Artificial intelligence has moved from a back-office novelty to the system quietly shaping how insurers underwrite, price and pay claims. Adoption is now near-universal – 90% of insurers report being in some stage of generative AI evaluation, with 55% already in early or full adoption [Conning, 2025], though far fewer have genuinely upskilled their teams. Beneath that adoption curve sits a more uncomfortable question: are we all approaching this technology in the same way?

Emerging evidence suggests that confidence, caution and the permission to experiment with AI are not evenly distributed – and that the gap tracks less with ability than with environment: who gets access, who gets sponsored to build, and who sees themselves reflected in the teams shaping these models. Harvard Business School research across 140,000 workers found women adopt AI tools at a 25% lower rate than men – not because of any difference in competence, but because of how their use of AI is evaluated. A 2026 study confirmed the mechanism: women who use AI to produce identical work are judged as less capable, while men using the same tools are credited with initiative. In an industry where women hold 59% of the workforce but only 22% of C-suite seats, that asymmetry compounds fast.

This panel treats "is gender part of the equation?" as a genuine, open question rather than a settled one: interrogating the premise honestly, with the people actually building insurance's AI. Whether you are an AI enthusiast, a sceptic, or somewhere in between, you will leave with a clearer, evidence-led view of one of the industry's most consequential shifts – and a sense of what leaders can do about it on Monday morning.