According to a recent MIT report, a remarkable 95% of gen AI programs fail to deliver bottom-line returns. In the wake of that finding, most commentators focused their attention on trying to explain why so many programs fail. Nathan Furr and Andrew Shipilov, for example, recently highlighted for HBR the very real danger of the “experimentation trap,” in which pilots never connect to customer value or scale beyond the lab.