Day Two | November 3
Here is the latest edition of the agenda. As we approach the event, we will be adding speakers and sessions to enhance your experience. To stay informed, please register your interest
Key topics
- Upskilling boards and executives on AI governance risks
- Improving AI literacy across senior leadership teams
- Strengthening board oversight and accountability for AI decisions
- Bridging the gap between technical complexity and executive decision-making
 | Ben Dynkin,Head of AI Governance – Global Markets,Barclays |
 | Rongsheng Gong,Chief Model Risk Officer,Huntington National Bank |
Key topics
- The challenges of maintaining meaningful human oversight as AI systems become more autonomous
- Emerging oversight approaches, including human-in-the-loop, human-on-the-loop, and human-in-command
- The evolving role of boards and senior management in governing increasingly autonomous AI systems
- Accountability, authority, and governance responsibilities from the board room to the front line
- Evolving U.S. and global regulatory expectations and industry approaches for human oversight and accountability
 | Naresh Raheja,Former Senior Risk Specialist & Examiner,OCC |
Key topics
- Applying risk-based governance across AI use cases
- Balancing governance controls with operational efficiency
- Prioritising oversight for high-impact AI systems
- Preventing governance processes from becoming barriers to innovation
 | Satyaki Dastidar,Former Senior Director Model Risk Management,Capital One |
Key topics
- Securing AI systems against emerging cyber threats
- Detecting Shadow AI and unauthorised AI usage
- Protecting enterprise data, models, and AI infrastructure
- Managing identity, access, and AI security exposure
Key topics
- Adapting governance frameworks to rapid AI evolution
- Managing governance lag across emerging AI capabilities
- Balancing innovation speed with risk oversight
- Building adaptive and scalable governance structures
 | Siddharth Dagar,Head of AI Governance,Santander US |
Key topics
- Scaling AI from targeted use cases to enterprise-wide adoption
- Navigating governance, information security, and risk management challenges
- Defining clear ownership, accountability, and operating models
- Key lessons learned from implementing AI in complex, regulated environments
 | Wei Ma,Managing Director,Head of Risk Modelling,SMBC |
Key topics
- How fragmented AI tools and platforms are increasing development and scaling costs
- The growing burden of multi-jurisdictional compliance on AI deployment and innovation
- Balancing national security concerns with global AI collaboration
- Preparing for regulatory fragmentation and sovereign AI strategies
Key topics
- Addressing shortages in AI governance and risk talent
- Upskilling governance, risk, and compliance professionals for AI
- Preparing governance teams for continuous AI evolution
- Developing interdisciplinary AI governance capabilities
 | Dhagash Mehta,Head of Applied Artificial Intelligence Research,BlackRock |
Key topics
- The convergence of AI, cyber, and operational excellence
- Why AI governance is becoming enterprise governance
- Building institutions capable of governing continuous change
- Trust and accountability as long-term competitive advantage
 | Linda Zhang,Executive Director, AI/ML and Data Platforms,JPMorgan Chase & Co |
 | Morgan Boyce,Executive Director – Head of Model Risk,Ally Financial |
 | Oscar Zheng, Executive Director – Head of Model Validation, Natixis |