Happy Birthday to ChatGPT, which turned two years old on Saturday, Nov. 30. There’s been a huge amount of excitement, plus some of the usual reality-settling-in that comes with a technology breakthrough. Oh, and a boatload of uncertainty about where generative AI can provide the most benefit – and about whether some competitor is going to nail the technology’s use and leap ahead of the rest of us. To figure out where the insurance industry stands in its use of generative AI and where we can go next, I sat down with Fady Khayatt, a partner at Oliver Wyman He confirmed my suspicions that insurers are mostly doing small-scale pilots and are focusing on efficiency, rather than on radical reinvention of processes, governance and structure or on top-line growth. He encourages clients to raise their sights, based on three bits of guidance, in particular. One is to focus on areas where an insurance company can create a sustainable advantage, not just short-term gains. He said, for instance, that generative AI is greatly increasing the productivity of coders but said IT generally isn’t a competitive differentiator for insurers, so they may be better off adopting third-party solutions rather than invest heavily in innovating themselves. Fady said, “HR, and legal and compliance [also] aren't necessarily areas where insurers want to be developing their own proprietary solutions….The key is identifying areas that will create a distinct competitive advantage if insurers take the lead. This will be different for different players depending on their areas of focus and strategic priorities.” Another is “ensuring alignment with broader transformation objectives within the business. What we've seen so far is some Gen AI experimentation that's disconnected from broader change programs. You'll get more traction by integrating Gen AI thinking into existing transformation goals, whether that's developing a new line of business around energy transition or cyber, or upgrading the underwriting workbench.” Third is “making sure that the focus is on both top line and bottom line. There's been a lot of focus on efficiency, but we need to understand these opportunities from both a growth perspective and an efficiency perspective. Otherwise, you're looking through too narrow a lens.” Beyond the advice on how to think about where to apply generative AI, he ended on a key point that I think isn’t being emphasized enough: the need to “actually making transformation happen. There needs to be a business-led change rather than a technology-led change. If generative AI is really going to fulfill its promise, it has to change how key people in the business work and fundamentally change those processes.” I’ve long said that “everybody loves change… except for the change part.” Change is great when you can impose it on someone else, not so great when you have to do it yourself. Getting the full benefit out of generative AI will require very different ways of working, so, as Fady emphasizes, we have to help people, including ourselves, buy into the benefits of change. I hope you find the interview as interesting as I did. Cheers, Paul | 
