Ramp Economics Lab Finds Companies That Invest Heavily in AI Hire More

First of its kind study links firm-level AI spending to workforce data

NEW YORK, June 30, 2026 /PRNewswire/ -- Ramp, the leading financial operations platform, today released new research from Ramp Economics Lab showing that companies making significant investments in AI grew their workforces faster than comparable firms. The findings counter predictions that AI adoption will lead to broad job loss.

The paper, "A New Look at AI's Impact on Jobs: Firm-Level AI Spending and Workforce Adjustment," is the first study to link observed, firm-level AI spending to workforce data at scale, tracking AI spending from Ramp's corporate card and bill pay data to Revelio Labs' workforce records across 21,599 U.S. firms. The research classifies firms as high- or low-intensity adopters based on AI spending per employee in the first three months after adoption.

Key Takeaways:

• 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.

"The research until now has relied on datasets that are available but not appropriate for these questions, resulting in the general public getting unreliable answers on how AI will actually affect our economy," said Ara Kharazian, Lead Economist at Ramp. "Our research shows that firms that invest more in AI also hire more following adoption, including in entry-level roles. These are early results that we will update over time, but should provide some confidence to the public about the potential gains of this technology."

Small Businesses Impact
A supplementary finding of the research shows small businesses are less likely to adopt AI than larger companies, but when they do adopt, they tend to adopt more intensively. Additionally, marginal impact is higher for small firms, showing AI can unlock capabilities that previously required a dedicated team.

"There are likely many small businesses that would benefit from AI but do not use it today, missing out on meaningful growth," continued Kharazian. "Our economy pays those costs when firms remain on the slower growth path. The challenge now is helping more businesses connect to the networks, tools, and long-term investment needed to use AI effectively."

To turn these findings into action, Ramp is partnering with Meta Small Business to enable small businesses to share in the growth and benefits of AI through strategic investment. Together, the two companies will bridge the gap by raising awareness of the challenges and interventions most needed to encourage the millions of businesses on Meta's platforms to use AI to accelerate their growth.

The paper was co-authored by Lisa Simon, Chief Economist at Revelio Labs and Ryan Stevens, Director of Applied Science at Ramp. The full paper is available at https://ramp.com/data/ai-jobs-impact.

About Ramp
Ramp is how companies save time and money on every dollar they spend. It's the smart financial infrastructure behind every card swipe, invoice, and reimbursement – streamlining approvals, processing payments, and closing the books automatically. More than 70,000 organizations, from family farms and space startups to the Fortune 100, have saved over $12 billion and 27 million hours with Ramp. For the median customer, that translates to 5% savings on expenses and 16% revenue growth in their first year. Founded in 2019, Ramp powers over $200 billion in purchases annually. Learn more at www.ramp.com.

* Ramp does not include bank transfers or non-monetized payments when calculating Total Purchase Volume.

Contact
[email protected]

SOURCE Ramp