In view of the increasing use of AI across industries, expectations for AI risk management are rising. One of the cornerstones of risk management is the development of a robust internal control framework. But how can you make sure your controls are good enough, especially while the regulatory landscape remains unsettled, and the industry benchmarks are unclear?

In this round table, we will look at some of the key components of AI risk management frameworks and consider some of the requirements of emerging legislation, such as mandatory audits or conformity assessments of AI systems, and how a robust risk management framework can help organisations to meet those requirements. We will also discuss and debate what “good controls” look like, drawing on participants’ industry perspectives and different use cases, and we will seek to gauge participants’ level of confidence in their internal controls and the challenges they have faced in implementing an AI control framework.

By joining us and participating in this session, participants will:

• Better understand the challenge of designing an AI risk management framework
• Gain a view of different approaches to AI risk management that may be useful in different scenarios
• Improve their understanding of the key components of an AI control framework and how it can support their business by reducing risk and facilitating innovation
• Gain an appreciation of how an auditor may approach assurance over AI