But 80% of AI projects in business fail... find out why in new article in IEEE Engineering Management Review
Dr. Robert G. Cooper
Professor Emeritus, McMaster University, Canada, ISBM Distinguished Research Fellow at Penn State University
The last few Spotlights have revealed the benefits of AI for use in new product development (NPD). But before you head out on the AI journey, it’s best that you learn about the pitfalls along the away. There are some, but all most all are avoidable… read on!
AI projects have an alarming failure rate! Estimated AI project failure rates, as high as 80%, are almost double the failure rate of IT projects a decade ago, and higher than the failure rate for new products.? A recent Harvard Business Review article points out that almost all failure causes are “dumb reasons”, the result of poor business practices, and can be avoided.
In this new 2024 article in IEEE Engineering Management Review, find out what the most common AI failure reasons are, and what you and your AI project teams can do to avoid them. To people in NPD, many of the failure reasons for AI are familiar, such as a lack of understanding of users’ needs, or technical issues due to lack of testing. But these deja vu reasons are not familiar to everyone in the company, especially to IT folks on AI project teams. One suggestion – get people who are experienced in NPD on the AI Ops Team, as well as people from the user community…. a cross-functional team, not just AI IT-techs!
?The full article “Why AI Project Fail” is available from my (safe!) website at:
There are 12 other articles and YouTube videos on that website on “AI for NPD” and what you need to know to get up to speed… and try to become “AI literate”. Try reading one or 2 articles a week.
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Other NPD topics are at:
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