the ai jobs debate just got messier

At a glance:

• Companies announced nearly 90,000 AI-related job cuts through May 2026, with up to 15% of U.S. jobs projected to be eliminated by AI over five years
• High-intensity AI adopters spending $30/employee/month saw 10.2% headcount growth, including 12% entry-level increases in tech firms
• AI job gains are concentrated in resource-rich firms, creating a widening gap between companies that can sustain AI investment and those stuck in pilot phases

The numbers behind the AI job anxiety

The conversation around AI and employment has taken on renewed urgency as layoff announcements accelerate. Through May 2026, companies have announced close to 90,000 job cuts tied to artificial intelligence, while broader projections suggest up to 15% of U.S. jobs could be eliminated by AI over the next five years. These figures have amplified concerns among graduating students and early-career professionals who wonder whether traditional hiring pipelines will remain viable in an AI-saturated economy.

While tech industry leaders continue to promise that AI will ultimately create new jobs to offset displacement, recent research complicates that optimistic narrative. A report from Ramp and Revelio Labs, which tracks enterprise AI spend and workforce records from nearly 22,000 companies, provides some counterpoint data that challenges the prevailing gloom.

AI adopters are hiring faster

According to the report, companies spending heavily on AI are actually growing headcount faster than their peers, even in entry-level roles that many fear are most at risk. The analysis identifies "high-intensity adopters" — firms that spend an average of $30 per employee per month on AI in their first three months — as seeing headcount increase by 10.2%. This growth spans multiple functions, including engineering, sales, administration, customer service, finance, marketing, and scientist roles.

The strongest job growth among these high-intensity adopters was observed in the information sector, which encompasses software, internet, media, and tech-adjacent firms. This concentration suggests that AI's impact on employment may vary significantly depending on industry composition and company characteristics.

The data tells a nuanced story

Despite these positive signals, the researchers acknowledge that the data doesn't definitively prove AI universally creates jobs. The report skews heavily toward tech-forward, knowledge-work firms — many of which have venture capital backing and are growing rapidly anyway. This makes it difficult to isolate whether AI adoption is driving hiring or if AI simply appears at companies that are expanding regardless.

"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."

The findings also directly counter claims that AI is eliminating all junior positions. While Goldman Sachs research found that AI has erased approximately 16,000 net jobs per month over the past year — with Gen Z and entry-level workers bearing the brunt — the Ramp and Revelio report found that entry-level headcount in tech-forward firms actually rose by 12%.

How AI drives expansion, not just replacement

The report suggests that for software and technology firms, AI functions as a tool for firm expansion rather than pure labor substitution. "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."

This dynamic helps explain why high-intensity AI adopters are seeing broader hiring increases. When AI reduces the cost of core outputs like code generation and debugging, it can make the entire business more efficient and profitable, creating incentives to expand across departments rather than simply replacing workers with automation.

However, the report notes an important caveat: companies that purchase AI subscriptions and run pilot programs but fail to make sustained investments typically do not see corresponding gains in headcount. This distinction reveals a critical threshold in AI adoption — the difference between experimentation and strategic integration.

A growing divide between AI haves and have-nots

This finding points to a potential widening gap between firms with the resources to transform AI adoption into measurable business gains and those still experimenting with limited subscriptions. The report identifies several key resources that enable successful AI integration: capital, technical staff, founder networks, and management bandwidth.

Firms lacking these advantages may struggle to move beyond proof-of-concept projects. The paper's authors speculate that this divide may continue to grow, warning: "Firms without those channels may fall behind."

This dynamic suggests that AI's impact on employment may ultimately reinforce existing inequalities between well-resourced companies and smaller or less technically sophisticated organizations. The benefits of AI-driven efficiency gains appear concentrated among firms already positioned for rapid growth.

What this means for the future of work

The AI jobs debate remains complex, with different studies pointing in different directions. The Ramp and Revelio findings challenge blanket predictions about job destruction while highlighting the uneven distribution of AI's benefits. Companies that can strategically integrate AI tools into their core workflows — particularly in software and technology sectors — appear positioned to expand their workforces.

Meanwhile, the gap between AI-capable and AI-struggling firms may have lasting implications for labor markets. As larger, resource-rich companies consolidate their AI advantages, smaller competitors may find themselves increasingly unable to compete, potentially leading to further consolidation and job market stratification.

For policymakers and workforce planners, these findings suggest that AI's employment impact will likely vary dramatically by industry, company size, and strategic approach to adoption. The conversation around AI and jobs is far from settled, but the data increasingly points toward a future where AI's benefits are unevenly distributed rather than uniformly destructive or beneficial.

The fundamental question moving forward is whether the current wave of AI investment will create sustainable competitive advantages for early adopters or whether the technology's benefits will eventually diffuse more broadly across the economy.