
Why 80% of AI Projects Fail—and How to Make Yours Work
Most AI projects fail. That’s not clickbait—it’s a well-documented reality, with failure rates as high as 90% according to research from Carnegie Mellon, Gartner, and the Wall Street Journal. Dan Saffer, Associate Director of Outreach at Carnegie Mellon’s Human-Computer Interaction Institute, says the reasons are rarely technical. They’re human: bad data, poor UX, vague goals, and inflated expectations. In this post, we unpack the