AI Risk Register : Tactical approach to AI Risk Management

​An effective AI Risk Register is the backbone of any risk management program. It transforms high-level principles into actionable, trackable controls—helping organizations navigate regulatory obligations, operational risks, and ethical challenges with clarity.

​In this session, we’ll explore a tactical approach to building and operationalizing AI Risk Registers, including:

• ​Building an AI Risk Register, Organize risks around AI use cases.

• ​Defining impact, likelihood, inherent risk (IR), control effectiveness (CE), and residual risk (RR).

• ​Mapping risks to frameworks such as ISO/IEC 42001, the EU AI Act, and NIST AI RMF.

• ​Integrating AI risks into enterprise GRC and vendor management programs.

​Whether you are building your first AI Risk Register or refining an existing one, this session will equip you with practical tools, templates, and insights to strengthen AI governance and risk management.

​

​Presenter:

​Harshit Chandel is a senior leader in Cybersecurity and AI Governance, Risk & Compliance , with 17+ years of work experience. In his recent role, Harshit served as Head of GRC at a leading fintech, driving enterprise-wide governance, risk, and compliance programs.

​Harshit is also an author and researcher, with IEEE publications including “Agentic AI in Fintech: Balancing Autonomy and Privacy in Multi-Agent Architecture” and “Emergent Ideas: A Framework for Measurable Privacy Controls.”

​His thought leadership emphasizes the importance of measurable, practical governance approaches that make AI risk management tangible for executives, regulators, and practitioners alike.