AI Leaders Boost Headcount by 10%, Junior Hiring Up 12%

New research that appeared on June 29, 2026 complicated one of the main economic debates of the moment. "High-intensity" AI users — companies that actively integrated the technology into their business processes — increased their overall headcount by 10.2%, while the number of positions for junior specialists grew by 12% for them. This directly contradicts the dominant narrative of AI as a "job killer."

What researchers found

The report authors divided companies into groups by the degree of artificial intelligence application — from isolated experiments to deep integration into all key processes. The group with the highest intensity of AI use showed the greatest increase in employment.

• Growth in total number of employees among "high-intensity" AI users — 10.2%
• Growth in the number of entry-level positions in the same group — 12%
• Both figures contradict the persistent forecast of automation displacing people from the labor market

The dynamics among junior specialists are particularly telling. Junior specialists are traditionally called the first victims of automation: their work is routine, well-described — seemingly most vulnerable to algorithm replacement. Nevertheless, the data shows the opposite: in companies using AI most actively, young employees are being hired faster, not slower.

Why has the debate become only more complex?

The report does not settle the debate about AI's impact on employment — rather, it adds a new layer of complexity. The growth in hiring at pioneering AI companies is consistent with two fundamentally different explanations, and the data does not allow us to choose between them.

The optimistic version: AI acts as a growth amplifier. By automating routine operations, companies free up resources and launch new directions that require new hires. The increase in entry-level positions fits into this picture: AI takes on mechanical tasks, leaving junior specialists with work that requires judgment, communication, and unconventional problem-solving — skills that are currently harder to automate.

The skeptical version: "high-intensity" AI users are typically technologically mature companies with strong funding and sustained organic growth. They would have hired aggressively in any case. Their figures are not representative of the labor market as a whole and certainly do not predict the fate of employees in traditional industries, where AI arrives later and in a different context.

Both interpretations are valid. This is what makes the picture "even more confusing."

What this means

The simplified thesis "AI kills jobs" is not supported by data from technology leaders — at least at the current stage. For regulators, this is an argument against hasty restrictions on AI adoption. For employers, it is a signal that fear of workforce reduction during AI transformation currently lacks empirical foundation. For those just entering the labor market, it is moderate but real reason for optimism. The debate continues, and now both sides have significant new arguments.