Bringing proprietary AI in-house is not a workable plan that has occasional side effects. It is a bad move with a straight line to failure – and that’s not hyperbole. Gartner reports that 85% of enterprise AI initiatives fail directly, meaning they never advance beyond the prototype (proof-of-concept) stage. Producing a fieldable product is an outright impossibility for most enterprise teams. Those that beat the odds by getting past the prototype stage still only stand a desperate hope for success. Success with proprietary AI requires surviving a gauntlet of execution challenges covering training at scale, generalization, performance, field qualification testing, software engineering, systems integration, human-centered design, and other workstreams. Mix in a highly technical domain that is packed with esoteric engineering challenges and the typical enterprise stands no chance. I’m sorry, but that’s the reality.