CIO.com reported that “Generative AI still has accuracy and safety problems, and the copyright issues haven’t yet been settled in the courts, all of which could create legal liabilities or other problems. And, of course, many early projects will fail to offer any actual business value, making them a waste of time and resources.” The January 15, 2025 article entitled ” Fast vs. slow: the real impact of AI adoption speed” (https://www.cio.com/article/3634175/fast-vs-slow-the-real-impact-of-ai-adoption-speed.html) included these comments:
According to a September IDC survey, 70% of CIOs reported a 90% failure rate for their custom-built AI app projects, and two-thirds reported a 90% failure rate with vendor-led AI proof-of-concepts. And Rand Corp. puts the AI failure rate at over 80%.
However, some early adopters report revenue growth, productivity enhancement, and early efforts bearing fruit by helping companies develop critical skills and abilities related to gen AI. The Boston Consulting Group, in fact, says companies that have adopted AI early claim 1.5 times higher revenue growth than other companies. So how do you reconcile the high failure rates of AI projects and reports of business benefit by early adopters? Both of these things can be true. Early adopters will try many different approaches before they find ones that work, and the ones that work will be scaled up, put into production, and deliver value to enterprises.
What do you think?
First posted on https://www.vogelitlaw.com/blog/fast-ai-adoption-speed-may-not-be-a-benefit