AI Hiring Is Up 28%-35% Even After Tech Layoffs-Why That Matters Now

Tech layoffs have coincided with a hiring reshuffle, not a sector-wide collapse

The headlines focus on cuts, but the labor data points to a more nuanced shift. Companies are still letting people go, yet they are also still building teams-just in different areas. Tech employers added 69,000 tech jobs in May, and unemployment among technology workers fell to 3.1%. At the same time, openings are rising fastest in roles that tend to ship work directly: computer programmers up 35%, software developers up 28%, and database administrators up 27% from a year earlier.

The demand is concentrated, not universal

This is not evidence that every tech company is hiring aggressively. It is evidence that demand is being reallocated. Even with layoff headlines, employers remain interested in core operational functions, including cloud infrastructure and IT services, as well as broader AI, data, and cybersecurity capabilities.

That matters because it argues against a simple "tech is rolling over" narrative. A collapsing sector usually sees broad hiring freeze across core roles. What we are seeing instead looks more like a market pruning weak fits while paying up for execution.

AI hiring is real, but it is also highly selective

Job openings and wage premiums point to real demand

If you want to test whether AI demand is genuine, look at postings and pay rather than buzzword usage. The U.S. posted 49,200 AI/ML positions, up 163% from 2024 to 2025, and AI Engineer postings rose 143% year over year. Roles requiring AI skills also carry a 56% wage premium over comparable non-AI jobs, up from 25% a year earlier.

That combination matters. Hype can create noisy headlines; sustained hiring and rising pay usually mean employers have real vacancies they cannot easily fill.

The posting data underestimates how much AI skill matters

There is an obvious mismatch between how much AI appears in job listings and how much workers are studying it. Only 4% of job listings mention AI, yet AI accounts for 67.5% of employee upskilling efforts. In technology, 95% of workers' upskilling is AI-related, while just 17.5% of the fastest-growing posted skills are AI-related.

A likely explanation is that many AI-enabled jobs are still attached to existing titles in software, data, security, and infrastructure. Employers may not label a posting "AI" even if they want someone who can operationalize those systems. Workers, meanwhile, appear to be preparing for a labor market where AI fluency matters more than current job-posting language suggests.

The broader market effect reaches beyond software

This is not only a white-collar coding story. Data-center buildouts tied to AI are creating specialized talent shortages, with demand extending to electricians, technicians, and security specialists. That shows the buildout is not confined to algorithm research or software tooling; it also requires physical infrastructure and hands-on technical roles.

For employers, that broadens the bottleneck. For investors, it narrows the opportunity set. The beneficiaries are not just AI platform leaders, but also companies tied to cloud infrastructure, IT services, data-center construction and operations, staffing, and cybersecurity.

AI is reshaping more jobs than it is replacing

The bigger mistake is assuming AI mainly cuts headcount. The stronger reading is that it changes most jobs. Over the next two to three years, 50% to 55% of jobs in the US will be reshaped, with many people staying in the same or a similar role while facing higher expectations for output and judgment.

That helps explain why the pay premium for AI skills may persist. Companies most exposed to AI are seeing productivity growth 40% higher than less-exposed peers. At the same time, skills are evolving 66% faster in AI-exposed roles than in less-exposed ones. The durable advantage, then, belongs to people who can keep pace with changing tools and still turn them into usable outcomes.

What would confirm-or weaken-this trend

One month does not settle the story. The latest data still supports the basic picture: employers added 69,000 tech jobs in May, and tech unemployment fell to 3.1%. But the next confirmation signal is whether hiring stays selective rather than slipping back into broad, undifferentiated head-count growth.

Signals to watch

• Software, data, cybersecurity, and cloud services: Do openings remain firm in roles that directly support delivery and operations?
• AI and ML postings: Does demand stay concentrated in roles that build and deploy systems, rather than fading into generic AI language?
• Physical buildout: Does demand continue to spill into electricians, technicians, and security specialists and related trade roles?

What would weaken the thesis

• The 69,000 tech jobs added in May proves to be a one-month rebound rather than the start of a steadier hiring pattern.
• AI/ML postings cool materially, even if general tech postings stay flat.
• Wage pressure eases enough to suggest the current talent squeeze is fading.
• Data-center and infrastructure demand stays isolated instead of broadening into wider technical hiring.

The core takeaway is simple: layoffs have not stopped tech hiring. They have changed what employers are willing to pay for.