Most large financial institutions now have dozens of AI initiatives underway, yet many struggle to move beyond pilots to deliver consistent, enterprise-wide impact. As AI becomes embedded in core functions, from risk and compliance to operations and customer experience, leaders are rethinking how AI is designed, deployed, governed, and scaled.
As enterprises accelerate AI adoption, traditional virtualization models are being pushed to their limits by rising costs, growing data demands, and the need for greater flexibility across hybrid environments. This peer-to-peer lunch brings infrastructure, IT, and cloud leaders together to discuss how virtualization is evolving into a cloud-like operating model that supports AI workloads, modern applications, and future growth.
Most enterprises now have dozens of AI initiatives but few have a repeatable way to move from pilot to production at scale. As AI becomes embedded in core business processes, leading organizations are shifting from project-based experimentation to a standardized enterprise AI factory operating model. This peer discussion explores how large enterprises are designing AI factories that balance speed, governance, and reliability—using shared infrastructure, validated architectures, and clear operating models to deliver AI outcomes consistently across the organization.
AI is accelerating change across the world of work, but for senior HR leaders, the real opportunity goes beyond automation; it’s about foresight. This peer discussion explores how HR and People leaders are using AI to move beyond retrospective feedback and gain earlier insight into cultural signals, workforce risks, and leadership challenges. As organizations navigate ongoing economic and organizational change, HR leaders are increasingly expected to anticipate issues, support leaders in real time, and influence outcomes before problems escalate.
As enterprises accelerate AI adoption, traditional virtualization models are being pushed to their limits by rising costs, growing data demands, and the need for greater flexibility across hybrid environments.
Most enterprises now have dozens of AI initiatives but few have a repeatable way to move from pilot to production at scale. As AI becomes embedded in core business processes, leading organizations are shifting from project-based experimentation to a standardized enterprise AI factory operating model. This peer discussion explores how large enterprises are designing AI factories that balance speed, governance, and reliability—using shared infrastructure, validated architectures, and clear operating models to deliver AI outcomes consistently across the organization.
