks and respond dynamically\, rather than optimizing solely for steady-state efficiency.\n \n\n \n Cost pressure returning to the forefront.\n After a period dominated by availability and service\, cost optimization is re-emerging as a priority due to inflation\, tariffs\, and consumer resistance to price increases.\n \n\n \n Data readiness before AI adoption.\n AI effectiveness depends on digitized\, accurate\, and integrated data. Many organizations are still focused on building reliable data pipelines before scaling advanced analytics or AI agents.\n \n\n \n Targeted\, use-case-driven AI.\n The most successful AI initiatives are narrowly scoped and tied to measurable outcomes—such as freight optimization\, packaging efficiency\, demand sensing\, or service-part prediction.\n \n\n \n From deterministic models to agent-based intelligence.\n Enterprises are evolving from rule-based and deterministic planning models toward multi-agent AI systems that collaborate across functions while retaining human oversight.\n \n \n\n Read more\n\n\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Actionable Takeaways for Enterprise Leaders\n \n \n \n \n Actionable Takeaways for Enterprise Leaders\n \n \n \n \n \n \n \n Design for disruption\, not stability.\n Assume supply chain shocks will continue. Build operating models that prioritize flexibility\, scenario planning\, and rapid reconfiguration.\n \n\n \n Refocus AI initiatives on core processes.\n Start with finance\, procurement\, supply planning\, logistics\, and service workflows where inefficiencies are well understood and ROI can be measured.\n \n\n \n Digitize end-to-end before scaling AI.\n Eliminate paper\, manual handoffs\, and siloed systems. AI delivers value only when underlying processes and data are fully digitized.\n \n\n \n Balance cost optimization with resilience.\n Evaluate sourcing\, manufacturing\, and logistics decisions through both cost and risk lenses to avoid trading short-term savings for long-term fragility.\n \n\n \n Adopt AI incrementally with governance.\n Deploy AI agents in constrained domains\, monitor performance\, and introduce human review where error tolerance is low.\n \n\n \n Strengthen supplier and partner integration.\n Increase real-time data sharing and visibility across supplier networks to detect quality\, capacity\, and delivery risks earlier.\n \n\n \n Use AI to accelerate decision speed\, not just insight.\n Prioritize applications that reduce manual effort and compress decision cycles\, enabling faster execution when conditions change.\n \n \n\n Read more\n\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n EVENT PHOTOS  \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Sponsors \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n NTT DATA is a $30+ billion trusted global innovator of business and technology services. We serve 75% of the Fortune Global 100 and are committed to helping clients innovate\, optimize and transform for long-term success. As a Global Top Employer\, we have experts in more than 50 countries and a robust partner ecosystem of established and startup companies. Our services include business and technology consulting\, data and artificial intelligence\, industry solutions\, as well as the development\, implementation and management of applications\, infrastructure and connectivity. We are also one of the leading providers of digital and AI infrastructure in the world. NTT DATA is part of NTT Group\, which invests over $3.6 billion each year in R&D to help organizations and society move confidently and sustainably into the digital future. Learn more at nttdata.com URL:https://bdionline.com/event/061125amd_oracle/ LOCATION:BE.STEAK.A\, 1887 S BASCOM AVE\, CAMPBELL\, CA\, 95008\, United States CATEGORIES:Event Calendar,No Header ATTACH;FMTTYPE=image/png:https://bdionline.com/wp-content/uploads/2025/05/AM-ADVANCING-AI-PREIVEIW-IMAGE.png END:VEVENT BEGIN:VEVENT DTSTART;TZID=America/Los_Angeles:20250611T180000 DTEND;TZID=America/Los_Angeles:20250611T210000 DTSTAMP:20260416T140751 CREATED:20250512T192316Z LAST-MODIFIED:20260203T172451Z UID:112556-1749664800-1749675600@bdionline.com SUMMARY:Advancing AI Executive Dinner & Winetasting: Building the Future of Enterprise Innovation with AMD & Lenovo DESCRIPTION:Event Recap: From Disruption to Advantage: AI-Powered Resilience in Supply Chains \n \n \n \n Rosemont\, IL | Gibsons Rosemont | November 13\, 2025 \n \n \n \n \n \n \n \n \n \n \n \n Speakers \n \n \n \n \n \n \n \n \n \n \n \n \n Ron Gilson \n \n \n NTT DATA Business Solutions \n \n \n \n \n \n \n \n Executive Advisor and Principal - Consumer Products and Agribusiness \n \n \n \n \n \n LinkedIn \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n John Buckley \n \n \n SAP \n \n \n \n \n \n \n \n Consumer Products Industry Advisor - Midwest Region \n \n \n \n \n \n LinkedIn \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Sai Simhadri \n \n \n Pampered Chef \n \n \n \n \n \n \n \n Senior Data Architect Manager \n \n \n \n \n \n LinkedIn \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Jody McDonough \n \n \n Sub-Zero Group\, Inc. \n \n \n \n \n \n \n \n VP of IT / CIO \n \n \n \n \n \n LinkedIn \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Executive SummaryEnterprise leaders described a clear shift in how supply chains\, operations\, and core business processes are being managed in an era defined by constant disruption. Resilience is no longer treated as a one-time corrective response to global shocks; it is becoming a permanent design principle. Organizations are rebalancing long-standing cost-optimization models with the need for flexibility\, visibility\, and faster decision-making across suppliers\, manufacturing\, logistics\, and service networks. The discussion highlighted that disruptions—geopolitical\, regulatory\, labor-related\, or demand-driven—are now expected\, not exceptional. AI emerged as an enabler rather than a starting point. Executives consistently emphasized that value comes from applying AI to clearly defined business problems\, supported by digitized\, high-quality data and integrated processes. Rather than pursuing broad or experimental AI initiatives\, leaders are embedding intelligence directly into core workflows such as demand planning\, transportation optimization\, supplier collaboration\, and service operations. The organizations seeing results are those that treat AI as a practical extension of operational discipline\, not a replacement for it. Looking forward\, competitive advantage will come from execution speed and adaptability. Companies that can move to “Plan B” faster—through scenario planning\, data transparency\, and orchestrated decision-making—are better positioned to turn disruption into opportunity. AI\, when grounded in clean data and governed processes\, is becoming a force multiplier for cost control\, service consistency\, and supply chain resilience. \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Key Themes \n \n \n \n Key Themes \n \n \n \n \n\n\n \n \n Resilience as a core operating model.\n Supply chain disruptions are now continuous. Organizations are redesigning processes to absorb shocks and respond dynamically\, rather than optimizing solely for steady-state efficiency.\n \n\n \n Cost pressure returning to the forefront.\n After a period dominated by availability and service\, cost optimization is re-emerging as a priority due to inflation\, tariffs\, and consumer resistance to price increases.\n \n\n \n Data readiness before AI adoption.\n AI effectiveness depends on digitized\, accurate\, and integrated data. Many organizations are still focused on building reliable data pipelines before scaling advanced analytics or AI agents.\n \n\n \n Targeted\, use-case-driven AI.\n The most successful AI initiatives are narrowly scoped and tied to measurable outcomes—such as freight optimization\, packaging efficiency\, demand sensing\, or service-part prediction.\n \n\n \n From deterministic models to agent-based intelligence.\n Enterprises are evolving from rule-based and deterministic planning models toward multi-agent AI systems that collaborate across functions while retaining human oversight.\n \n \n\n Read more\n\n\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Actionable Takeaways for Enterprise Leaders\n \n \n \n \n Actionable Takeaways for Enterprise Leaders\n \n \n \n \n \n \n \n Design for disruption\, not stability.\n Assume supply chain shocks will continue. Build operating models that prioritize flexibility\, scenario planning\, and rapid reconfiguration.\n \n\n \n Refocus AI initiatives on core processes.\n Start with finance\, procurement\, supply planning\, logistics\, and service workflows where inefficiencies are well understood and ROI can be measured.\n \n\n \n Digitize end-to-end before scaling AI.\n Eliminate paper\, manual handoffs\, and siloed systems. AI delivers value only when underlying processes and data are fully digitized.\n \n\n \n Balance cost optimization with resilience.\n Evaluate sourcing\, manufacturing\, and logistics decisions through both cost and risk lenses to avoid trading short-term savings for long-term fragility.\n \n\n \n Adopt AI incrementally with governance.\n Deploy AI agents in constrained domains\, monitor performance\, and introduce human review where error tolerance is low.\n \n\n \n Strengthen supplier and partner integration.\n Increase real-time data sharing and visibility across supplier networks to detect quality\, capacity\, and delivery risks earlier.\n \n\n \n Use AI to accelerate decision speed\, not just insight.\n Prioritize applications that reduce manual effort and compress decision cycles\, enabling faster execution when conditions change.\n \n \n\n Read more\n\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n EVENT PHOTOS  \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Sponsors \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n NTT DATA is a $30+ billion trusted global innovator of business and technology services. We serve 75% of the Fortune Global 100 and are committed to helping clients innovate\, optimize and transform for long-term success. As a Global Top Employer\, we have experts in more than 50 countries and a robust partner ecosystem of established and startup companies. Our services include business and technology consulting\, data and artificial intelligence\, industry solutions\, as well as the development\, implementation and management of applications\, infrastructure and connectivity. We are also one of the leading providers of digital and AI infrastructure in the world. NTT DATA is part of NTT Group\, which invests over $3.6 billion each year in R&D to help organizations and society move confidently and sustainably into the digital future. Learn more at nttdata.com URL:https://bdionline.com/event/061125amd_lenovo/ LOCATION:MILAN\, 1712 Meridian Avenue\, San Jose\, CA\, 95125\, United States CATEGORIES:Event Calendar,No Header ATTACH;FMTTYPE=image/png:https://bdionline.com/wp-content/uploads/2025/05/AM-ADVANCING-AI-PREIVEIW-IMAGE.png END:VEVENT BEGIN:VEVENT DTSTART;TZID=America/New_York:20250611T180000 DTEND;TZID=America/New_York:20250611T210000 DTSTAMP:20260416T140751 CREATED:20250512T183436Z LAST-MODIFIED:20260203T172452Z UID:112505-1749664800-1749675600@bdionline.com SUMMARY:Advancing AI Executive Dinner & Winetasting: Building the Future of Enterprise Innovation DESCRIPTION:Event Recap: From Disruption to Advantage: AI-Powered Resilience in Supply Chains \n \n \n \n Rosemont\, IL | Gibsons Rosemont | November 13\, 2025 \n \n \n \n \n \n \n \n \n \n \n \n Speakers \n \n \n \n \n \n \n \n \n \n \n \n \n Ron Gilson \n \n \n NTT DATA Business Solutions \n \n \n \n \n \n \n \n Executive Advisor and Principal - Consumer Products and Agribusiness \n \n \n \n \n \n LinkedIn \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n John Buckley \n \n \n SAP \n \n \n \n \n \n \n \n Consumer Products Industry Advisor - Midwest Region \n \n \n \n \n \n LinkedIn \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Sai Simhadri \n \n \n Pampered Chef \n \n \n \n \n \n \n \n Senior Data Architect Manager \n \n \n \n \n \n LinkedIn \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Jody McDonough \n \n \n Sub-Zero Group\, Inc. \n \n \n \n \n \n \n \n VP of IT / CIO \n \n \n \n \n \n LinkedIn \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Executive SummaryEnterprise leaders described a clear shift in how supply chains\, operations\, and core business processes are being managed in an era defined by constant disruption. Resilience is no longer treated as a one-time corrective response to global shocks; it is becoming a permanent design principle. Organizations are rebalancing long-standing cost-optimization models with the need for flexibility\, visibility\, and faster decision-making across suppliers\, manufacturing\, logistics\, and service networks. The discussion highlighted that disruptions—geopolitical\, regulatory\, labor-related\, or demand-driven—are now expected\, not exceptional. AI emerged as an enabler rather than a starting point. Executives consistently emphasized that value comes from applying AI to clearly defined business problems\, supported by digitized\, high-quality data and integrated processes. Rather than pursuing broad or experimental AI initiatives\, leaders are embedding intelligence directly into core workflows such as demand planning\, transportation optimization\, supplier collaboration\, and service operations. The organizations seeing results are those that treat AI as a practical extension of operational discipline\, not a replacement for it. Looking forward\, competitive advantage will come from execution speed and adaptability. Companies that can move to “Plan B” faster—through scenario planning\, data transparency\, and orchestrated decision-making—are better positioned to turn disruption into opportunity. AI\, when grounded in clean data and governed processes\, is becoming a force multiplier for cost control\, service consistency\, and supply chain resilience. \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Key Themes \n \n \n \n Key Themes \n \n \n \n \n\n\n \n \n Resilience as a core operating model.\n Supply chain disruptions are now continuous. Organizations are redesigning processes to absorb shocks and respond dynamically\, rather than optimizing solely for steady-state efficiency.\n \n\n \n Cost pressure returning to the forefront.\n After a period dominated by availability and service\, cost optimization is re-emerging as a priority due to inflation\, tariffs\, and consumer resistance to price increases.\n \n\n \n Data readiness before AI adoption.\n AI effectiveness depends on digitized\, accurate\, and integrated data. Many organizations are still focused on building reliable data pipelines before scaling advanced analytics or AI agents.\n \n\n \n Targeted\, use-case-driven AI.\n The most successful AI initiatives are narrowly scoped and tied to measurable outcomes—such as freight optimization\, packaging efficiency\, demand sensing\, or service-part prediction.\n \n\n \n From deterministic models to agent-based intelligence.\n Enterprises are evolving from rule-based and deterministic planning models toward multi-agent AI systems that collaborate across functions while retaining human oversight.\n \n \n\n Read more\n\n\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Actionable Takeaways for Enterprise Leaders\n \n \n \n \n Actionable Takeaways for Enterprise Leaders\n \n \n \n \n \n \n \n Design for disruption\, not stability.\n Assume supply chain shocks will continue. Build operating models that prioritize flexibility\, scenario planning\, and rapid reconfiguration.\n \n\n \n Refocus AI initiatives on core processes.\n Start with finance\, procurement\, supply planning\, logistics\, and service workflows where inefficiencies are well understood and ROI can be measured.\n \n\n \n Digitize end-to-end before scaling AI.\n Eliminate paper\, manual handoffs\, and siloed systems. AI delivers value only when underlying processes and data are fully digitized.\n \n\n \n Balance cost optimization with resilience.\n Evaluate sourcing\, manufacturing\, and logistics decisions through both cost and risk lenses to avoid trading short-term savings for long-term fragility.\n \n\n \n Adopt AI incrementally with governance.\n Deploy AI agents in constrained domains\, monitor performance\, and introduce human review where error tolerance is low.\n \n\n \n Strengthen supplier and partner integration.\n Increase real-time data sharing and visibility across supplier networks to detect quality\, capacity\, and delivery risks earlier.\n \n\n \n Use AI to accelerate decision speed\, not just insight.\n Prioritize applications that reduce manual effort and compress decision cycles\, enabling faster execution when conditions change.\n \n \n\n Read more\n\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n EVENT PHOTOS  \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Sponsors \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n NTT DATA is a $30+ billion trusted global innovator of business and technology services. We serve 75% of the Fortune Global 100 and are committed to helping clients innovate\, optimize and transform for long-term success. As a Global Top Employer\, we have experts in more than 50 countries and a robust partner ecosystem of established and startup companies. Our services include business and technology consulting\, data and artificial intelligence\, industry solutions\, as well as the development\, implementation and management of applications\, infrastructure and connectivity. We are also one of the leading providers of digital and AI infrastructure in the world. NTT DATA is part of NTT Group\, which invests over $3.6 billion each year in R&D to help organizations and society move confidently and sustainably into the digital future. Learn more at nttdata.com URL:https://bdionline.com/event/061125amd_vultr/ LOCATION:Mastro’s Steakhouse\, 2855 Stevens Creek Blvd Suite 1860\, Santa Clara\, CA\, 95050\, United States CATEGORIES:Event Calendar,No Header ATTACH;FMTTYPE=image/png:https://bdionline.com/wp-content/uploads/2025/05/AM-ADVANCING-AI-PREIVEIW-IMAGE.png END:VEVENT BEGIN:VEVENT DTSTART;TZID=America/Los_Angeles:20250611T180000 DTEND;TZID=America/Los_Angeles:20250611T210000 DTSTAMP:20260416T140751 CREATED:20250512T180452Z LAST-MODIFIED:20260203T172453Z UID:112482-1749664800-1749675600@bdionline.com SUMMARY:Advancing AI Executive Dinner & Winetasting: Building the Future of Enterprise Innovation with AMD & AWS DESCRIPTION:Event Recap: From Disruption to Advantage: AI-Powered Resilience in Supply Chains \n \n \n \n Rosemont\, IL | Gibsons Rosemont | November 13\, 2025 \n \n \n \n \n \n \n \n \n \n \n \n Speakers \n \n \n \n \n \n \n \n \n \n \n \n \n Ron Gilson \n \n \n NTT DATA Business Solutions \n \n \n \n \n \n \n \n Executive Advisor and Principal - Consumer Products and Agribusiness \n \n \n \n \n \n LinkedIn \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n John Buckley \n \n \n SAP \n \n \n \n \n \n \n \n Consumer Products Industry Advisor - Midwest Region \n \n \n \n \n \n LinkedIn \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Sai Simhadri \n \n \n Pampered Chef \n \n \n \n \n \n \n \n Senior Data Architect Manager \n \n \n \n \n \n LinkedIn \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Jody McDonough \n \n \n Sub-Zero Group\, Inc. \n \n \n \n \n \n \n \n VP of IT / CIO \n \n \n \n \n \n LinkedIn \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Executive SummaryEnterprise leaders described a clear shift in how supply chains\, operations\, and core business processes are being managed in an era defined by constant disruption. Resilience is no longer treated as a one-time corrective response to global shocks; it is becoming a permanent design principle. Organizations are rebalancing long-standing cost-optimization models with the need for flexibility\, visibility\, and faster decision-making across suppliers\, manufacturing\, logistics\, and service networks. The discussion highlighted that disruptions—geopolitical\, regulatory\, labor-related\, or demand-driven—are now expected\, not exceptional. AI emerged as an enabler rather than a starting point. Executives consistently emphasized that value comes from applying AI to clearly defined business problems\, supported by digitized\, high-quality data and integrated processes. Rather than pursuing broad or experimental AI initiatives\, leaders are embedding intelligence directly into core workflows such as demand planning\, transportation optimization\, supplier collaboration\, and service operations. The organizations seeing results are those that treat AI as a practical extension of operational discipline\, not a replacement for it. Looking forward\, competitive advantage will come from execution speed and adaptability. Companies that can move to “Plan B” faster—through scenario planning\, data transparency\, and orchestrated decision-making—are better positioned to turn disruption into opportunity. AI\, when grounded in clean data and governed processes\, is becoming a force multiplier for cost control\, service consistency\, and supply chain resilience. \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Key Themes \n \n \n \n Key Themes \n \n \n \n \n\n\n \n \n Resilience as a core operating model.\n Supply chain disruptions are now continuous. Organizations are redesigning processes to absorb shocks and respond dynamically\, rather than optimizing solely for steady-state efficiency.\n \n\n \n Cost pressure returning to the forefront.\n After a period dominated by availability and service\, cost optimization is re-emerging as a priority due to inflation\, tariffs\, and consumer resistance to price increases.\n \n\n \n Data readiness before AI adoption.\n AI effectiveness depends on digitized\, accurate\, and integrated data. Many organizations are still focused on building reliable data pipelines before scaling advanced analytics or AI agents.\n \n\n \n Targeted\, use-case-driven AI.\n The most successful AI initiatives are narrowly scoped and tied to measurable outcomes—such as freight optimization\, packaging efficiency\, demand sensing\, or service-part prediction.\n \n\n \n From deterministic models to agent-based intelligence.\n Enterprises are evolving from rule-based and deterministic planning models toward multi-agent AI systems that collaborate across functions while retaining human oversight.\n \n \n\n Read more\n\n\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Actionable Takeaways for Enterprise Leaders\n \n \n \n \n Actionable Takeaways for Enterprise Leaders\n \n \n \n \n \n \n \n Design for disruption\, not stability.\n Assume supply chain shocks will continue. Build operating models that prioritize flexibility\, scenario planning\, and rapid reconfiguration.\n \n\n \n Refocus AI initiatives on core processes.\n Start with finance\, procurement\, supply planning\, logistics\, and service workflows where inefficiencies are well understood and ROI can be measured.\n \n\n \n Digitize end-to-end before scaling AI.\n Eliminate paper\, manual handoffs\, and siloed systems. AI delivers value only when underlying processes and data are fully digitized.\n \n\n \n Balance cost optimization with resilience.\n Evaluate sourcing\, manufacturing\, and logistics decisions through both cost and risk lenses to avoid trading short-term savings for long-term fragility.\n \n\n \n Adopt AI incrementally with governance.\n Deploy AI agents in constrained domains\, monitor performance\, and introduce human review where error tolerance is low.\n \n\n \n Strengthen supplier and partner integration.\n Increase real-time data sharing and visibility across supplier networks to detect quality\, capacity\, and delivery risks earlier.\n \n\n \n Use AI to accelerate decision speed\, not just insight.\n Prioritize applications that reduce manual effort and compress decision cycles\, enabling faster execution when conditions change.\n \n \n\n Read more\n\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n EVENT PHOTOS  \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Sponsors \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n NTT DATA is a $30+ billion trusted global innovator of business and technology services. We serve 75% of the Fortune Global 100 and are committed to helping clients innovate\, optimize and transform for long-term success. As a Global Top Employer\, we have experts in more than 50 countries and a robust partner ecosystem of established and startup companies. Our services include business and technology consulting\, data and artificial intelligence\, industry solutions\, as well as the development\, implementation and management of applications\, infrastructure and connectivity. We are also one of the leading providers of digital and AI infrastructure in the world. NTT DATA is part of NTT Group\, which invests over $3.6 billion each year in R&D to help organizations and society move confidently and sustainably into the digital future. Learn more at nttdata.com URL:https://bdionline.com/event/061125amd_aws/ LOCATION:Morton’s The Steakhouse\, 184 S Market St Ste 100\, San Jose\, CA\, 95113\, United States CATEGORIES:Event Calendar,No Header ATTACH;FMTTYPE=image/png:https://bdionline.com/wp-content/uploads/2025/05/AM-ADVANCING-AI-PREIVEIW-IMAGE.png END:VEVENT BEGIN:VEVENT DTSTART;TZID=America/Los_Angeles:20250611T180000 DTEND;TZID=America/Los_Angeles:20250611T210000 DTSTAMP:20260416T140751 CREATED:20250512T172316Z LAST-MODIFIED:20260203T172454Z UID:112443-1749664800-1749675600@bdionline.com SUMMARY:Advancing AI Executive Dinner & Winetasting: Building the Future of Enterprise Innovation with AMD & Supermicro DESCRIPTION:Event Recap: From Disruption to Advantage: AI-Powered Resilience in Supply Chains \n \n \n \n Rosemont\, IL | Gibsons Rosemont | November 13\, 2025 \n \n \n \n \n \n \n \n \n \n \n \n Speakers \n \n \n \n \n \n \n \n \n \n \n \n \n Ron Gilson \n \n \n NTT DATA Business Solutions \n \n \n \n \n \n \n \n Executive Advisor and Principal - Consumer Products and Agribusiness \n \n \n \n \n \n LinkedIn \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n John Buckley \n \n \n SAP \n \n \n \n \n \n \n \n Consumer Products Industry Advisor - Midwest Region \n \n \n \n \n \n LinkedIn \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Sai Simhadri \n \n \n Pampered Chef \n \n \n \n \n \n \n \n Senior Data Architect Manager \n \n \n \n \n \n LinkedIn \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Jody McDonough \n \n \n Sub-Zero Group\, Inc. \n \n \n \n \n \n \n \n VP of IT / CIO \n \n \n \n \n \n LinkedIn \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Executive SummaryEnterprise leaders described a clear shift in how supply chains\, operations\, and core business processes are being managed in an era defined by constant disruption. Resilience is no longer treated as a one-time corrective response to global shocks; it is becoming a permanent design principle. Organizations are rebalancing long-standing cost-optimization models with the need for flexibility\, visibility\, and faster decision-making across suppliers\, manufacturing\, logistics\, and service networks. The discussion highlighted that disruptions—geopolitical\, regulatory\, labor-related\, or demand-driven—are now expected\, not exceptional. AI emerged as an enabler rather than a starting point. Executives consistently emphasized that value comes from applying AI to clearly defined business problems\, supported by digitized\, high-quality data and integrated processes. Rather than pursuing broad or experimental AI initiatives\, leaders are embedding intelligence directly into core workflows such as demand planning\, transportation optimization\, supplier collaboration\, and service operations. The organizations seeing results are those that treat AI as a practical extension of operational discipline\, not a replacement for it. Looking forward\, competitive advantage will come from execution speed and adaptability. Companies that can move to “Plan B” faster—through scenario planning\, data transparency\, and orchestrated decision-making—are better positioned to turn disruption into opportunity. AI\, when grounded in clean data and governed processes\, is becoming a force multiplier for cost control\, service consistency\, and supply chain resilience. \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Key Themes \n \n \n \n Key Themes \n \n \n \n \n\n\n \n \n Resilience as a core operating model.\n Supply chain disruptions are now continuous. Organizations are redesigning processes to absorb shocks and respond dynamically\, rather than optimizing solely for steady-state efficiency.\n \n\n \n Cost pressure returning to the forefront.\n After a period dominated by availability and service\, cost optimization is re-emerging as a priority due to inflation\, tariffs\, and consumer resistance to price increases.\n \n\n \n Data readiness before AI adoption.\n AI effectiveness depends on digitized\, accurate\, and integrated data. Many organizations are still focused on building reliable data pipelines before scaling advanced analytics or AI agents.\n \n\n \n Targeted\, use-case-driven AI.\n The most successful AI initiatives are narrowly scoped and tied to measurable outcomes—such as freight optimization\, packaging efficiency\, demand sensing\, or service-part prediction.\n \n\n \n From deterministic models to agent-based intelligence.\n Enterprises are evolving from rule-based and deterministic planning models toward multi-agent AI systems that collaborate across functions while retaining human oversight.\n \n \n\n Read more\n\n\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Actionable Takeaways for Enterprise Leaders\n \n \n \n \n Actionable Takeaways for Enterprise Leaders\n \n \n \n \n \n \n \n Design for disruption\, not stability.\n Assume supply chain shocks will continue. Build operating models that prioritize flexibility\, scenario planning\, and rapid reconfiguration.\n \n\n \n Refocus AI initiatives on core processes.\n Start with finance\, procurement\, supply planning\, logistics\, and service workflows where inefficiencies are well understood and ROI can be measured.\n \n\n \n Digitize end-to-end before scaling AI.\n Eliminate paper\, manual handoffs\, and siloed systems. AI delivers value only when underlying processes and data are fully digitized.\n \n\n \n Balance cost optimization with resilience.\n Evaluate sourcing\, manufacturing\, and logistics decisions through both cost and risk lenses to avoid trading short-term savings for long-term fragility.\n \n\n \n Adopt AI incrementally with governance.\n Deploy AI agents in constrained domains\, monitor performance\, and introduce human review where error tolerance is low.\n \n\n \n Strengthen supplier and partner integration.\n Increase real-time data sharing and visibility across supplier networks to detect quality\, capacity\, and delivery risks earlier.\n \n\n \n Use AI to accelerate decision speed\, not just insight.\n Prioritize applications that reduce manual effort and compress decision cycles\, enabling faster execution when conditions change.\n \n \n\n Read more\n\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n EVENT PHOTOS  \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Sponsors \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n NTT DATA is a $30+ billion trusted global innovator of business and technology services. We serve 75% of the Fortune Global 100 and are committed to helping clients innovate\, optimize and transform for long-term success. As a Global Top Employer\, we have experts in more than 50 countries and a robust partner ecosystem of established and startup companies. Our services include business and technology consulting\, data and artificial intelligence\, industry solutions\, as well as the development\, implementation and management of applications\, infrastructure and connectivity. We are also one of the leading providers of digital and AI infrastructure in the world. NTT DATA is part of NTT Group\, which invests over $3.6 billion each year in R&D to help organizations and society move confidently and sustainably into the digital future. Learn more at nttdata.com URL:https://bdionline.com/event/061125amd_supermicro/ LOCATION:Meso\, 3060 Olsen Dr #50\, San Jose\, CA\, 95128\, United States CATEGORIES:Event Calendar,No Header ATTACH;FMTTYPE=image/png:https://bdionline.com/wp-content/uploads/2025/05/AM-ADVANCING-AI-PREIVEIW-IMAGE.png END:VEVENT BEGIN:VEVENT DTSTART;TZID=America/New_York:20250611T180000 DTEND;TZID=America/New_York:20250611T200000 DTSTAMP:20260416T140751 CREATED:20250506T183011Z LAST-MODIFIED:20260203T172455Z UID:111962-1749664800-1749672000@bdionline.com SUMMARY:Advancing AI Executive Dinner & Winetasting: Building the Future of Enterprise Innovation DESCRIPTION:Event Recap: From Disruption to Advantage: AI-Powered Resilience in Supply Chains \n \n \n \n Rosemont\, IL | Gibsons Rosemont | November 13\, 2025 \n \n \n \n \n \n \n \n \n \n \n \n Speakers \n \n \n \n \n \n \n \n \n \n \n \n \n Ron Gilson \n \n \n NTT DATA Business Solutions \n \n \n \n \n \n \n \n Executive Advisor and Principal - Consumer Products and Agribusiness \n \n \n \n \n \n LinkedIn \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n John Buckley \n \n \n SAP \n \n \n \n \n \n \n \n Consumer Products Industry Advisor - Midwest Region \n \n \n \n \n \n LinkedIn \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Sai Simhadri \n \n \n Pampered Chef \n \n \n \n \n \n \n \n Senior Data Architect Manager \n \n \n \n \n \n LinkedIn \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Jody McDonough \n \n \n Sub-Zero Group\, Inc. \n \n \n \n \n \n \n \n VP of IT / CIO \n \n \n \n \n \n LinkedIn \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Executive SummaryEnterprise leaders described a clear shift in how supply chains\, operations\, and core business processes are being managed in an era defined by constant disruption. Resilience is no longer treated as a one-time corrective response to global shocks; it is becoming a permanent design principle. Organizations are rebalancing long-standing cost-optimization models with the need for flexibility\, visibility\, and faster decision-making across suppliers\, manufacturing\, logistics\, and service networks. The discussion highlighted that disruptions—geopolitical\, regulatory\, labor-related\, or demand-driven—are now expected\, not exceptional. AI emerged as an enabler rather than a starting point. Executives consistently emphasized that value comes from applying AI to clearly defined business problems\, supported by digitized\, high-quality data and integrated processes. Rather than pursuing broad or experimental AI initiatives\, leaders are embedding intelligence directly into core workflows such as demand planning\, transportation optimization\, supplier collaboration\, and service operations. The organizations seeing results are those that treat AI as a practical extension of operational discipline\, not a replacement for it. Looking forward\, competitive advantage will come from execution speed and adaptability. Companies that can move to “Plan B” faster—through scenario planning\, data transparency\, and orchestrated decision-making—are better positioned to turn disruption into opportunity. AI\, when grounded in clean data and governed processes\, is becoming a force multiplier for cost control\, service consistency\, and supply chain resilience. \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Key Themes \n \n \n \n Key Themes \n \n \n \n \n\n\n \n \n Resilience as a core operating model.\n Supply chain disruptions are now continuous. Organizations are redesigning processes to absorb shocks and respond dynamically\, rather than optimizing solely for steady-state efficiency.\n \n\n \n Cost pressure returning to the forefront.\n After a period dominated by availability and service\, cost optimization is re-emerging as a priority due to inflation\, tariffs\, and consumer resistance to price increases.\n \n\n \n Data readiness before AI adoption.\n AI effectiveness depends on digitized\, accurate\, and integrated data. Many organizations are still focused on building reliable data pipelines before scaling advanced analytics or AI agents.\n \n\n \n Targeted\, use-case-driven AI.\n The most successful AI initiatives are narrowly scoped and tied to measurable outcomes—such as freight optimization\, packaging efficiency\, demand sensing\, or service-part prediction.\n \n\n \n From deterministic models to agent-based intelligence.\n Enterprises are evolving from rule-based and deterministic planning models toward multi-agent AI systems that collaborate across functions while retaining human oversight.\n \n \n\n Read more\n\n\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Actionable Takeaways for Enterprise Leaders\n \n \n \n \n Actionable Takeaways for Enterprise Leaders\n \n \n \n \n \n \n \n Design for disruption\, not stability.\n Assume supply chain shocks will continue. Build operating models that prioritize flexibility\, scenario planning\, and rapid reconfiguration.\n \n\n \n Refocus AI initiatives on core processes.\n Start with finance\, procurement\, supply planning\, logistics\, and service workflows where inefficiencies are well understood and ROI can be measured.\n \n\n \n Digitize end-to-end before scaling AI.\n Eliminate paper\, manual handoffs\, and siloed systems. AI delivers value only when underlying processes and data are fully digitized.\n \n\n \n Balance cost optimization with resilience.\n Evaluate sourcing\, manufacturing\, and logistics decisions through both cost and risk lenses to avoid trading short-term savings for long-term fragility.\n \n\n \n Adopt AI incrementally with governance.\n Deploy AI agents in constrained domains\, monitor performance\, and introduce human review where error tolerance is low.\n \n\n \n Strengthen supplier and partner integration.\n Increase real-time data sharing and visibility across supplier networks to detect quality\, capacity\, and delivery risks earlier.\n \n\n \n Use AI to accelerate decision speed\, not just insight.\n Prioritize applications that reduce manual effort and compress decision cycles\, enabling faster execution when conditions change.\n \n \n\n Read more\n\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n EVENT PHOTOS  \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Sponsors \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n NTT DATA is a $30+ billion trusted global innovator of business and technology services. We serve 75% of the Fortune Global 100 and are committed to helping clients innovate\, optimize and transform for long-term success. As a Global Top Employer\, we have experts in more than 50 countries and a robust partner ecosystem of established and startup companies. Our services include business and technology consulting\, data and artificial intelligence\, industry solutions\, as well as the development\, implementation and management of applications\, infrastructure and connectivity. We are also one of the leading providers of digital and AI infrastructure in the world. NTT DATA is part of NTT Group\, which invests over $3.6 billion each year in R&D to help organizations and society move confidently and sustainably into the digital future. Learn more at nttdata.com URL:https://bdionline.com/event/061125amd1/ LOCATION:IL CATEGORIES:Event Calendar,No Header ATTACH;FMTTYPE=image/png:https://bdionline.com/wp-content/uploads/2025/05/AM-ADVANCING-AI-PREIVEIW-IMAGE.png END:VEVENT BEGIN:VEVENT DTSTART;TZID=America/New_York:20250605T120000 DTEND;TZID=America/New_York:20250605T140000 DTSTAMP:20260416T140751 CREATED:20250409T171617Z LAST-MODIFIED:20260203T172501Z UID:111407-1749124800-1749132000@bdionline.com SUMMARY:Unlocking Agility and Scale in Marketing with AI DESCRIPTION:Event Recap: From Disruption to Advantage: AI-Powered Resilience in Supply Chains \n \n \n \n Rosemont\, IL | Gibsons Rosemont | November 13\, 2025 \n \n \n \n \n \n \n \n \n \n \n \n Speakers \n \n \n \n \n \n \n \n \n \n \n \n \n Ron Gilson \n \n \n NTT DATA Business Solutions \n \n \n \n \n \n \n \n Executive Advisor and Principal - Consumer Products and Agribusiness \n \n \n \n \n \n LinkedIn \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n John Buckley \n \n \n SAP \n \n \n \n \n \n \n \n Consumer Products Industry Advisor - Midwest Region \n \n \n \n \n \n LinkedIn \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Sai Simhadri \n \n \n Pampered Chef \n \n \n \n \n \n \n \n Senior Data Architect Manager \n \n \n \n \n \n LinkedIn \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Jody McDonough \n \n \n Sub-Zero Group\, Inc. \n \n \n \n \n \n \n \n VP of IT / CIO \n \n \n \n \n \n LinkedIn \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Executive SummaryEnterprise leaders described a clear shift in how supply chains\, operations\, and core business processes are being managed in an era defined by constant disruption. Resilience is no longer treated as a one-time corrective response to global shocks; it is becoming a permanent design principle. Organizations are rebalancing long-standing cost-optimization models with the need for flexibility\, visibility\, and faster decision-making across suppliers\, manufacturing\, logistics\, and service networks. The discussion highlighted that disruptions—geopolitical\, regulatory\, labor-related\, or demand-driven—are now expected\, not exceptional. AI emerged as an enabler rather than a starting point. Executives consistently emphasized that value comes from applying AI to clearly defined business problems\, supported by digitized\, high-quality data and integrated processes. Rather than pursuing broad or experimental AI initiatives\, leaders are embedding intelligence directly into core workflows such as demand planning\, transportation optimization\, supplier collaboration\, and service operations. The organizations seeing results are those that treat AI as a practical extension of operational discipline\, not a replacement for it. Looking forward\, competitive advantage will come from execution speed and adaptability. Companies that can move to “Plan B” faster—through scenario planning\, data transparency\, and orchestrated decision-making—are better positioned to turn disruption into opportunity. AI\, when grounded in clean data and governed processes\, is becoming a force multiplier for cost control\, service consistency\, and supply chain resilience. \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Key Themes \n \n \n \n Key Themes \n \n \n \n \n\n\n \n \n Resilience as a core operating model.\n Supply chain disruptions are now continuous. Organizations are redesigning processes to absorb shocks and respond dynamically\, rather than optimizing solely for steady-state efficiency.\n \n\n \n Cost pressure returning to the forefront.\n After a period dominated by availability and service\, cost optimization is re-emerging as a priority due to inflation\, tariffs\, and consumer resistance to price increases.\n \n\n \n Data readiness before AI adoption.\n AI effectiveness depends on digitized\, accurate\, and integrated data. Many organizations are still focused on building reliable data pipelines before scaling advanced analytics or AI agents.\n \n\n \n Targeted\, use-case-driven AI.\n The most successful AI initiatives are narrowly scoped and tied to measurable outcomes—such as freight optimization\, packaging efficiency\, demand sensing\, or service-part prediction.\n \n\n \n From deterministic models to agent-based intelligence.\n Enterprises are evolving from rule-based and deterministic planning models toward multi-agent AI systems that collaborate across functions while retaining human oversight.\n \n \n\n Read more\n\n\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Actionable Takeaways for Enterprise Leaders\n \n \n \n \n Actionable Takeaways for Enterprise Leaders\n \n \n \n \n \n \n \n Design for disruption\, not stability.\n Assume supply chain shocks will continue. Build operating models that prioritize flexibility\, scenario planning\, and rapid reconfiguration.\n \n\n \n Refocus AI initiatives on core processes.\n Start with finance\, procurement\, supply planning\, logistics\, and service workflows where inefficiencies are well understood and ROI can be measured.\n \n\n \n Digitize end-to-end before scaling AI.\n Eliminate paper\, manual handoffs\, and siloed systems. AI delivers value only when underlying processes and data are fully digitized.\n \n\n \n Balance cost optimization with resilience.\n Evaluate sourcing\, manufacturing\, and logistics decisions through both cost and risk lenses to avoid trading short-term savings for long-term fragility.\n \n\n \n Adopt AI incrementally with governance.\n Deploy AI agents in constrained domains\, monitor performance\, and introduce human review where error tolerance is low.\n \n\n \n Strengthen supplier and partner integration.\n Increase real-time data sharing and visibility across supplier networks to detect quality\, capacity\, and delivery risks earlier.\n \n\n \n Use AI to accelerate decision speed\, not just insight.\n Prioritize applications that reduce manual effort and compress decision cycles\, enabling faster execution when conditions change.\n \n \n\n Read more\n\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n EVENT PHOTOS  \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Sponsors \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n NTT DATA is a $30+ billion trusted global innovator of business and technology services. We serve 75% of the Fortune Global 100 and are committed to helping clients innovate\, optimize and transform for long-term success. As a Global Top Employer\, we have experts in more than 50 countries and a robust partner ecosystem of established and startup companies. Our services include business and technology consulting\, data and artificial intelligence\, industry solutions\, as well as the development\, implementation and management of applications\, infrastructure and connectivity. We are also one of the leading providers of digital and AI infrastructure in the world. NTT DATA is part of NTT Group\, which invests over $3.6 billion each year in R&D to help organizations and society move confidently and sustainably into the digital future. 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