Your AI Pilot Didn’t Fail. Your Org Chart Did.

IntroductionMost carriers have stopped asking whether AI works. So why does so little of it ever leave the pilot?Kurt Diederich has spent 25 years building the core policy, billing, and claims systems that property and casualty insurers run on. Two years ago he looked at AI and, in his words, thought it was a pile of trash. He kept retrying it every six months anyway, and the thing that flipped him was a bread recipe. He asked a model to cut it in half, it correctly turned tablespoons into one and a half teaspoons, and he went in with both feet.That arc is the episode. Kurt walks through the adoption curve he sees in most organizations, from skepticism, to being wowed, to badly overestimating what the technology can do, and then the hard landing into execution where the roadblocks show up. His argument is that the software was never the constraint. The constraint is whether a company will restructure how it works, put the right people in front of the change, and actually measure what it gets.Guest BioKurt Diederich is the Chief Executive Officer and co-founder of Finys, a Troy, Michigan software company whose Suite covers policy administration, billing, claims, portals, and business intelligence for P&C carriers, mutuals, and state FAIR Plans. He started writing assembly-language games as a teenager on TRS-80s and Apple IIs, worked his way through college as a consultant, and has been an entrepreneur ever since. He spent the 1990s building custom claims and policy systems for carriers, then founded Finys in 2001 and went all in on insurance, building the platform on Microsoft .NET. Finys marked its 25th anniversary in 2026 and employs roughly 175 people.Key Topics-The four-stage adoption curve - Skepticism, then being wowed, then overestimating what AI can do, then the drop into execution where the real roadblocks appear.-30% versus three to five times - Let people work the way they always have and you get a modest lift. Restructure the work into small pods and the number changes completely.-The SDLC becomes the AI PLC - Kurt argues the software development lifecycle is turning into a product lifecycle, where the idea of developers sitting down to write code starts to go away.-The 40-point measurement gap - Studies found developers predicting a 20% productivity gain while actually running a 20% deficit, and most organizations never measure at all.-Champions rather than training - Training wears off because people default back to old habits. Kurt uses peopl