Firms that adopt AI grow headcount 10.2% over the two years following adoption, but these gains are entirely driven by high-intensity adopters. Low-intensity adopters see no statistically significant change.
Entry-level headcount grew even faster. At the companies making the largest AI investments, entry-level headcount grew 12% over the two years following adoption.
AI adoption and the associated gains are unevenly distributed. AI adopters are already larger, more engineering-intensive, more likely to be venture-backed, and faster-growing than non-adopters. These firms then grow faster upon adoption.
Firms that are Ramp customers are likely not a representative sample so I don’t entirely trust it, but it does counter the narrative. Also see their previous post on AI spending per employee: [...]
Firms that are Ramp customers are likely not a representative sample so I don’t entirely trust it, but it does counter the narrative. Also see their previous post on AI spending per employee:
The top 1% of firms spend $7.45K per employee per month. The top 10% spend $611 per employee per month. The median firm spends just $11.38 – about the cost of a seat on an enterprise ChatGPT or Claude subscription.
And while several high-profile proclamations have said you should be spending as much on AI as you do on a software engineer’s salary…no one is actually doing that. For the top 1% of spenders, per employee AI spend is still less than half the typical monthly salary for an engineer. Not to say that won’t change – AI spend is still rising – but very few firms, if any, are actually doing that.
[...]
The top 1% of firms grew spend per employee 14.1% last month. That said, we previously found evidence firms are increasingly opting for cheaper AI models, including ones from DeepSeek, the Chinese competitor to OpenAI and Anthropic. So while firms are applying cost discipline on the margin, that’s a function of total spend rising, and rising faster than firms’ willingness to switch to cheaper solutions.
I don't know if this really says much. This might be a case of population map. Especially with its geographic disclaimer: Those companies that are "high intensity" adoption also seemed to be much...
I don't know if this really says much. This might be a case of population map. Especially with its geographic disclaimer:
There’s also proliferation around who you know and the places you hire from. California-based tech companies are more likely to use AI than similar companies in New York. There’s no inherent reason for that, other than the fact AI spreads through networks.
Those companies that are "high intensity" adoption also seemed to be much smaller than low intensity or non-Ai companies. They can grow much faster becsuse they have a larger pocket to fill.
The only real conclusion I feel I can get from this is "Silicon Valley tech startups are hiring"
From the article:
Firms that are Ramp customers are likely not a representative sample so I don’t entirely trust it, but it does counter the narrative. Also see their previous post on AI spending per employee:
[...]
I don't know if this really says much. This might be a case of population map. Especially with its geographic disclaimer:
Those companies that are "high intensity" adoption also seemed to be much smaller than low intensity or non-Ai companies. They can grow much faster becsuse they have a larger pocket to fill.
The only real conclusion I feel I can get from this is "Silicon Valley tech startups are hiring"