technology
PushButton AI Team ·
Most AI implementations fail not because the technology is bad — but because they were optimizing for the wrong outcome from day one. Sound familiar? You bought the tool. Paid the subscription. Team
Most AI implementations fail not because the technology is bad — but because they were optimizing for the wrong outcome from day one.
Sound familiar?
You bought the tool. Paid the subscription. Team tried it twice and moved on. Now it's a $200/month reminder that AI didn't work for you. That's not a you problem. That's an outcome problem.
The World Economic Forum just published research on how AI-driven cities are failing their residents — not from lack of technology, but from measuring the wrong things. Efficiency metrics looked great. Human outcomes didn't.
Your business has the same risk. Vendors sell you capability. Nobody helps you define what success actually looks like for your specific operation. So you measure "are we using the tool" instead of "did we save 10 hours a week on this one task."
That's the shift.
Before you evaluate any AI tool, write one sentence: "This works if it saves us _____ hours/dollars on _____ specific task within 30 days." That's your filter. Everything else is noise.
One outcome. One measurement. One win.
What's the one business task you'd most want to hand off right now — and has AI ever actually delivered on that promise for you?
#AIStrategy #BusinessGrowth #SmallBusiness #AIImplementation
Hector Gonzalez Jimenez. Professor of Marketing, ESCP Business School ... AI, driven by disparities in skills, infrastructure and institutional ...
