The next phase of enterprise AI is moving beyond isolated copilots and experiments toward AI systems and agents capable of reasoning, accessing organizational knowledge, and taking action across business processes. For enterprise leaders, that creates enormous opportunity, but also new requirements for security, governance, observability, data access, and control.

This session will explore what organizations need to move AI from proof of concept to secure, scalable production. An AWS thought leader will examine the architectural and governance principles behind enterprise AI and agentic systems, including how organizations can connect models to trusted enterprise knowledge, manage agent access and identity, establish appropriate guardrails, and create an AI foundation that can safely extend across teams and use cases.

AI adoption is accelerating, but enterprise execution remains fragmented. Teams are experimenting with AI while still managing priorities, dependencies, approvals, resources, and critical initiatives across disconnected systems. The result can be more intelligence without greater organizational velocity.

This session will explore how Intelligent Work Management can close the gap between AI insight and business execution by connecting people, data, workflows, and AI within the context of how work actually gets done. Attendees will learn how organizations can use operational context to surface risk earlier, coordinate work across functions, maintain human oversight, and measure AI's impact against real business outcomes—not simply productivity gains.

Enterprise leaders face a critical paradox: they're investing heavily in AI infrastructure, but 74% of digital transformations still fail due to cross-system execution gaps, not strategy. The average knowledge worker now switches between 11 enterprise apps daily, yet most organizations have no unified way to see work status, track dependencies, or orchestrate handoffs across these systems.

Here's the deeper challenge: most AI tools treat each interaction as a blank slate. They see a snapshot of data, not the living record of how work actually gets done. That missing piece is context, the rich, operational intelligence embedded in structured work: every sheet built, every form submitted, every workflow triggered, every approval signed. When AI lacks this kind of context, it can't truly understand what matters or what's at stake across your business.

In this joint session, AWS and Smartsheet reveal why connecting governed AI intelligence to this operational context is the missing piece in successful AI adoption. We'll explore how leading Fortune 500 companies are breaking down silos between their AI infrastructure and execution context, pairing AWS's cloud foundation and AI services with Smartsheet's intelligent work management layer to deliver measurable ROI. You'll learn practical frameworks for extending your AWS investments across cross-functional teams and burning down commitments while solving real execution problems.