Every Successful AI Pilot Creates a Hidden Liability A large US insurer once asked us to help modernize how claims got processed. RPA bots went in, two legacy systems got replaced with one platform, and the pilot numbers looked excellent, faster intake, fewer manual touchpoints, happier claims adjusters in the room where it was tested. Everyone in that room had reason to be pleased. The metrics were real, the adjusters were not exaggerating their relief, and on paper this looked like exactly the kind of automation story organizations like to tell about themselves. Eighteen months later, that same pilot was still running in exactly one regional office. The model had not gotten worse. Nothing about its performance had changed. What changed is that scaling it meant pulling in people who were never part of the pilot, a budget owner who had to fund the rollout, a compliance team that suddenly had to sign off on something that used to be a contained experiment, an operations lead who had to ...