AI & Jobs Statistics 2026: Who Is Gaining and Who Is Losing

AI is creating and cutting jobs in 2026. The data shows a labor market that is splitting into group that gain and groups that lose, not one that is shrinking.

This article pulls together figures from the World Economic Forum, PwC, Challenger, Gray & Christmas, Stanford, the Dallas Fed, Indeed and others. Each number is labeled as a forecast or a measurement, because the two often differ by a wide margin.

The World Economic Forum (WEF) expects 170 million jobs to be created and 92 million displaced by 2030. That is a net gain of 78 million jobs worldwide. The same period will bring a hard transition for some workers.

These figures measure different things. They should not be added together or compared row by row.

A Harvard Business School working paper analyzed nearly all US job postings from 2019 to March 2025. Openings for routine, automation-prone roles fell 13% after ChatGPT launched in November 2022, while demand for analytical, technical and creative roles grew 20%.

The WEF numbers also cover every trend it tracks, including demographics and the green transition. AI alone accounts for a much smaller share, as the sections below explain.

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AI Job Cuts Are Rising, but Still a Small Part of All Layoffs

Challenger, Gray & Christmas tracks the reasons US employers give for announced layoffs. From January to August 2026, employers cited AI for 116,175 cuts. That is about 22% of the 529,914 total and the top stated reason for the year.

The growth is steep. AI was named in 12,742 cuts in 2024 and 54,836 in 2025. The 2026 total through August is already more than double the figure for all of 2025.

Technology absorbed the most. The sector announced 149,023 cuts through July, up 67% from a year earlier and 31% of every cut announced in 2026.

Two cautions apply. These are employer announcements with employer-stated reasons, not verified separations. Also, AI fell to the fourth most cited reason in August, which ended a five-month run at the top.

Surveys add context. McKinsey found that 14% of respondents at organizations using AI said it contributed to a smaller workforce over the past year. The New York Fed found that 1% of service firms using AI laid off workers because of it, while 12% said they hired fewer people.

Hiring less is harder to count than firing. That gap may mean layoff trackers capture only part of the effect.

What the Forecasts Say, and Why They Differ

Forecasts vary widely because they ask different questions. Some count jobs exposed to AI. Others estimate how many workers could lose work.

Goldman Sachs Research estimates that 6% to 7% of the US workforce could be displaced if AI is widely adopted, with a range of 3% to 14%. Goldman calls the effect temporary.

A popular claim says Goldman predicted 300 million jobs would be lost. The 2023 report said AI could expose the equivalent of 300 million full-time jobs to automation. Exposed does not mean replaced.

The IMF says almost 40% of global employment is exposed to AI. That rises to about 60% in advanced economies and falls to 26% in low-income countries. McKinsey calls its 57% figure technical potential, not a forecast of job losses.

For AI and information processing technology alone, the WEF expects 11 million jobs created and 9 million displaced by 2030.

The St. Louis Fed found a correlation of 0.47 between an occupation’s AI exposure and its rise in unemployment from 2022 to 2025. The authors call it correlation, not causation.

Measured effects so far are smaller than many forecasts. A study of Danish records ruled out effects larger than 2% on earnings and hours two years after ChatGPT launched. Yale Budget Lab and Brookings found no discernible disruption to the broader US labor market in the 33 months after its release.

AI Skills Carry a Growing Pay Premium

PwC reports that workers with AI skills earn a 62% wage premium over peers in the same roles. The premium was 57% a year earlier and 25% the year before that, though an earlier PwC report cited 56% for the prior year.

The figure compares advertised wages for similar jobs with and without AI skills across 27 countries. It does not control for education, experience or location. It is not an average AI salary.

Demand is rising as well. Postings that require AI skills grew 69%, compared with 9% for the job market overall.

The premium varies by sector. It reaches 118% in consumer markets and falls to 16% in government and public sector work.

Research by Fabian Stephany of the Oxford Internet Institute found that AI skills can offset other disadvantages. Older applicants and candidates without advanced degrees saw better callback rates when AI skills appeared on their résumés.

Young and Entry-Level Workers Face the Most Pressure

The clearest evidence of harm is in early-career work. A Stanford payroll study using ADP records found a 13% relative employment decline for workers aged 22 to 25 in the most AI-exposed occupations.

An update from the Stanford Digital Economy Lab, using data through June 2026, puts the gap at 19%. Experienced workers show no gap. The authors call it an early indicator, not a causal estimate.

The Stanford AI Index 2026 reports a 16% fall for the same age group. Early-career software developers saw a larger drop of about 20%.

The Dallas Fed found that young workers aged 20 to 24 in AI-exposed jobs fell from 16.4% to 15.5% of employment between November 2022 and September 2025. This is not mainly about layoffs. Employers are hiring fewer young people into those roles.

The job-finding rate for young workers entering highly exposed occupations dropped by more than 3 percentage points from its November 2023 peak.

Ravio data on European tech companies shows entry-level hiring down 73.4% and administrative hiring down 35.5% in 2025. Half of reward leaders surveyed cited AI automation as the reason for deprioritizing administrative roles.

PwC adds a twist. AI-exposed junior roles are seven times more likely to demand traditionally senior skills such as leadership. Entry-level roles of this kind grew 35% since 2019, while overall early-career postings in highly exposed sectors stayed flat.

Anthropic reported no systematic rise in unemployment among workers in the most exposed occupations since late 2022, though hiring of younger workers shows signs of slowing. Anthropic sells AI models, so readers should weigh that source with care.

Other forces matter too. The OECD says young people face difficult entry conditions, and the Stanford authors do not claim AI is the only cause.

Software Developers: A Rebound With Limits

Software development is a useful test case. Indeed Hiring Lab reports that US software postings rose almost 15% from late February 2025, while all job postings fell about 7%.

Postings are still about 27.5% below their pre-pandemic level. The earlier drop was not only an AI story, since technology firms also pulled back after a hiring surge during the pandemic.

The rebound is uneven. Senior roles made up 71% of the increase between May 2025 and May 2026, and jobs with AI in the title made up 37%.

GitHub reported that one in three pull requests now involve an AI agent. A year earlier the figure was fewer than one in 10.

Eric Kutcher of McKinsey said, “We’re seeing much more growth in the places we thought we were gonna see the biggest displacement.” Sneha Puri, an economist at Indeed Hiring Lab, said employers still need developers to oversee AI work and help clients put it to use.

The US Bureau of Labor Statistics (BLS) projects 10% growth for software developers from 2025 to 2035. That would take employment from about 1.72 million to 1.89 million.

AI-Exposed Companies Are Growing, Not Shrinking

PwC found that productivity growth is 40% higher at companies most exposed to AI than at those least exposed. Sector productivity grew 34% from 2018 to 2025 in the most exposed group, against 24% in the least exposed.

Headcount tells a surprising story. The most exposed companies grew headcount 52% since 2018, compared with 36% for the least exposed. Wages grew 24% against 17%.

The top fifth of the most exposed companies achieved 163% productivity growth on average. PwC calls this a super-star effect.

PwC also describes a two-track job market. In jobs it calls professionalised, AI handles basic work and leaves expert tasks to people. In democratised jobs, AI makes complex work easier for non-experts.

These are associations, not proof of cause. Strong firms may adopt AI first, so AI may not explain every gain.

A gap also remains between use and mastery. McKinsey found that nearly 90% of organizations use AI in operations, while Gartner reports that only 9% have reached true AI maturity.

Skills Are Changing Fast, and Employers Plan to Retrain

The WEF expects 39% of workers’ core skills to change by 2030, down from 44% in its 2023 edition. It lists the skills gap as the largest barrier to business change, cited by 63% of employers.

PwC finds that skills in the most AI-exposed jobs are changing more than twice as fast as in the least exposed jobs. New tasks added to those jobs are 2.5 times more likely to rely on skills such as empathy, judgment and creativity.

Employers say they will respond mainly by retraining. Some also plan to cut staff. In the WEF survey, 41% plan to reduce their workforce where AI automates tasks.

The WEF says 59 of every 100 workers will need reskilling or upskilling by 2030, and 11 of them are unlikely to receive it. Analytical thinking is the top core skill, cited by 70% of employers. Resilience, flexibility and agility follow at 67%.

New jobs are also appearing outside tech. Goldman Sachs reports that data center construction jobs have grown by 216,000 since 2022.

What Workers Think, and Who Is Gaining and Losing

Public worry is rising. Pew Research Center found that 71% of US adults think AI will lead to fewer jobs over the next 20 years, up from 64% in 2024. Only 5% expect more jobs.

Adults under 30 are more worried, at 73%, up from 61% two years earlier. In 34 of 37 countries surveyed, more people expect AI to reduce jobs than to add them.

Gallup found that 18% of US employees think it is very or somewhat likely their own job will be eliminated within five years because of AI or automation, up from 15% in 2025. McKinsey found that 39% of respondents expect AI to shrink their organization’s headcount over the next year, up from 32%.

Policy also shapes who gains. Ireland, Finland and Denmark lead the IMF Skill Readiness Index, which covers 23 countries, thanks to high shares of tech graduates and strong adult retraining systems.

The BLS projects that employment of secretaries and administrative assistants will fall 2% from 2025 to 2035, a loss of 75,300 jobs. It ties the decline to technology, including AI.

Goldman Sachs has called AI the big story in 2026 in labor. The impact is still concentrated in tech, creative and knowledge work, which are a small share of the whole economy. The BLS notes that technological displacement tends to unfold more slowly than forecasters predict.

The data does not show a jobs collapse or a smooth transition. It shows pay and hiring moving toward workers with AI skills and experience, while early-career workers in exposed fields face a harder path in.

Forecasts will keep changing, so the measured numbers deserve the most weight. The layoff counts, posting data and payroll studies above are the ones to watch as 2026 ends.

Sources

• World Economic Forum, Future of Jobs Report 2025
• PwC, 2026 Global AI Jobs Barometer
• Challenger, Gray & Christmas, job cuts reports
• Stanford Digital Economy Lab, AI and early-career employment
• Stanford AI Index 2026
• Federal Reserve Bank of Dallas, research on AI and young workers
• Harvard Business School Working Knowledge, AI and job postings
• Goldman Sachs Research, AI and the labor market
• International Monetary Fund, AI and jobs analysis
• International Labour Organization, generative AI and jobs
• Indeed Hiring Lab, software development postings
• CNBC, AI is automating coding, so why are software developer job postings on the rise?
• US Bureau of Labor Statistics, Employment Projections 2025 to 2035
• Pew Research Center, public views on AI and jobs
• McKinsey, The State of AI Global Survey
• Ravio, European tech compensation and hiring data