'AI-pilled' firms spend $7,500 per employee each month on AI

Overview

The heaviest corporate AI users, the top 1% of firms Ramp calls "AI-pilled," now spend roughly $7,500 per employee each month on AI tools, while the median business spends only $11.38. That is a gap of about 680 times between the most aggressive adopters and the middle of the pack. The Ramp AI Index draws this picture from anonymized spending data across more than 70,000 U.S. businesses, showing how concentrated heavy AI investment remains.

Key Takeaways

The top 1% of firms by AI adoption spend about $7,500 per employee each month, compared with $611 for the top 10% and $11.38 for the median company.
The gap between the heaviest spenders and the typical firm is roughly 680 times, one of the widest adoption divides measured to date.
Among the top 1%, per-employee AI spend grew 14.1% in a single month, showing the most committed firms keep widening their lead.
Even the biggest AI budgets stay below human labor costs: the top spend is under half the roughly $16,000 a month an average software engineer earns.
Heavy adopters avoid vendor lock-in, switching between frontier models and cheaper open-source options such as DeepSeek to control costs.
The data comes from the Ramp AI Index, which tracks anonymized card and bill-pay activity across more than 70,000 U.S. businesses.

Stats & Key Facts

#$7,500 per employee per month: AI spend among the top 1% of firms, the "AI-pilled" group (Ramp lists about $7,449).
#$611 per employee per month: AI spend among the top 10% of firms.
#$11.38 per employee per month: AI spend at the median company, near the cost of one enterprise subscription seat.
#14.1%: month-over-month growth in per-employee AI spend among the top 1%.
#680x: the spending gap between the top 1% and the median firm.
#70,000+: U.S. businesses tracked in the Ramp AI Index dataset.

What "AI-pilled" Means and How Much These Firms Spend

Ramp uses the label for the small group of companies pouring the most money into AI per worker.

Ramp applies the term "AI-pilled" to the top 1% of firms ranked by AI adoption. These companies spend about $7,500 per employee each month on AI tools and services, a figure that dwarfs nearly every other business in the dataset.

The label captures more than a budget line. It describes firms that have reorganized work around AI to the point where their per-worker spending looks closer to a salary line than a software subscription. Ramp's report puts the exact figure near $7,449 per employee.

The 680x Gap Between Top Spenders and the Median Company

The distance between the leaders and the typical firm is wide enough to reshape how adoption gets measured.

›Top 1% of firms: about $7,500 per employee each month.
›Top 10% of firms: about $611 per employee each month.
›Median company: $11.38 per employee each month, near the price of one enterprise seat.
›The result is a roughly 680-fold gap between the most aggressive adopters and the middle.

The median figure of $11.38 lines up with the cost of a single enterprise ChatGPT or Claude subscription seat. Most companies, in other words, are paying for little more than basic access while a thin slice of firms spend hundreds of times more.

Spending Is Still Climbing Fast at the High End

The heaviest users are not slowing down.

Among the top 1%, per-employee AI spend grew 14.1% in the most recent month alone. That pace suggests the leaders keep pulling away from everyone else rather than settling into a steady budget.

The growth comes despite rising token costs and pressure to control expenses. Instead of cutting back, these firms are reshaping how they buy AI to keep spending more while managing the bill.

AI Budgets Still Trail Human Salaries, For Now

Even the biggest AI spenders pay less per worker than they pay people.

The average software engineer earns roughly $16,000 a month, or about $192,000 a year. Even the top AI spenders pay under half of that on AI per worker, so human salaries remain the larger cost.

Several executives have argued that companies should spend as much on AI as they pay an engineer. The Ramp data shows no firm is doing that yet, though the gap is narrowing as the heaviest adopters keep raising their budgets.

Why Heavy Adopters Switch Between Models and Vendors

The top spenders shop around rather than commit to one provider.

›They bounce between multiple frontier models and platforms to find cheaper options.
›They mix in open-source alternatives such as DeepSeek to trim costs.
›Vendor adoption splits closely, with Anthropic near 41% and OpenAI near 39.5%.
›The strategy points to margin discipline, not lower total spending.

This mix-and-match approach lets heavy users push more work through AI while holding down the cost of each task. Rather than locking into a single vendor, they treat models as interchangeable tools and route work to whichever option is cheapest for the job.

How the Ramp AI Index Builds These Numbers

The figures come from real corporate spending, not a survey.

The Ramp AI Index tracks aggregated, anonymized card and bill-pay data across more than 70,000 U.S. businesses. Because it watches actual transactions, it captures what firms pay rather than what they say they plan to spend.

The index breaks spending into categories such as subscriptions, coding agents, and token or API usage, and it allows filtering by state, sector, company size, and funding stage. That structure gives one of the clearest views yet of how unevenly AI investment is spread across the economy.

Frequently Asked Questions

What does "AI-pilled" mean in this report?

Ramp uses "AI-pilled" for the top 1% of companies ranked by AI adoption. These firms spend about $7,500 per employee each month on AI, far more than nearly every other business.

How big is the gap between top spenders and typical companies?

It is roughly 680 times. The top 1% spend about $7,500 per employee monthly while the median firm spends only $11.38, close to the cost of one enterprise subscription seat.

Is AI spending now higher than employee salaries?

No. Even the top AI spenders pay under half the roughly $16,000 a month an average software engineer earns. Human salaries remain the larger cost, though the gap is narrowing.

Where do these figures come from?

They come from the Ramp AI Index, which tracks anonymized card and bill-pay spending across more than 70,000 U.S. businesses, measuring actual transactions rather than survey responses.

Why do heavy adopters switch between AI models?

The top spenders move between frontier models and cheaper open-source options such as DeepSeek to lower the cost of each task. It reflects cost discipline rather than reduced total spending.

The Ramp AI Index shows AI investment remains highly concentrated, with a small group of firms spending hundreds of times more per worker than everyone else. For now those budgets stay below human salaries, but the fast growth at the top suggests the gap will keep closing.