Oliver Patel

As AI adoption outpaces formal regulation in the U.S., large enterprises are being forced to lead on responsible AI without a prescriptive rulebook. This opening panel sets the tone for 2026, exploring how risk-based governance, self-regulatory commitments and evidence-driven decision-making can unlock innovation, rather than constrain it.

• Balancing innovation and accountability by applying risk-based governance models that scale across diverse AI use.

• Embedding practical standards and measurable evidence of responsible AI in action.

• Accelerating enterprise-wide AI enablement in a largely unregulated American landscape.

AI agents are moving from assistance to action by planning, executing, and triggering outcomes across business systems. This plenary examines the challenges organizations face as agentic AI enters core operating environments, including unclear accountability and expanding risk surfaces. Speakers will share practical approaches to governing AI agents responsibly while maintaining efficiency, control, and trust.

• Defining accountability for autonomous agent actions.

• Managing risk as agents operate across systems.

• Maintaining oversight without slowing execution.

Moving from principle to practice, organizations face growing pressure to translate assurance, transparency and security into day-to-day decision-making. This closing panel focuses on what comes next, highlighting practical actions that organizations can take to govern AI systems.