The initial wave of AI experimentation is over. Now, technical and engineering leaders face a harder reality: transitioning from fragile prototypes to resilient, scalable production systems. For many enterprises, this transition is blocked by fragmented environments, “Shadow AI” sprawl, and the difficulty of integrating legacy data. Success is no longer defined by how fast you can build a demo, but by how reliably you can govern, secure, and evolve it over time. Join us for this executive session where we move beyond high-level strategy to examine the operational blueprints of successful AI scaling. Featuring insights from industry leaders, we will dissect the “Day 2" challenges of enterprise AI:
Operational Consistency: How to standardize AI deployment across data center, cloud, and edge without locking yourself in.
The Governance Gap: Practical frameworks for securing private data and managing “Shadow Agents” without stifling innovation.
Sustainable Economics: Real-world lessons on managing inference costs and infrastructure ROI as workloads expand.
