A few months ago, I watched something interesting play out in a boardroom.
A big company was in talks to buy a small AI startup, the kind of deal people call AI M&A, (AI mergers and acquisitions).
The founders were excited.
The acquirer was excited.
Everyone said this was “the next big AI success story.”
On paper, the startup looked perfect.
Their demo was smooth.
Their slides were beautiful.
Their metrics were impressive.
But halfway through the review, the acquirer paused and said a sentence I’ll never forget:
“Show me how this actually works.”
And that’s when the room went quiet.
The model they claimed to have “built from scratch” was mostly stitched together using public tools.
The data they said was “proprietary” turned out to be borrowed from everywhere.
The accuracy they promised was never tested outside a demo.
The deal didn’t collapse because the team wasn’t talented.
It collapsed because they couldn’t prove anything.
That’s what people miss about AI M&A.
It’s not about buzzwords.
It’s not about fancy prototypes.
It’s not even about valuation.
It’s about evidence.
Today, acquirers ask simple questions that decide everything:
→ Who owns the data?
→ Can this system survive in the real world?
→ What happens when something goes wrong?
→ Is this an AI product or just an AI presentation?
And honestly, these aren’t “technical questions.”
They’re trust questions.
In the AI era, the strongest companies won’t be the ones with the loudest pitches.
They’ll be the ones who can open the box and say,
“Here’s how it works. Here’s why it works. And here’s the proof.”
