A recent study offers a counter-narrative to the widespread anxiety that artificial intelligence will decimate the job market. Rather than triggering mass layoffs, companies that have embraced AI most aggressively are actually expanding their workforces — including hiring new graduates and other entry-level talent.
The research, conducted by financial operations platform Ramp and workforce data provider Revelio Labs, analyzed records from over 21,000 U.S. firms. It tracked AI-related spending — including coding agents, large language models, GPU cloud services, API tokens, model serving, and inference — alongside employment data. The key finding: companies that adopted AI saw total headcount grow by 10.2% in the two years following initial deployment.
This growth, however, is not uniform. Nearly all of the hiring increase is concentrated among what the report calls “high-intensity adopters” — organizations that make substantial, long-term investments in AI. These firms spend an average of $33.67 per employee per month on AI services, compared to just $2.78 among low-intensity adopters. They are not simply offering chatbot subscriptions or running short-term pilots; they embed AI into core operations.
Ara Kharazian, lead economist at Ramp, noted that the current information environment is confusing for job seekers. “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,” he said. The study aims to reconcile these contradictions. The data suggests that joining a company heavily invested in AI is actually safer — those firms are growing faster and hiring more.
One of the most striking findings concerns entry-level roles. Contrary to predictions that AI would eliminate the bottom rungs of the career ladder, high-intensity adopters increased entry-level headcount by 12%. The report posits that companies are actively seeking recent graduates who are already fluent in using AI tools. Young workers who can demonstrate proficiency with generative AI, coding assistants, and other platforms may have an edge in the job market.
This perspective challenges earlier warnings from some tech leaders. In 2025, Anthropic CEO Dario Amodei suggested that half of entry-level white-collar jobs could disappear, though he later softened his remarks. Consultancy Forrester projects that AI will replace about 6% of U.S. jobs by 2030, or roughly 10.4 million positions. The Boston Consulting Group estimates a slightly higher range of 10% to 15%. Yet the Ramp-Revelio data indicates that AI adoption does not necessarily equate to automation and job loss — at least not in the short term.
The study also highlights a potential downside: small businesses are less likely to be high-intensity adopters. They often lack venture capital backing, specialized engineering teams, or access to networks where AI adoption is common. This puts them at risk of being outcompeted by AI-savvy newcomers. Kharazian noted that “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.” For small firms, failing to adopt AI effectively could mean losing ground to larger, more nimble competitors.
The research does not yet explain exactly which practices drive the hiring growth. Potential factors include product acceleration, sales productivity gains, and faster internal analysis — all of which can create new roles even as some tasks are automated. Kharazian plans to dig deeper into the types of candidates being hired, the specific roles that expand, and whether these patterns hold true outside white-collar work.
This study adds to a growing body of evidence that AI’s impact on employment is more nuanced than simple replacement. While some tasks will certainly be automated, companies that integrate AI effectively often need more human workers to manage, train, and improve the technology — as well as to handle the increased business that AI-enabled efficiency brings.
For job seekers, the message is clear: developing AI skills is not just about avoiding obsolescence — it may be a ticket to a growing company. Entry-level candidates who can demonstrate AI proficiency are particularly well-positioned. As Kharazian put it, “Young people, especially, are very well positioned to show that they can introduce these new technologies and apply them effectively to the workplace.”
The Ramp-Revelio report is one of the first to link actual corporate spending on AI to hiring outcomes across a large sample of firms. It provides a data-driven counterpoint to the fear that AI will inevitably shrink the job market. Instead, it suggests that the most AI-forward companies are also the most talent-hungry. The key for workers is to position themselves as enablers of that AI transition, not as victims of it.
Additional context: The findings come at a time when global investment in AI continues to surge. According to market research, corporate spending on AI-related infrastructure and services exceeded $200 billion in 2025, with projections for double-digit growth through 2030. This capital flow is creating entire new categories of jobs — AI prompt engineers, model trainers, data curators, and ethics specialists — that did not exist five years ago.
Educational institutions are also adapting. Many universities now require students to complete coursework in AI literacy, and bootcamps focused on generative AI have proliferated. This alignment between education and industry needs is likely contributing to the hiring uptick for entry-level positions. Companies see recent graduates as a pipeline for fresh perspectives on how to leverage AI tools in creative ways.
Meanwhile, the gap between high- and low-intensity adopters raises policy questions. If smaller businesses are left behind, it could exacerbate economic inequality. Government and industry initiatives to provide AI training and infrastructure support for SMEs may become increasingly important. Some states have already launched programs to subsidize AI adoption for local small businesses, though the effectiveness of such initiatives remains to be seen.
The report also underscores the importance of measurement. By linking actual expenditure data to workforce records, Ramp and Revelio offer a more granular look at the AI-employment relationship than many previous studies. Earlier research often relied on surveys or broad economic models. This empirical approach allows for more confidence in the finding that AI adoption does not automatically reduce headcount — at least in the early years.
Further investigation will be needed to see if these trends persist as AI technology matures. If AI becomes capable of automating higher-level cognitive tasks, the dynamics could shift. For now, however, the data provides a nuanced picture: AI is reshaping work, but it is also creating new opportunities — especially for those who are ready to work alongside it.
Source: ZDNET News