Something keeps coming up in the enterprise AI data that I think gets overlooked in most AI discussions. The failure rate is around 80%. That part gets attention. But the reason almost never does. 77% of failures: strategy, governance, change management 23% of failures: the actual technology Companies with strong data foundations get 10.3x ROI. Companies with weak data get 3.7x. Same models. Same vendors. Nearly 3x difference in outcomes based purely on what they built before touching any AI. And the leadership stat is the one I keep coming back to. 56% of AI projects lose active executive support within 6 months. Success rate with sustained sponsorship: 68%. Without it: 11%. Curious whether people think this changes as the tools get easier to use, or whether the organizational problems just get more expensive. Source: https://www.pertamapartners.com/insights/ai-project-failure-statistics-2026 Made a short visual breakdown of these numbers: AI narrated, cinematic style, about 3 minutes: https://youtu.be/cPwSmHR4qWk submitted by /u/MaJoR_-_007
Originally posted by u/MaJoR_-_007 on r/ArtificialInteligence