"Generative AI is exceptional at producing language. But companies do not run on language: they run on memory, context, feedback, and constraints. That's the gap."
"A widely cited MIT-backed analysis found that around 95% of enterprise generative AI pilots fail to deliver meaningful results, with only about 5% making it to sustained production."
"Inside most companies today, two realities coexist: on one side, employees use tools like ChatGPT constantly. On the other, official enterprise AI initiatives struggle to scale beyond carefully controlled pilots."
"The problem isn't enthusiasm, or even capability: it's that the tools don't translate into real, operational change."
Generative AI has shown remarkable capabilities in language production, leading to high individual adoption. However, within organizations, it has proven ineffective, with around 95% of enterprise pilots failing to yield meaningful results. Companies operate on memory, context, feedback, and constraints, which generative AI does not adequately address. Despite widespread use of AI tools like ChatGPT, official enterprise initiatives often fail to scale beyond pilot programs, highlighting a significant gap between individual use and organizational impact.
Read at Fast Company
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