3 signs your company is using AI incorrectly |
3 signs your company is using AI incorrectly
From the electric motor to modern AI, history shows the same pattern: productivity only rises when organizations reinvent how work happens.
The productivity numbers don’t lie. Or do they?
Most companies have now rolled out AI tools enterprise-wide. Licenses have been purchased. Trainings have been scheduled. Slack channels have been flooded with prompts. And yet, when leadership asks about the ROI, the room goes quiet.
This is not a new story. In 1987, economist Robert Solow looked at the data after years of massive corporate investment in personal computers and found something baffling: zero statistically significant improvement in productivity. Companies had bought the technology. They just had not changed how they worked. This became known as the productivity paradox, and it is playing out again right now with AI.
Here is the uncomfortable truth: most organizations are not suffering from a technology problem. They are suffering from a thinking problem. They got the tool. They skipped the strategy. I’m an AI transformation strategist, keynote speaker, and author of How to Do More with Less Using AI. I saw how AI changed my own team at Alibaba in 2018 and now I’m seeing the same mistakes happen in the wider industry.
Here are three signs your company is using AI wrong right now, and what to do instead.
1. You are measuring adoption, not outcomes
I was keynoting at a large Fortune 500 company the other day, and I heard that the big exec at the company was using adoption numbers by the number of people that logged into the tool. Yikes! I couldn’t believe that we were still looking at that as a verifiable number when it comes to AI adoption.
If your AI success metrics look like “percentage of employees who have logged in” or “number of prompts submitted per week,” you are measuring the wrong thing entirely.
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