AI Skills Now Command a 62% Wage Premium as PwC Barometer Reveals a Two-Track Global Labour Market

The most comprehensive study of AI's impact on global employment published to date has delivered a verdict that will unsettle complacent professionals and encourage forward-thinking ones in equal measure. PwC's 2026 Global AI Jobs Barometer, released on 15 June and drawing on analysis of more than one billion job advertisements across 27 countries and territories, finds that AI is cleaving the global labour market into two sharply diverging tracks. Jobs requiring specific AI skills — such as prompt engineering, machine learning, and AI-adjacent analytical work — are growing roughly eight times faster than the overall market, at 69% versus 9%, while the average wage premium for those skills has climbed to 62%, up from 57% the previous year. The number of AI-related jobs posted is now almost twice the level seen in 2024, with growth in AI hiring outpacing all other employment categories since 2015.

PwC's framework divides the emerging landscape into two categories it labels professionalised and democratised roles. Professionalised roles — such as radiologists and recruiters, where AI handles routine tasks so that human judgement and expertise become more, not less, valuable — are seeing twice the growth in available jobs and 42% faster salary increases than democratised roles, where AI simplifies the job itself and reduces the need for deep specialist knowledge. Pete Brown, PwC's Global Workforce Leader, has noted that the traditional relationship between experience and expertise is changing, with AI removing some of the routine work that once acted as an apprenticeship while simultaneously increasing demand for judgement, leadership, and adaptability much earlier in careers. The wage premium varies dramatically by industry: as high as 118% in consumer markets and as low as 16% in government and public sector work, according to the Barometer.

For employers, the productivity data embedded in the report may be the most consequential finding of all. Companies operating in the most AI-exposed sectors recorded 34% productivity growth between 2018 and 2025, compared with 24% for those least able to use AI. Within that group, a pronounced superstar effect has emerged: the top 20% of the most AI-exposed companies achieved average labour productivity growth of 163% relative to 2018 levels — nearly five times higher than the most AI-exposed companies overall. Perhaps most counter-intuitively, headcount growth at the most AI-exposed companies is outpacing growth at the least AI-exposed companies, at 52% versus 36% on a 2018 baseline, suggesting that the most effective deployments of AI are augmenting rather than replacing workforces. Joe Atkinson, Global Chief AI Officer at PwC, has stated that the companies seeing the greatest returns on AI are using it to amplify human expertise, accelerate innovation, and create entirely new sources of value.

The implications for early-career professionals are particularly acute. PwC's analysis of 2.4 million entry-level roles in the United States found that jobs with high AI exposure are now seven times more likely to require skills traditionally associated with senior employees, including leadership, decision-making, and interpersonal engagement. Demand for these seniorised entry-level roles has grown 35% since 2019, while other entry-level positions have declined by 10% over the same period. Research published by Lightcast found that 51% of job postings requiring AI skills now sit outside IT and computer-science occupations — spanning marketing, human resources, finance, and operations — often with no coding requirement whatsoever. This dismantles the assumption that AI fluency is purely a technical concern and underscores how broadly the skill premium is spreading across professional disciplines.

For professionals and organisations alike, the Barometer's message is directional rather than deterministic. S&P Global's own analysis of employment trends, drawing on PMI survey data, found that the dominant pattern across the global economy remains one of task reallocation — shifts in labour demand rather than outright workforce reduction — while noting that globally the net employment effect has been slightly negative, with the balance of firms reporting job losses running five percentage points higher than those reporting gains. That gap is likely to widen as agentic AI — systems designed to plan, act, and complete multistep workflows with significant autonomy — moves from experiment to enterprise standard. Workers and HR leaders who treat the 62% wage premium as a ceiling are likely to find it has become a floor before the decade is out.