There’s a number sitting in the middle of a new opinion piece in The Hill, and it deserves more attention than it’s getting.
Fourteen percent.
That’s the average productivity gain when AI was put into real customer support jobs, according to a widely cited economic study. Not a lab demo. Real workers, real shifts, real tickets.
And here’s the detail that matters most: the biggest gains went to the least experienced workers.
The new hire with the AI at her elbow closed the gap on the ten-year veteran. Fast.
Now hold that thought, because the rest of the story is what nobody rebuilt.
The piece was written by Gleb Tsipursky, a workplace consultant.
Fair notice, same as always on this page: he runs a consultancy, so he has a stake in companies hiring help for this problem. But his argument stands on named sources — Stanford’s 2026 AI Index, a McKinsey global survey, that economic study, Pew polling. The evidence is checkable. That earns the read.
His core finding, in plain words:
AI is everywhere. The rules around it are nowhere.
Stanford’s data shows AI reaching mass adoption at historic speed. McKinsey’s survey shows companies using it widely — but struggling to turn it into real, deep change.
His phrase for it: institutional absorption remains shallow.
Everybody grabbed the tool. Almost nobody rewrote the terms.
And the workers are standing right in that gap.
Think about what the 14 percent actually means on the ground.
Work got faster. But the job ladder got weaker. Entry-level roles — the bottom rungs, where people learn a trade — are quietly shrinking. Managers are redesigning teams around software instead of people.
Tsipursky says it in one clean line: faster work is not the same thing as a settled social contract.
Read that again. He said contract.
The productivity showed up. The terms never did.
Nobody rewrote hiring around this. Nobody rewrote training, or pay, or how a worker gets evaluated when half her output now runs through a machine.
The people with the least power in this shift — the new, the young, the entry-level — are the ones working with no stated terms at all. They got the tool. They never got the deal.
His second point lands even harder.
“Governance is no longer a brake on innovation. It is part of the innovation race itself.”
The winners of the next phase, he argues, won’t just be the ones with the strongest AI. They’ll be the ones with the most trusted systems — clear accountability, real workforce transitions, terms people can rely on.
If that sounds familiar, it should. This page published the same conclusion yesterday, from a different source, in a piece about companies that build governance in now. The record has the dates.
Two voices, two days, one finding: the rules aren’t the drag on the race. The rules are the race.
Now the part The Hill piece walks up to and stops short of.
Tsipursky’s divide is between organizations that treat AI as a total system shift and those still treating it like a clever app. The first group redesigns. The second waits to be overwhelmed.
True. But it leaves the worker waiting on her employer to do the redesigning.
Here’s what this page adds: you don’t have to wait.
A company’s governance protects the company. A nation’s laws protect the nation — Australia started writing theirs this very week. Both move at the speed of committees.
But the worker sitting with an AI at her elbow tonight can set her own terms now. What it’s allowed to shape. What she checks before she trusts it. What stays hers — her judgment, her record, her name on the work.
That’s not a policy proposal. That’s a contract. Stated terms, chosen conduct, a kept record — and it travels with her, from this employer to the next one, from this year’s tools to whatever replaces them.
The Faust Baseline has been that working contract, on the public record, since May of 2025. Not written for corporations. Written at a kitchen table, for the person at the table.
The companies are racing. The governments are drafting. The worker can be done by Friday.
The house rules are written. Sign when you’re ready.
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