AI risk management starts with the board. Board directors play a critical role in setting the firm's risk appetite, establishing context and objectives, and ensuring that AI initiatives align with overall strategy. Well-established risk management frameworks like ISO 31000, COSO ERM, and the NIST Cybersecurity Framework can be adapted for AI-specific risks.
The risk management process begins with establishing context and objectives — understanding the current regulatory environment and the specific uses of AI within the organization. This includes data flow mapping, a critical step in risk identification that helps boards understand jurisdictional data flows and regulatory requirements.
Risk assessment encompasses identification, analysis, and evaluation. AI introduces unique risk categories including bias, opacity, data provenance challenges, and rapidly evolving regulatory requirements. Boards must ensure assessment processes are comprehensive and regularly updated.
Risk treatment options include avoidance (choosing not to deploy AI in high-risk contexts), mitigation (implementing technical guardrails and human oversight), transfer (through insurance or contractual allocation), and acceptance (where risks fall within the organization's defined tolerance). Each approach has implications that boards should understand.
Recording and reporting should be carefully documented to support transparency and accountability. By creating and preserving records, organizations can demonstrate compliance with regulatory obligations and industry standards. Despite mitigation strategies, risks may still be realized — having a well-crafted response plan minimizes impact.
Effective risk management is continuous, not a one-time exercise. Given the speed at which AI and related legal obligations evolve, boards must regularly evaluate their AI risks and opportunities. This involves assessing whether the existing program still meets organizational needs, identifying new risks, finding areas for improvement, and implementing changes that strengthen the program's effectiveness.