How US tech job losses coexist with rising IT recruitment

Tech employment fell while recruitment continued

US tech employment can fall even while employers seek people for strategically important work. In September, employment losses coincided with increases in new IT job advertisements and active postings requiring artificial intelligence, or AI, skills. For leaders setting staffing budgets, these measures answer different questions: employment figures track workforce changes, while postings show where employers are still seeking candidates.

September reversed August’s gains in tech employment across industries

The scale of September’s decline depended on which workforce was counted. Technology-sector employment covers positions within technology businesses, while tech employment across all industries also includes IT roles at other employers. CompTIA, the technology consortium, reported that technology-sector employment dropped by 10,350 positions in September after a reduction of 14,700 in August. The sector’s monthly loss narrowed, but employment continued to fall.

Across all industries, tech employment changed direction more sharply. CompTIA’s analysis of US Bureau of Labor Statistics data found a decline of about 6,000 tech jobs in September after an increase of 86,000 in August. The earlier gain had raised hopes that employment was stabilizing, but September’s reversal weakened that reading by erasing part of the increase.

The broader US labor market also added jobs more slowly. The Bureau of Labor Statistics reported 29,000 additional nonfarm jobs in September, below expectations and down from 133,000 in August. CompTIA put tech-worker unemployment at 3.3%, reporting an increase in September that still left it below the national rate of 4.2%. Tech workers retained an unemployment advantage even as employment figures showed renewed weakness.

Employment changes reflect a different stage of workforce decisions from announced job cuts. Challenger, Gray & Christmas counted 10,799 cuts announced by tech companies in September, a 77% increase from 6,103 in August. Those announcements describe planned reductions, whereas federal employment data track changes in workforce size. So the rise in announcements can coexist with CompTIA’s smaller monthly technology-sector employment loss.

Across all sectors, however, announced cuts declined to 43,281 in September from 52,881 in August. Technology employers also had a higher cumulative total: Challenger, Gray & Christmas reported that the sector had cut 165,925 jobs this year, up 54% from the same period in 2025. The fall in overall monthly announcements therefore offered little reason to assume that technology employment had stabilized.

Recruitment growth was concentrated in particular skills

Despite the employment losses, employers continued opening searches for technical staff. Lightcast job-posting data reported by CompTIA showed 272,040 new US IT openings in September, up 16% from September 2025. This year-over-year comparison covers a different period from the August-to-September employment change. Still, it shows that a declining workforce coexisted with substantial recruitment activity.

Recruitment activity records employers looking for candidates, with hiring decisions still ahead. CompTIA interpreted falling employment alongside rising new IT postings as evidence of demand for particular skills. Under that interpretation, the overall decline gives a hiring manager limited guidance about a specific vacancy: what matters is whether available candidates meet the role’s requirements.

Ger Doyle, ManpowerGroup’s regional president in North America, described employers as recruiting cautiously and tying positions to strategic business priorities. ManpowerGroup has a commercial interest in employers’ demand for staffing and recruitment services. “The market is no longer defined simply by how many people employers hire, but by how precisely they hire,” Doyle said. His assessment places each position’s business purpose at the center of the approval decision.

AI skills illustrate this concentration of demand. ManpowerGroup identified them as the skills employers sought most, while CompTIA counted 349,821 active postings requiring AI-related skills in September, up 32,327 from August. Active postings are advertisements still open during the measurement period; new postings count advertisements added during it. The AI count and the new IT openings count therefore cover different groups of searches as well as different comparison periods.

Demand for particular skills also affects workers and hiring managers. Workers whose experience falls outside current priorities may find fewer suitable opportunities, even as advertisements grow overall. Employers, meanwhile, need to define the work a proposed hire will perform before using market-wide employment figures to judge how easy recruitment will be. Selective demand helps explain the recruitment pattern without establishing that a skills shortage caused the employment decline.

Recruitment time affects when capacity becomes available

Once a role is approved, the search can take long enough to affect delivery plans. “The roles that matter most also take the longest to fill,” Doyle said. He put the typical period a job posting stays open at 61 days and the typical time required to fill an engineer role at 77 days. These measure different durations, but both make recruitment time an important part of staffing decisions.

For an engineering leader, that delay separates approval to recruit from the date an employee can contribute. Work that depends on a new hire needs a schedule that allows for the search and its completion. A staffing plan should therefore state the role’s business purpose, record the approval decision, and allow time for recruitment before relying on the additional capacity. Doyle’s figures describe this planning constraint without guaranteeing that any particular advertisement will lead to a hire.

Cost pressures shape employers’ willingness to commit

Recruitment time is one constraint; willingness to fund a position is another. Andy Challenger, chief revenue officer at Challenger, Gray & Christmas, said higher costs and political uncertainty were encouraging employers to wait before hiring. His company provides workforce-transition services, giving it a commercial interest in employers’ responses to layoffs and organizational change. His assessment concerns the conditions influencing commitments, while Doyle’s concerns the priorities used to select roles.

Challenger named several pressures behind that hesitation. “Employers are facing high energy costs, an uncertain war in Iran, a rate hike that could make hiring more expensive, plus the likelihood of surging healthcare costs,” Challenger said. Energy and potential healthcare increases affect operating expenses, while a rate hike could raise hiring costs. Uncertainty around the war in Iran adds geopolitical risk to those financial considerations.

These pressures can affect new hiring decisions even when employers announce fewer cuts overall. Slowing reductions and authorizing additional positions are separate choices, so the decline in all-sector cut announcements does not by itself establish greater willingness to expand payrolls. Challenger’s assessment offers an explanation for caution. It does not establish which pressure, if any, caused September’s tech employment losses.

AI-skill demand and AI-attributed cuts measure different decisions

Alongside those cost pressures, AI appears in the employment data as both a requested skill and an employer-stated reason for cuts. Recruitment postings record the expertise employers seek, while Challenger, Gray & Christmas’s layoff figures record reductions attributed to AI. Both measures can rise because they describe different decisions. An employer seeking AI expertise and an employer citing AI when eliminating positions both contribute to the wider employment picture.

For September, Challenger, Gray & Christmas reported that employers cited AI for 3,961 of the 43,281 announced cuts across all sectors, or about 9% of the total. Because the denominator covers all sectors, the percentage describes the broader US announcement figures. The reported count also records employers’ stated reasons, which differ from a measure of every employment effect associated with AI.

The year-to-date figures show how September’s stated reasons differed from the cumulative pattern. Challenger, Gray & Christmas reported that employers had attributed 120,136 cuts to AI so far in 2026, representing 21% of all cuts during that period. AI had frequently been cited as a main reason for job losses earlier in the year, while September’s share was lower than the cumulative share. The comparison shows a change in the mix of reasons employers gave for announced cuts; it does not establish the cause of the broader tech employment contraction.

Key takeaways for decision-makers

• Employment and recruitment measure different decisions: US tech employment across industries fell by about 6,000 in September, while new IT postings rose 16% year over year. Staffing planners need role-specific recruitment data alongside employment trends to assess candidate availability.
• Hiring demand centers on priority skills: Active postings requiring AI skills increased by 32,327 in September to 349,821. Hiring managers need a clear business purpose and defined skill requirements for each proposed position.
• Recruitment delays affect delivery schedules: ManpowerGroup put the typical time to fill an engineer role at 77 days. Engineering managers need to build recruitment time into project schedules before committing work to additional capacity.
• Cost uncertainty raises the bar for hiring commitments: Energy costs, potential healthcare increases, interest-rate risk and geopolitical uncertainty are encouraging caution. Finance and technology executives need to test proposed hires against operating-cost pressures and strategic priorities.
• AI hiring and AI-attributed cuts require separate tracking: Employers cited AI in about 9% of September’s announced cuts across all sectors, compared with 21% year to date. Workforce planners need to distinguish demand for AI skills from employers’ stated reasons for eliminating positions.