Why do AI Projects Fail?

There is a widely circulated claim that a Gartner report stated 85% of AI projects fail. In fact, the original Gartner press release was a forecast that from 2018 through to 2022, 85% of AI projects would deliver erroneous outcomes due to bias in the data, misaligned algorithms, or project team implementation.

Setting aside the misinterpretation, organizations that succeed in deploying AI tend to do four things differently:
· Redesign processes instead of automating bad workflows
· Provide training that explains what makes AI successful
· Establish governance to realize benefits and avoid pitfalls
· Lead change intentionally through structured change management

In my view, the most significant factor is that AI projects fail because organizations don’t incorporate AI into their project processes. It is inconsistent to expect successful AI deployment without integrating AI into the very processes that manage its implementation. AI projects do not fail because of the technology, but because organizations don’t embed AI into their project management methodology. For AI projects to succeed, organizations need to redesign project processes, provide targeted training, and reinforce governance and change management to sustain adoption.

Reference
Gartner. (2018, February 13). Gartner says nearly half of CIOs are planning to deploy artificial intelligence. Gartner Newsroom. https://www.gartner.com/en/newsroom/press-releases/2018-02-13-gartner-says-nearly-half-of-cios-are-planning-to-deploy-artificial-intelligence