Enterprise AI is moving from assistants that recommend actions to agents capable of executing them. What changes when autonomous systems begin participating directly in business processes and workflows?

We’ll explore where companies are already moving from human-in-the-loop copilots toward increasingly autonomous operations, and what this means for decision-making, governance and accountability. The session will also examine where autonomy creates real value – and where human oversight still matters.

Models are only one part of the emerging agentic stack. This session explores agents, enterprise data, tools, MCP, permissions, memory, observability and orchestration, and where companies should build versus buy.

As the ecosystem expands, enterprises face a growing number of architectural and vendor decisions. We’ll look at which layers are becoming commodities, where differentiation still matters, and how technology leaders can avoid building an overly complex stack before the market has settled.

After years of pilots and experimentation, boards want measurable results. Enterprise leaders discuss where AI is generating productivity, revenue and cost savings, and which projects remain difficult to justify.

The conversation will go beyond headline productivity claims to examine how companies are actually measuring returns, what costs are often underestimated, and how long meaningful ROI takes to appear. We’ll also look at which use cases are scaling across the organization and which are still struggling to move beyond the pilot stage.