The anxiety surrounding artificial intelligence and job displacement has been a dominant theme in economic discourse, with many workers fearing that automation will render their skills obsolete. However, a recent study offers a more nuanced perspective: companies that genuinely invest in AI are actually hiring more people, including entry-level workers.

The paper, released at the end of June by financial operations platform Ramp and workforce data firm Revelio Labs, analyzed records from over 21,000 U.S. firms. By linking Ramp card and bill pay data with Revelio workforce records, researchers tracked how much companies spent on AI services—such as coding agents, large language models, GPU cloud, API tokens, model serving, and inference—per employee per month over the first three months after adoption.

High-Intensity Adopters Drive Growth

The key finding: companies that embraced AI grew headcount by 10.2% in the two years following adoption. But this growth is not uniform. Nearly all of it comes from what the report calls “high-intensity adopters”—companies that make long-term, substantial investments in AI rather than merely experimenting with chatbots or short-term pilots.

These high-intensity adopters spend an average of $33.67 per person monthly on AI, compared to just $2.78 among low-intensity adopters. They are typically VC-backed, engineering-focused, and deeply integrated into networks where AI adoption is common. For job seekers, joining a company that heavily uses AI might seem risky, but the data suggests it is actually a safer bet: such companies tend to grow faster and hire more.

Ara Kharazian, lead economist at Ramp, noted the paradox in public perception. “If you’re a consumer of information today, you’re getting a lot of mixed messages. 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 cut through the noise by providing empirical evidence.

Entry-Level Jobs Not Disappearing

One of the most striking findings concerns entry-level positions. Despite widespread predictions that AI would eliminate junior roles—especially in white-collar fields—high-intensity adopters actually grew entry-level headcount by 12%. This suggests that companies are actively seeking recent graduates who can apply 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 explained. The implication is that familiarity with AI is becoming a valuable asset for entry-level candidates, not a threat to their career prospects.

This counters earlier warnings from figures like Anthropic CEO Dario Amodei, who in 2025 predicted that half of entry-level white-collar jobs could disappear—though he later moderated his stance. Other consultancies offer varying projections: Forrester estimates AI will replace about 6% of U.S. jobs by 2030 (approximately 10.4 million), while Boston Consulting Group puts the figure at 10–15%. Yet the Ramp-Revelio study indicates that for high-intensity AI adopters, the net effect so far is positive for total employment.

Small Businesses Lag Behind

The study also highlights a growing divide between large, well-funded firms and smaller businesses. Smaller companies are less likely to be high-intensity adopters, often lacking VC backing, engineering expertise, or networks that facilitate AI integration. 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 is that smaller businesses could be outcompeted or even unseated by new entrants that harness AI effectively.

This has broader implications for economic inequality and small business survival. As large firms accelerate their AI investments, the productivity gap may widen, potentially concentrating market power further. Policymakers and business support organizations may need to consider programs that help smaller enterprises adopt AI strategically.

Understanding the Mechanisms

While the data shows a clear correlation between high-intensity AI adoption and job growth, the report acknowledges that it does not reveal the exact mechanisms driving this growth. Possible explanations include product acceleration, sales productivity improvements, and faster internal analysis. These productivity gains may allow companies to expand operations and hire more staff rather than replacing existing workers.

The study also leaves room for further investigation. Kharazian expressed interest in examining the types of candidates being hired—for example, whether they are predominantly in technical roles or also in areas like marketing, finance, and customer service. Additionally, the analysis currently focuses on white-collar work; it remains to be seen whether similar patterns hold for blue-collar or service jobs.

Another open question is how sustainable this growth is over the long term. The two-year post-adoption window may capture initial expansion, but the effects could change as AI matures and becomes more embedded. Future studies will need to track longer-term trends.

Implications for Job Seekers

For individuals navigating the current job market, the study offers actionable insights. First, learning to use AI tools is not just about staying relevant—it can be a differentiator. Second, targeting companies that are deeply invested in AI may be a better career strategy than avoiding them, despite headlines about layoffs.

The report also suggests that the narrative of AI destroying jobs is overly simplistic. In practice, AI adoption often complements human labor, especially when firms use it to enhance productivity and expand their business. The key is how AI is implemented: superficial usage (like giving everyone a chatbot subscription) has little effect, while deep integration drives hiring.

As the economy continues to digest AI, studies like this provide a more grounded understanding of its impact. Rather than a binary future of job loss or job growth, the reality is likely to be complex and varied across industries, company sizes, and job types. The companies leading the charge in AI are not slashing headcount; they are building their workforces—and they want younger, tech-savvy talent to help them do it.

Source: ZDNET News