"Of course, there's going to be a ton of experiments that don't work. But, like, has anybody ever started to ride a bike on the first try? No. We get up, we dust ourselves off, we keep experimenting, and somehow we figure it out. And it's the same thing with AI."
"We're on that jagged frontier, which is we're going to have some wins, and then we're going to see that trough, and then we're going to have some more wins,"
"this is all about experimentation."
Approximately 95% of enterprise AI pilots reportedly fail to pay off, creating skepticism about AI's value. High failure rates can reflect early-stage experimentation, iterative learning, and the need to explore many approaches before finding effective solutions. Nontechnical employees can adopt accessible tools to build useful applications, expanding the pool of innovators beyond traditional programmers. Adoption will likely follow a jagged path with intermittent wins and troughs. Organizational culture, executive engagement, and a willingness to experiment matter more than the technology alone for achieving long-term AI success.
Read at Fortune
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