PwC Finds AI Creates Two-Track Global Labour Market

According to PwC's 2026 Global AI Jobs Barometer, released June 15, AI is reshaping the global labour market into a two-track structure. The Barometer analysed more than 1 billion job ads across six continents, per the report. It classifies roles as "professionalised" (where AI automates routine tasks and emphasises human judgement and expertise) and "democratised" (where AI makes roles easier for non-experts). PwC reports that "professionalised" roles show twice the job growth and 42% faster salary growth than "democratised" roles. The report finds firms most able to use AI experienced headcount growth of 52% versus 36% for the least AI-exposed firms, and wage growth of 24% versus 17%. PwC highlights that "super-star companies" most exposed to AI achieved labour productivity gains of 163%. Jobs explicitly requiring AI skills grew 69%, relative to 9% for the total jobs market, and the average wage premium for AI skills rose to 62%. In US entry-level data covering 2.4 million job ads, PwC found AI-exposed entry-level roles are seven times more likely to list traditionally senior human-intensive skills; those roles grew 35% since 2019 while other entry-level roles fell 10%.

Industry-pattern observations: the Barometer uses large-scale job-ad text analysis, which captures employer demand signals rather than worker-level outcomes. Measuring exposure through job-ad language typically highlights changing skill requirements and wage offers, but it does not directly measure incumbent worker displacement or retraining outcomes. Analysts reading demand-side job-ad studies should note that job posting counts can be influenced by hiring practices, churn, and multiple postings per vacancy.

Industry context: The report reinforces a recurring distinction in recent research between task augmentation and task automation. For practitioners, the combination of a 62% wage premium for AI skills and rapid growth in AI-labelled openings suggests continued market pressure to upskill in AI-related competencies and in human-intensive skills like judgement and leadership. Employers, training providers, and workforce planners will likely treat job-ad signals as an input when designing curricula and recruitment criteria, not as a full view of labour market transitions.

Watch for follow-up metrics that validate demand-side signals at the worker level, including employment retention, wage trajectories for incumbent workers, and formal upskilling investments. Observers should also monitor sectoral variation in the two-track pattern and whether entry-level "seniorised" roles persist as hiring and onboarding practices evolve.