A new study is pushing back on some of the most anxiety-inducing narratives around AI-driven job loss. Contrary to widespread fears that artificial intelligence will replace workers en masse, companies that are embracing AI most aggressively are actually hiring more people — including entry-level employees.

The report, published at the end of June by financial operations platform Ramp and workforce data company Revelio Labs, analyzed records from more than 21,000 U.S. firms. It linked Ramp card and bill pay data to Revelio workforce records to track how much companies spent on AI services — such as coding agents, large language models, GPU cloud computing, API tokens, model serving, and inference — per employee per month in the first three months after adoption.

The headline finding: companies that embraced AI grew headcount by 10.2% in the two years following adoption. This growth was not evenly distributed. Nearly all of the hiring surge came from what the paper calls “high-intensity adopters” — firms that make long-term, significant investments in AI rather than just offering chatbot subscriptions or running short pilots. These companies spend an average of $33.67 per person per month on AI, compared to just $2.78 among low-intensity adopters.

“If you're a consumer of information today, you're getting a lot of mixed messages,” said Ara Kharazian, Ramp's lead economist, in an interview. “[If] you are on the job market, you are simultaneously hearing that you must learn AI, or you'll get left behind. And yet, AI is also going to be the technology that will likely lead to your layoff.”

The report aims to shed light on these contradictions and guide job seekers navigating a rocky employment landscape. It suggests that joining a company heavily using AI is actually the safer bet. “That's the one that's going to grow faster,” Kharazian said.

Entry-level jobs are growing, not shrinking

One of the most striking findings concerns entry-level positions. Despite warnings from tech leaders — including Anthropic CEO Dario Amodei, who in 2025 suggested half of entry-level white-collar jobs could disappear — the data shows the opposite trend. Among high-intensity AI adopters, entry-level headcount grew by 12%.

The reason may be that companies are actively seeking recent graduates who already know how to use AI tools effectively. “Young people, especially, are very well positioned to show that they can introduce these new technologies and apply them effectively to the workplace,” Kharazian noted. This suggests that AI fluency is becoming a valuable credential, much like computer literacy became essential in the 1990s.

The growth in entry-level hiring also challenges the broader narrative of a “hollowing out” of the labor market, where mid-level jobs disappear and only senior roles remain. Instead, the report indicates that companies investing in AI are building talent pipelines from the ground up, training new workers to operate alongside AI systems.

Small businesses at a crossroads

Another critical insight from the study is that smaller businesses are far less likely to be high-intensity AI adopters. They tend to lack venture capital backing, engineering focus, and the networks that facilitate AI adoption. This puts them at a competitive disadvantage.

“So much of your usage of AI, and how you use it and whether or not you use it well, is also driven by who you know and where you can hire from and the networks you're connected to,” Kharazian said. The risk for smaller firms is getting outcompeted or even unseated by new startups that leverage AI effectively from day one.

This dynamic echoes earlier technology shifts, such as the adoption of cloud computing or e-commerce, where early movers gained lasting advantages. Small businesses that hesitate to invest in AI may find themselves losing market share to more agile competitors. For job seekers, this means that joining a small business without a strong AI focus might carry more risk than joining a larger, AI-heavy firm.

Broader context: AI and the future of work

The study's findings come at a time of intense debate about AI's impact on employment. Layoffs at major tech companies have often been attributed to automation, and surveys show that workers are increasingly anxious about their job security. Yet the data from Ramp and Revelio Labs adds a nuanced perspective.

Other consultancies offer a range of projections. Forrester estimates that AI will replace about 6% of U.S. jobs by 2030 — roughly 10.4 million positions. The Boston Consulting Group puts the figure at 10–15%. But these projections often focus on job displacement without fully accounting for the new roles created by AI adoption. The Ramp report suggests that AI is not simply a job killer; it can be a job creator when implemented strategically.

The mechanisms driving hiring growth in high-intensity adopters likely include product acceleration, sales productivity, and faster internal analysis. However, the study acknowledges that it doesn't pinpoint exactly which practices drive the hiring increases. Future research could explore the types of candidates being hired, the specific roles added, and whether the pattern holds beyond white-collar work.

Kharazian expressed interest in digging deeper into these questions. He wants to understand if the benefits of AI adoption extend to blue-collar or service jobs, and whether the hiring boost is sustained over longer periods. The initial data covers only two years after adoption, so longer-term trends remain unknown.

Key takeaways for job seekers and businesses

For individuals on the job market, the report offers a clear message: AI skills are an asset, not a liability. Entry-level candidates who can demonstrate proficiency with AI tools — whether through coursework, personal projects, or internships — may have an edge. Companies that are investing heavily in AI are not only hiring more but actively seeking young talent.

For businesses, the imperative is equally clear. Delaying AI adoption could mean falling behind in both growth and talent acquisition. The cost of not adopting may be higher than the cost of adopting, especially as competitors leverage AI to improve efficiency and scale.

The study also raises important questions about inequality. If AI adoption is concentrated among well-funded, engineering-intensive firms, workers at smaller or less tech-savvy companies may miss out on the job growth. Policymakers and economic development organizations may need to consider programs that help small businesses access AI tools and training.

Ultimately, the Ramp-Revelio Labs report provides a valuable counterpoint to alarmist headlines. AI is not a uniform force for job destruction; its impact depends heavily on how businesses choose to implement it. The companies that are betting big on AI appear to be betting even bigger on people.

Source: ZDNET News