Ramp and Revelio Labs study of 21,559 firms finds high-intensity AI adopters grew headcount by 10% over two years

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Sources:

Study: https://ramp.com/data/ai-jobs-impact

Charts: https://www.ft.com/content/8026eac6-16ad-467d-b8c3-c48c5af684e6?syn-25a6b1a6=1

Narrative violation: A new study of 21,559 firms in the U.S. finds that “companies that adopt AI tend to grow faster following adoption”.

“Firms making the largest AI investments grow employment by roughly 10% following adoption, while low-intensity adopters see no statistically significant change.”

“Entry-level headcount rises 12% for high-intensity adopters.”

“Gains emerge gradually and are broad across roles, including engineering, sales, administration, and customer service.”

“The results counter predictions that AI adoption will lead to broad job loss.”

The study is based on observed AI spending from Ramp card and bill pay data linked to Revelio Labs workforce records.

11h3K51

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Aaron Levie@levie

More data is showing the opposite of what many people expected with AI adoption and jobs. Ramp found that the more AI adoption a company has the more their headcount grows.

At Box, we recently did a survey of 1,600+ mid and large sized companies, and the findings were similar. 58% of respondents expected headcount to rise over the next three years. Interestingly, that figure climbs to 79% among the most mature adopters of AI. The more advanced AI adopters expected to grow their headcount at a greater rate in the future than others.

Of course it's true that the companies that can afford to adopt AI the most are also the ones that likely are seeing growth in their business, leading to more headcount. So the point of the story isn't necessarily that by adopting AI you will inherently grow.

*But* the most important takeaway is that the opposite is not proving out. The fears a couple years ago would have been that the companies adopting AI the most would be hiring fewer people.

But in reality this is what actually you should expect to happen. If a company can get more customers because they use AI in sales for account or market intelligence, they hire more sales people not fewer. If you can build way more software than before, you end up hiring more engineers because the projects get bigger and you take on more. And so on.

David Sacks@DavidSacks

Narrative violation: A new study of 21,559 firms in the U.S. finds that “companies that adopt AI tend to grow faster following adoption”.

“Firms making the largest AI investments grow employment by roughly 10% following adoption, while low-intensity adopters see no statistically significant change.”

“Entry-level headcount rises 12% for high-intensity adopters.”

“Gains emerge gradually and are broad across roles, including engineering, sales, administration, and customer service.”

“The results counter predictions that AI adoption will lead to broad job loss.”

The study is based on observed AI spending from Ramp card and bill pay data linked to Revelio Labs workforce records.

6h2.9K56

LIKES7

signüll@signulll

@rabois too early to tell tbh. the economic ripple effects are not even close to any meaningful convergence yet. & the tools sorta suck too but they will get better.

this i think roughly is the fomo effect playing out over the first few years.

Keith Rabois@rabois

Narrative violation:)

7h44171

RETWEETS255

David Sacks@DavidSacks

Narrative violation: A new study of 21,559 firms in the U.S. finds that “companies that adopt AI tend to grow faster following adoption”.

“Firms making the largest AI investments grow employment by roughly 10% following adoption, while low-intensity adopters see no statistically significant change.”

“Entry-level headcount rises 12% for high-intensity adopters.”

“Gains emerge gradually and are broad across roles, including engineering, sales, administration, and customer service.”

“The results counter predictions that AI adoption will lead to broad job loss.”

The study is based on observed AI spending from Ramp card and bill pay data linked to Revelio Labs workforce records.

11h11.9K5510

Cristóbal Valenzuela@c_valenzuelab

The interesting thing about viral narratives is that they don't have to be true to spread. There's now enough evidence pointing to the fact that AI usage does not kill jobs, but that might not matter if you feel like it does. The same goes for water usage, AI killing creativity, and so on.

Ara Kharazian@arakharazian

We can finally say AI isn't killing jobs.

A new paper from me, @tryramp, and @RevelioLabs uses firm-level spend and workforce data across 21K U.S. businesses to measure AI's impact on jobs.

Firms that adopt AI heavily grow headcount 10% over two years following adoption. Low adopters see no statistically significant change.

7h20710

Brian Albrecht@BrianCAlbrecht

AI adopters are obviously not random as the paper shows. They recognize it and don’t rely on this for the key comparisons.

But this is surely on a spectrum and at play with high vs low as well.

8h2843

Cody Blakeney@code_star

AI killing jobs … at companies that don’t use AI

Ara Kharazian@arakharazian

We can finally say AI isn't killing jobs.

A new paper from me, @tryramp, and @RevelioLabs uses firm-level spend and workforce data across 21K U.S. businesses to measure AI's impact on jobs.

Firms that adopt AI heavily grow headcount 10% over two years following adoption. Low adopters see no statistically significant change.

5h11330

Brian Albrecht@BrianCAlbrecht

Even if we assumed this was a completely tight causal study, we still have the missing intercept problem.

This comparison simply can’t be conclusive on the aggregate effect https://www.economicforces.xyz/p/the-invisible-hand-screws-up-your?utm_source=publication-search

8h2992

Brian Albrecht@BrianCAlbrecht

Okay. One more worry. We are looking at percentage growth for small firms. This is notoriously tricky and can bias things.

This shows up in the business dynamism literature https://www.bls.gov/opub/mlr/2013/article/clayton.htm

7h2972

Ara Kharazian@arakharazian

First, you should be skeptical.

Companies that adopt AI are already faster growing.

We control for that by comparing early adopters against firms who haven't adopted yet. This allowed us to build like-for-like control groups of firms on nearly identical pre-adoption growth paths.

9h722

Brian Albrecht@BrianCAlbrecht

For example high adopters are small, fast-growing, high-salary, tech-adjacent firms.

8h1491

Ara Kharazian@arakharazian

These gains are unevenly distributed.

A side result of this paper is that AI spreads through networks. Who funded you is a better predictor of AI adoption than the sector you’re in.

California-based tech companies are more likely to use AI than similar companies in New York.

There’s no inherent reason for that, but it's economically suboptimal.

9h351

Ara Kharazian@arakharazian

Take small businesses for example. They are less likely to use AI in the first place, but when they do, they use it more intensely.

They may not have a dedicated engineering or finance team, so AI can unlock new revenue streams that previously required higher upfront investment.

Ultimately, I think this is the mechanism by which firms increase headcount upon AI adoption, even though AI presumably fulfills new and existing tasks for their teams. They can go do more things now.

9h75

Keith Rabois@rabois

Narrative violation:)

Ara Kharazian@arakharazian

We can finally say AI isn't killing jobs.

A new paper from me, @tryramp, and @RevelioLabs uses firm-level spend and workforce data across 21K U.S. businesses to measure AI's impact on jobs.

Firms that adopt AI heavily grow headcount 10% over two years following adoption. Low adopters see no statistically significant change.

7h47220

Ara Kharazian@arakharazian

Our main result: firms that adopt AI grow headcount 10% over two years. Two caveats.

1. Growth subject to a minimum threshold: "Low" adopters, we defined as the bottom two terciles of per employee per month, spend on AI see no change in hiring. High adopters spend ~$30 per employee per month in the first 3 months (rising thereafter, but not thousands of dollars).

2. Learning curve: Firms don’t see gains until 6-12 months following adoption.

9h45

Ara Kharazian@arakharazian

Entry-level headcount grows even faster, 12% over two years.

This is our first evidence that high-AI adopting firms are hiring different kinds of employees.

We believe they are selecting for a new set of skills, specifically, people who know how to use AI and use it well.

Entry-level workers, especially recent graduates and college students, are a natural place to look.

9h41

Brian Albrecht@BrianCAlbrecht

Suppose you undercount headcount (big deal with small firms), then the firm’s AI spend per employee is mechanically inflated.

This makes it more likely to be classified as high AI.

If that undercount later corrects, the firm appears to have strong post-adoption growth.

7h2271

Ara Kharazian@arakharazian

Our paper is out TODAY, but this is not my last word. We will update these results as more data comes in.

Read our paper and explore your own job function: https://ramp.com/data/ai-jobs-impact

And read my substack about it here: https://econlab.substack.com/p/we-can-finally-say-ai-isnt-killing-jobs

9h72

BucketBoyPlunger@N8BIZNESS

@DavidSacks Is this an argument for government expansion? Not referring to AI usage of course David

11h59

GigaCocoN@GigaCocoN

@DavidSacks

11h45

Ramp and Revelio Labs study of 21,559 firms finds high-intensity AI adopters grew headcount by 10% over two years

Story Overview

Hiring gains appear across roles

Sample limits broader claims