"Companies spending heavily on AI are growing headcount faster, even in the entry-level roles that many fear are doomed," [1]writes TechCrunch . That's the conclusion of new [2]report tracking AI spending from Ramp's corporate card/bill pay data as well as Revelio Labs' workforce records from 21,599 U.S. firms:

> According to the report, "high-intensity adopters" — firms that spend on average $30 per employee per month on AI in the first three months — saw headcount increase 10.2%. Headcount also rose across functions, including [3]engineering , sales, administration, customer service, finance, marketing, and scientist roles. The strongest job growth among high-intensity adopters was in the information sector, which includes software, internet, media, and tech-adjacent firms.

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> Despite these positive signals, the data isn't as rosy as it seems. It skews heavily toward tech-forward, knowledge-work firms — ones that might have VC-backing and are growing fast anyway, making it difficult to say whether AI is contributing to the hiring or just showing up at companies that are expanding anyway. "This paper does not show that AI universally creates jobs," the paper's authors admit, "but it does counter claims that AI will lead to broad job losses."

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> It also counters claims that AI is killing all junior jobs. [4]Recent research from Goldman Sachs found that AI has already erased about 16,000 net jobs per month over the past year, with Gen Z and entry-level workers taking the brunt of the burden. But in tech-forward firms, the report finds that entry-level headcount actually rose by 12%... "For software and technology firms, AI can make core output cheaper or faster to produce: writing code, debugging, building internal tools, producing technical documentation, and supporting product development," the report reads. "Lower production costs in these workflows can raise the return to expanding the whole firm, not just the engineering team."

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> But companies that buy subscriptions and run pilots, yet did not go on to make sustained investments, don't tend to see any gains in headcount, per the report. That sets up the potential for a [5]widening gap between firms that have the resources — like capital, technical staff, founder networks, and management bandwidth — to turn AI adoption into actual business gains and those that are stuck experimenting with subscriptions. In other words, this report suggests that firms that already have the resources are the ones that will see the largest gains.

CNBC argues another AI "narrative" was challenged this week: [6]that open source can't make money . "The assumption was that giving your model away for free meant no business. That's breaking too, as open-model companies start posting real revenue and enterprises move from renting AI to running their own."



[1] https://techcrunch.com/2026/06/29/the-ai-jobs-debate-just-got-messier/

[2] https://www.prnewswire.com/news-releases/ramp-economics-lab-finds-companies-that-invest-heavily-in-ai-hire-more-302814151.html

[3] https://techcrunch.com/2026/06/24/ai-was-supposed-to-kill-engineering-jobs-but-new-data-suggests-theyre-the-most-resilient/

[4] https://finance.yahoo.com/economy/articles/ai-cutting-16-000-u-171008831.html

[5] https://techcrunch.com/2026/03/25/the-ai-skills-gap-is-here-says-ai-company-and-power-users-are-pulling-ahead/

[6] https://www.cnbc.com/video/2026/07/02/ais-three-big-narrative-violations.html