About the session

From Autonomy to Accountability: A Product Framework for Agentic AI Governance

Learn to treat compliance as a core product feature by using automated compliance rules and deterministic guardrails to safely deploy autonomous AI agents in highly regulated markets.

As financial services adopt autonomous AI agents, traditional manual compliance creates massive delivery bottlenecks. This session explores how Product Managers can embed deterministic guardrails and machine-readable engineering controls directly into the agent architecture, treating governance as a core product capability. Attendees will learn to build auditable, autonomous agents that safely balance rapid innovation with strict regulatory accountability.

What you will take away

• Treat compliance as a product capability rather than a manual review step at the end.
• Embed deterministic guardrails and machine-readable controls directly into agent architecture.
• Build autonomous AI systems that are auditable while still supporting rapid innovation.

About the speaker

About Deepesh

Deepesh Khanna is an Enterprise AI and Technology Executive with over 17 years of experience driving AI governance, cloud transformation, and technology strategy across Fortune 100 financial institutions. Currently serving as the Senior Manager of Architecture Strategy & Governance at Capital One, Deepesh defines the long-term enterprise strategy for Responsible AI and Agentic AI governance. His leadership enables the secure, scalable, and compliant adoption of Generative AI technologies across an ecosystem of more than 3,000 enterprise applications.

A recognized AI researcher and IEEE Senior Member, Deepesh holds a Master of Science in Artificial Intelligence from the University of Texas, Austin. He actively contributes to the broader technology community as an international technology judge, the Vice President of the PDMA Washington DC Chapter, and was the AWS AI League Global 2nd Runner-Up.