Why Most AI Projects Fail in Business -- And What to Do About It (New article)

Artificial Intelligence (AI) is a transformative force, currently reshaping the business landscape and almost all facets?of it.? While companies have adopted AI for a number of reasons – to improve productivity, or ?reduce costs – the major payoff, according to an IDC Research study, has been “improved innovation”. Indeed, early adopters, such as GE, Pfizer, Unilever, Nestle, and Siemens, have reaped significant benefits the use of AI in their product development efforts... cutting time-to-market (by as much as 50%), and a faster pace of innovation.

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But these leading firms with deep pockets, large IT departments, and considerable experience in introducing new ways of working are not typical. The average company fares much worse: The failure rate for AI projects in business is estimated to be as high as 80% on average, and most projects do not proceed past the pilot stage – it’s called “pilot paralysis”. ?A recent Harvard Business Review article says that most of the reasons for AI failure are “dumb ones”, the result of classic mistakes made by the AI Ops Team, and can be easily avoided.

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Before you, your colleagues, and your firm charge ahead with AI, take a look at this latest article on “why AI projects fail in business.” It’s based on solid research and is a peer reviewed article in a good journal. Many of the reasons for failure will be familiar ones to new product developers. There’s also a number of mitigating strategies offered for reducing the failure rates.

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Article is: “Why AI Projects Fail: Lessons from New Product Development”

Available as Article #10 at my website (it’s safe): ?

https://www.bobcooper.ca/articles/artificial-intelligence-in-npd

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There are lots more resources at that website on "AI for NPD" too.

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