Why Most AI Features Fail After Launch (And How PMs Can Prevent It) | HackerNoon

AI features don’t fail at launch, but they perform the best on day one. Unlike traditional software, AI systems deteriorate due to model drift, stale data, and evolving user behaviour. Early launch metrics do not quite capture the nuances of AI features and can create a false sense of success. After launch, PMs are likely to miss the warning signs of failures as users move on to available alternatives rather than complain about an AI feature. This brings us to the point that the best AI features are managed as a living system, and not a one-and-done project.