How is AI changing jobs and skills?

What the research shows

Employers are paying more for AI skills. PwC's 2026 Global AI Jobs Barometer, based on more than one billion job advertisements in 27 countries and territories, finds an average wage premium of 62% for AI skills, up from 57% a year earlier, ranging from 16% in government and public-sector work to 118% in consumer markets. Jobs requiring specific AI skills grew 69%, against 9% for the jobs market overall.

Companies most able to use AI are growing faster. Since 2018 they have increased headcount by 52%, against 36% at the least AI-exposed companies, and wages by 24% against 17%. Roles where AI amplifies expert judgement, such as radiologists or recruiters, are seeing twice the job growth and 42% faster salary growth than roles AI makes easier for non-experts.

Entry-level work is being redefined. In the United States, entry-level roles most exposed to AI are seven times more likely to ask for traditionally senior skills such as leadership and judgement. Openings for these roles grew 35% since 2019, while other entry-level roles shrank 10%.

Expectations of job cuts are running ahead of actual cuts. In McKinsey's 2026 survey, 39% of respondents expect AI to reduce their organisation's total headcount over the next year, up from 32% a year earlier, but only 14% report that AI contributed to a decline over the past year, less than half the share that had expected one.

Longer term, the World Economic Forum's Future of Jobs Report 2025 expects 170 million jobs to be created and 92 million displaced by 2030, a net gain of 78 million, with 39% of key skills changing. Asked which human skills matter more as AI takes on work, AI users in Microsoft's 2026 Work Trend Index put quality control of AI output (50%) and critical thinking (46%) first.

What comes next

• Demand will keep shifting toward roles that combine AI fluency with judgement, leadership and client skills.
• Workforce plans built on expected AI savings will face more scrutiny as expectations outpace actual reductions.
• Entry-level hiring will increasingly test for skills once expected later in a career.

What it means for leaders

• Identify the roles most exposed to AI and plan the skills each one needs.
• Redesign early-career roles and development paths rather than removing them.
• Train people to check, refine and take responsibility for AI output.
• Base workforce plans on observed productivity, not forecasts alone.