Context
In an article by Pro Global for the MGAA, Mike Dalzell, Group Head of Governance, Risk and Compliance at Pro Global, states his belief that the insurance industry’s conversation about AI is already moving on. Dalzell sets out that, for the past couple of years, much of the focus has been on generative AI: what it can write, summarise, analyse or retrieve. The more interesting development now is agentic AI: these are AI programmes that do not simply produce an answer, but can autonomously take actions, make a series of decisions and adapt what they do in response to new information.
Key points to note and next actions
- This raises some questions from a compliance perspective. A tool that helps an underwriter summarise a submission is relatively easy to place within an existing control environment. A system that can interpret information, decide what should happen next, interact with other systems and potentially influence a customer outcome is something different.
- The risk is not necessarily that the AI gets one decision spectacularly wrong. More difficult is the possibility that a system begins to behave slightly differently from the way the organisation intended, and does so repeatedly, at scale.
- The article includes commentary on the shift in risk post-implementation, and what firms should consider doing now.
- Under the heading ‘Compliance needs to become more operational’, Dalzell states that compliance teams do not necessarily need to become data scientists, but they do need sufficiently good understanding of how an agent works to challenge the right things:
- What objective has it been given?
- What decisions is it permitted to make?
- What happens when it encounters something outside its expected parameters?
- Which decisions require human intervention?
- How would we know if its behaviour had started to drift?