# AI-intensive companies are growing and hiring faster

Markdown copy of https://realalpha.app/s/ai-intensive-companies-are-growing-and-hiring-faster/ on Real Alpha, the best minutes from long interviews with the people building AI. Cite and link the page, not this copy.

- Speaker: [Eric Glyman](https://realalpha.app/people/eric-glyman/) · Eric Glyman is cofounder and co-CEO of Ramp. · Co-founded Ramp, now used by 85,000 businesses and building AI tools to automate finance and manage company spend.
- Host: [Christine Anderson](https://realalpha.app/people/christine-anderson/) · Global Head of Corporate Affairs, Blackstone
- Show: Inside Blackstone
- Episode: [Ramp Co-Founder and Co-CEO Eric Glyman on AI Adoption, Jobs, and Token Spend](https://realalpha.app/v/cgXAk8pZ1uA/), Nov 3, 2026
- Moment: 10:30 to 15:51 of the episode (5 min), playing on https://realalpha.app/s/ai-intensive-companies-are-growing-and-hiring-faster/; the episode from there: https://realalpha.app/v/cgXAk8pZ1uA/?t=630

## Quote

> “these firms, despite growing at these same rates, were **hiring 12% more people** than ones who did not or would adopt it later.”
> — [Eric Glyman](https://realalpha.app/people/eric-glyman/) at [15:13](https://realalpha.app/v/cgXAk8pZ1uA/?t=913) · Inside Blackstone

## Takeaways

1. Top-quartile AI spenders roughly doubled revenue over three years.
2. AI adoption reaches beyond tech, including healthcare and manufacturing.
3. Firms spending at least $30 per employee monthly hired 12% more.

## About this segment

Ramp’s spending data links heavier AI use with faster revenue growth, and firms spending more on AI hired 12% more people. The findings challenge the idea that AI adoption is already reducing jobs.

From “Ramp Co-Founder and Co-CEO Eric Glyman on AI Adoption, Jobs, and Token Spend”, Nov 3, 2026. [Watch the full episode](https://realalpha.app/v/cgXAk8pZ1uA/)

## Transcript

From the transcript Inside Blackstone publishes with the episode.

[10:36](https://realalpha.app/v/cgXAk8pZ1uA/?t=636) And you see all of the payments and where they spend money. So what are some of the things you've learned that might surprise people about how businesses spend money? What has been most surprising to me, when we look at the aggregated data is, what feels at times is there's almost two economies is been the biggest change from what we saw years ago. Maybe just to jump to the topic that's on the mind of a lot of people is AI.

[11:00](https://realalpha.app/v/cgXAk8pZ1uA/?t=660) We were looking, about a year ago, and this set us off to creating an Economics Lab focused on AI spend in particular, but at the time we had about 50, 000 businesses and we were trying to separate, okay, this AI line item is getting big. Does it matter? Are these businesses growing quickly or not? And it turned out that the top quartile of businesses, about 12, 500 businesses, of most intense spend over a three- year period after ChatGPT came out, roughly doubled the revenue.

[11:28](https://realalpha.app/v/cgXAk8pZ1uA/?t=688) And these are not just tech businesses. It's like a roofer in Utah, a construction firm in Florida. They were growing a lot faster with a lot less overhead. And then there were the businesses that didn't adopt AI, the bottom quartile. Over a three- year period, they were roughly flat. They grew about 10%. Okay, I wanna, I wanna break this down a little bit more. Let’s go. Yeah. So let's start at the top around your monthly AI index that you… Yes. … put out.

[11:51](https://realalpha.app/v/cgXAk8pZ1uA/?t=711) So it's a real- time snapshot… Yup. … of how businesses are adopting AI. What are you seeing? It is happening, very quickly, and it is happening at a rate that's faster. If you look at kind of census estimates, I think that the most recent census estimate, which is survey- based, says roughly 22% to 25% of businesses are spending, and we see when you actually... On AI? On AI. But when you look at actual spend data, we think it's significantly higher. So your data is ahead of government data in terms of AI adoption across corporate America? Yes, and we believe, they pull from a variety of resources, but the Federal Reserve, in the FRED database, started pulling in Ramp data directly because it was this more real- time indicator of what's really happening in business spend.

[12:35](https://realalpha.app/v/cgXAk8pZ1uA/?t=755) You see different types of spend in different industries. You see very heavy adoption in more tech- forward. So a tech business… Makes sense. … exactly. Financial services businesses are very heavy, but even businesses you wouldn't typically expect. Healthcare, restaurants and food service, manufacturing, can be anywhere from 25% to call it 40% type of adoption. So this is something that's happening and it continues to grow.

[13:00](https://realalpha.app/v/cgXAk8pZ1uA/?t=780) But in terms of corporate AI adoption, right, where are you seeing it accelerate the most? Today, estimates are that there’s about $ 160 to $ 180 billion roughly in spend on inference. That’s just really on the models themselves. If you think about that, about $ 8 to $ 10 trillion a year is spent on white- collar labor in the US. And so, this is almost saying that the spend on inference is already about 2% of that, already.

[13:33](https://realalpha.app/v/cgXAk8pZ1uA/?t=813) And so it’s quite large and growing quite quickly. Some businesses are spending even more on inference than they are on their team. But when you look at the median company in our dataset, in, I would say most, I think about 55% of businesses, do spend on AI already. The median dollar spent per employee is about $ 12 per employee per month. Whereas in that top 1% it’s almost $ 10, 000. And so, you really kind of see there’s some people that are all the way in, and others which are just dabbling.

[14:05](https://realalpha.app/v/cgXAk8pZ1uA/?t=845) Do you see this all leading towards a productivity gain? The way I think about it is the future is here but it’s not evenly distributed. There are some businesses that, you know, I’ll take Ramp as an example. We are growing 25% faster this year than we were last year at, you know, over $ 2 billion a year in revenue and that’s happened in part because we’ve seen AI has made our sales team more productive, we’ve seen it make our engineering team more productive, our product team more productive.

[14:37](https://realalpha.app/v/cgXAk8pZ1uA/?t=877) And we’re simply, I think it is allowing heavyweight companies to start moving like lightweights again. Your data also challenges the idea that AI is eliminating entry- level work. I thought this was really interesting. Yes. Tell me a little bit more. At the start of the year and towards the middle, there was a lot of fear around this. And so we got curious to ask. And so in the Ramp dataset, we could see who was spending.

[14:59](https://realalpha.app/v/cgXAk8pZ1uA/?t=899) And we partnered with a company called Revelio Labs that looks at jobs data, pairs it with LinkedIn data, a variety of other sources. And it turned out that if you get to high- intensity usage, which is not that high, turns out $ 30 per employee per month. That's like a license or two. You suddenly start hiring more and that these firms, despite growing at these same rates, were hiring 12% more people than ones who did not or would adopt it later.

[15:28](https://realalpha.app/v/cgXAk8pZ1uA/?t=928) And so, it was very clear and it was the first quantitative finding showing very clearly that spending on AI actually is leading to more job growth. So, so not the conventional wisdom… Yes. … but so interesting to hear and really does jive with what we're hearing at our companies as well. For sure. Let's talk about token spend. Yeah.