AI systems rarely fail because of a flawed launch—they fail because organizations mistake initial trust for permanent trust. Whether in pricing, underwriting, or customer service, the real challenge isn't gaining approval or executive buy-in; it's ensuring someone continues to validate that the model remains accurate, relevant, and worthy of reliance as business conditions evolve. Building trust in AI is not a one-time milestone but an ongoing governance discipline, where continuous monitoring, retraining, and human oversight determine whether an AI investment delivers lasting value or quietly drifts into irrelevance.