Heavy AI Adoption Linked To More Hiring, Not Layoffs, New Data Shows
A new Ramp study shows that the companies spending the most on AI are actually hiring more and not cutting the workforce.
There’s a flawed yet oft-repeated narrative that AI adoption in the workplace will inevitably lead to layoffs and job loss. The narrative’s been propagated by some of the most visible leaders in tech, including Anthropic CEO Dario Amodei and Block CEO Jack Dorsey, the latter of whom used AI as a rationale for laying off 40% of his staff.
But a new study from Ramp and Revelio Labs finds the opposite: The most enthusiastic adopters of AI are actually adding employees, not subtracting them.
“In a sample covering more than 21,000 U.S. firms,” Ramp lead economist Ara Kharazian wrote on Tuesday, “We find that companies that invest heavily in AI grow headcount 10% over the two years following adoption. Entry-level headcount grows 12%.”
The study, coming nearly four years after OpenAI released ChatGPT, should cool down some of the inflammatory rhetoric about AI and job loss, or at least contextualize it. To date, there’s been no sign of widespread job loss despite the availability of AI tools that can do human work. That could change as the technology gets stronger, but there’s little indication that today’s AI tools are job takers vs. job makers.
The benefits of using AI don’t seem to accrue right away, per the study. “The earliest signs of growth emerge roughly 6-12 months after adoption,” it found. “Perhaps after firms establish best practices, integrate AI tools into workflows, and are subsequently able to make new investments and hire staff.”
To be sure, there are some important caveats here. Overall AI investment across the companies studied is still quite small, with the heavy adopters spending $33.67 per employee per month on average. And many of the firms using AI and hiring are startups or venture-backed companies that have an imperative to grow. “Adopters are more technical, higher-paying, and more likely to be venture-backed,” the study said.
Still, for those seeking to categorically link AI adoption with job loss, the early data seems to be making the opposite case.
More: Listen to Ramp lead economist Ara Kharazian discuss what the company’s latest data says about AI adoption on Big Technology Podcast.
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Dario Amodei has repeatedly said in interviews that, in the short term, forces such as comparative advantage, Jevons paradox, and demand elasticity are likely to operate, meaning that jobs like software engineering may actually increase rather than disappear.
What he is warning about is the long term: as AI’s uneven capabilities gradually smooth out, there may come a point where comparative advantage no longer holds for humans. At that stage, unemployment could rise. And his point is that this “long term” may arrive surprisingly soon — possibly within just a few years.
Because accelerationists often selectively quote and distort Dario’s remarks, many misunderstandings have spread.
I hope that thoughtful people like you will understand his point correctly.
This does not refute AI displacement.
It shows the transition pattern: first AI lets ambitious firms expand faster, then the expanding firm needs fewer humans per unit of output.