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.
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.
