
The AI Productivity Story Is Starting to Sound Familiar
I've seen hype cycles before. This one has some of the same warning signs.
Crédito da imagem: Image via Source article. Used under fair use for news commentary. · source
Remember when collaborative robots were going to replace every assembly line worker by 2020? I do. I was at Kuka when we were fielding calls from Fortune 500 companies who wanted to know how fast they could deploy cobots across their entire operation. The answer, which nobody wanted to hear, was "slower than you think, and it'll cost more than the brochure says."
I'm getting the same feeling watching the AI productivity conversation right now.
Bloomberg ran a segment this week arguing that the AI productivity boost is overhyped. Their analysts, the folks who actually look at the numbers rather than the press releases, are saying what a lot of us in the trenches have been muttering for months. The gains aren't showing up where they're supposed to.
The Gap Between Demo and Deployment
Look, here's the thing. I spent over a decade watching companies buy industrial automation equipment, run a beautiful pilot program, then struggle for years to scale it. The demo always works. The demo is designed to work. What happens when you try to integrate that shiny new system with your 15-year-old ERP software and a workforce that wasn't trained for it? That's where things get interesting.
AI is following the same pattern. The demos are spectacular. I've seen language models write code, summarise documents, generate reports. Genuinely impressive stuff. But the productivity gains that were supposed to transform entire industries? They're proving harder to measure than the consultants promised.
Part of the problem is that we're measuring the wrong things. When I was working on automotive assembly automation, we had clear metrics: cycle time, defect rate, throughput. You could point to a number and say "this is better than it was." With AI productivity tools, what exactly are we measuring? That someone wrote an email faster? That a report got drafted in half the time but then needed three rounds of human editing?
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