Companies that spend heavily on AI are hiring faster, not slower — including in the entry-level roles widely assumed to be the first casualties. A new report from Ramp and Revelio Labs, covering enterprise AI spend and workforce records across nearly 22,000 companies, finds that firms it labels high-intensity adopters grew headcount 10.2% after rolling out AI, and entry-level headcount at tech-forward firms in the sample rose 12%. That cuts directly against the prevailing narrative built on close to 90,000 AI-tied job cuts announced through May 2026.
The report defines high-intensity adopters as firms spending an average of $30 per employee per month on AI in their first three months of deployment. Headcount growth at those firms showed up across engineering, sales, administration, customer service, finance, marketing, and scientist roles — not just in the technical functions closest to the tools. The strongest gains were concentrated in the information sector: software, internet, media, and adjacent tech firms.
That number sits awkwardly next to the broader labor picture. Goldman Sachs has estimated AI has erased roughly 16,000 net jobs per month over the past year, with Gen Z and entry-level workers absorbing most of the damage. Separate projections cited in the report put up to 15% of U.S. jobs at risk of AI elimination over the next five years. Two data sets, two stories.
Key facts
- 01Companies announced close to 90,000 AI-tied job cuts through May 2026, with up to 15% of U.S. jobs projected to be eliminated by AI over the next five years.
- 02High-intensity AI adopters — firms spending $30 per employee per month in their first three months — grew headcount 10.2%, per Ramp and Revelio Labs.
- 03Entry-level headcount rose 12% at tech-forward firms in the dataset, even as Goldman Sachs counted 16,000 net jobs erased by AI per month over the past year.
- 04The Ramp and Revelio Labs dataset covers nearly 22,000 companies, skewed toward knowledge-work and VC-backed firms already positioned to grow.
The Ramp and Revelio Labs authors are explicit about the limits of their finding.
The skew matters. The companies showing the strongest hiring are tech-forward, often VC-backed, and were likely growing anyway — making it genuinely hard to isolate AI's contribution from the broader expansion that brought it in the door. Firms that only bought subscriptions or ran pilots without sustained investment showed no headcount gains at all.
What the data does suggest is that AI is functioning less as straight labor substitution and more as a firm-expansion lever at companies positioned to use it that way. The report frames the mechanism specifically for software and technology firms: AI cuts the cost of writing code, debugging, building internal tools, producing technical documentation, and supporting product development.
“Lower production costs in these workflows can raise the return to expanding the whole firm, not just the engineering team.”— Ramp and Revelio Labs, report authors
In that framing, cheaper engineering output raises the return on hiring everywhere else in the business — sales to sell the new capacity, marketing to position it, finance and ops to scale it. The 12% jump in entry-level headcount at tech-forward firms reads less like AI hiring junior engineers and more like AI making the rest of the company worth expanding. Whether that pattern holds in non-tech sectors with thinner margins is the unanswered question.
The harder finding is the divergence. Firms with capital, technical staff, founder networks, and management bandwidth turn AI adoption into measurable business gains. Firms without those resources sit on subscriptions and pilots and show no growth. The authors warn that firms without those channels may fall behind — a polite way of describing a widening structural gap between AI haves and have-nots that gets harder to close the longer it runs.
That divergence is also why the macro layoff number and the micro hiring number can both be true. The 90,000 announced cuts are concentrated at large incumbents — Ford recently rehired veteran engineers after AI fell short on vehicle programs, and Infosys's former chief just launched a startup explicitly targeting the IT services model AI is hollowing out. Meanwhile, the firms growing headcount are the well-resourced adopters running AI as a force multiplier rather than a replacement. Different companies, different playbooks, same technology.
For the AI jobs debate, the Ramp and Revelio Labs report doesn't resolve anything — it sharpens the question. The honest read is that AI is widening the gap between firms that can operationalize it and firms that can only buy it. The headline jobs number depends entirely on which side of that gap you're measuring, and right now both sides are real.
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