A friend recently told me he’s worried AI will make his design skills irrelevant, that clients will soon use AI-powered tools instead of hiring him.
I told him, “Focus on doing what AI can’t.”
A friend recently told me he’s worried AI will make his design skills irrelevant, that clients will soon use AI-powered tools instead of hiring him.
I told him, “Focus on doing what AI can’t.”
We’ve all seen the headline: according to MIT’s “GenAI Divide” report, roughly 95% of enterprise generative-AI pilot programs deliver no measurable financial return (though the method used wasn’t as thorough as one would like). Sounds catastrophic, right? Wrong. Most AI initiatives are experiments, and that’s exactly what they should be. The only failure worth avoiding is failing without learning.
David Senra has read over 400 biographies of history’s greatest entrepreneurs, and he can quote them from memory with the fervor of a preacher.
A solopreneur just launched a product that would’ve required a 12-person team two years ago. A regional bank is approving loans in 4 minutes that used to take 4 days. A manufacturer eliminated 80% of their customer service queue without firing anyone; they redeployed them to solve complex problems AI couldn’t touch.
“This will take us about three months.”
I look across the table. “What would it take to ship something in two weeks?”
Silence. Then nervous laughter. Then, every single time, someone says: “Well, if we just…”
That moment. That’s where everything changes.
Over eight years ago, I founded Netek, an affective computing startup exploring how to measure human emotion through technology. This was before “AI” dominated every conference keynote and LinkedIn bio.
There’s a comforting narrative making the rounds in boardrooms and LinkedIn posts: “AI will democratize excellence. Everyone will perform like the best.”
It’s a nice story. It’s also dangerously wrong.