The rush to “AI everything” recently created a disconnect between the people building systems and the people meant to use them. At the same time, far too many so-called innovations are simply marketing theatre or layers of unnecessary complexity wrapped in buzzwords.
When everyone wants to automate and optimise everything, everywhere, all at once, the result is confusing, wasteful, and of no value to the enterprise. When 95 percent of AI projects fail to deliver financial impact, as a recent MIT study shows, that is not just a sign of growing pains, it’s a sign of strategic blindness.
We’ve confused speed with direction.
The irony is that the industry isn’t wrong about AI’s potential. It will reshape the enterprise. But not in its current form. We need a new, human-centric approach to AI, where technology is built with purpose and an understanding of where it adds value.
AI is a tool, not an oracle.
You still need people who understand what it’s doing, why it’s doing it, and what happens when it goes wrong. If a misplaced model run wipes your GitHub repo, the model won’t save you. Humans will.
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