The global labour market is being fractured by artificial intelligence into winners and losers, with the crucial difference lying in how companies deploy the technology, according to new research from PricewaterhouseCoopers. Rather than simply automating tasks, the most successful organisations are using AI as a tool to amplify distinctly human capabilities—creativity, judgment, empathy and leadership—and these companies are pulling ahead dramatically in productivity and growth. Meanwhile, firms relying on AI primarily to reduce headcount are finding themselves lagging as the competitive landscape shifts to favour intelligence and innovation over cost-cutting efficiency.
The findings emerge from PwC's 2026 AI Jobs Barometer, a comprehensive analysis drawing on over one billion job postings across 27 countries and territories combined with labour-market, financial and occupational data. The scale of the research underscores how fundamentally AI is reshaping the nature of work globally, with implications that extend far beyond Silicon Valley into every sector and geography, including Southeast Asia's rapidly digitalising economies. The disparity in outcomes between companies using AI differently is stark enough to reshape entire industries and labour markets over the coming years.
Positions requiring specialised AI competencies have expanded at a breathtaking pace, growing roughly eight times faster than the overall job market in 2025. Jobs demanding expertise in machine learning, prompt engineering and similar technical skills grew 69 percent last year, compared with just 9 percent growth across the broader labour market. Equally significant, wages for these highly technical roles are expanding substantially, with the wage premium reaching 62 percent above baseline salaries—up from 57 percent the previous year. This premium varies dramatically by industry: consumer markets offer a striking 118 percent wage premium for AI specialists, whereas government and public sector roles command only 16 percent above standard rates.
Yet the most consequential finding concerns the jobs that are flourishing fastest. Professional roles such as radiologists, air traffic controllers and recruiters—positions where AI augments rather than replaces human judgment—are experiencing job growth twice as rapid as positions where AI primarily makes routine tasks accessible to non-specialists. Financial analysts exemplify this pattern: rather than being displaced by AI tools, they have become more valuable as the technology enables them to undertake far more sophisticated analyses. Analyst employment has continued rising as new specialisations emerge, many commanding premium compensation, demonstrating that the feared wholesale displacement of knowledge workers appears less likely than some analysts predicted.
This divergence is particularly evident in entry-level hiring patterns, where a subtle but profound transformation is occurring. Roles requiring what were traditionally senior competencies—judgment, empathy, ethics, creativity and leadership—have expanded 35 percent since 2019, while conventional entry-level positions without such demands have contracted 10 percent. Companies are increasingly requiring junior employees to demonstrate sophisticated human capabilities that were once reserved for experienced staff, fundamentally altering how organisations structure talent development. The implication is that traditional apprenticeships and on-the-job training pathways may be disappearing, forcing both employers and educational institutions to rethink how professionals acquire foundational skills.
Corporate hiring intentions reveal management's recognition of this shift. A parallel PwC Global CEO Survey found that 49 percent of chief executives expect AI adoption to reduce hiring of junior staff over the next three years, whereas only 12 percent anticipate cuts to senior roles. This asymmetry suggests that companies are not simply eliminating entry-level positions but rather expecting fewer people to fill them while raising expectations for their capabilities. The challenge this creates is substantial: organisations must simultaneously reduce junior hiring while expecting those they do employ to possess advanced human skills, creating a potential bottleneck in talent pipelines.
CounterIntuitively, greater AI exposure correlates with employment growth rather than contraction. Companies positioned at the highest end of AI adoption increased headcount 52 percent from 2018 baseline levels, substantially exceeding the 36 percent growth achieved by firms with minimal AI exposure. This finding contradicts the dystopian automation narrative that often dominates public discourse, suggesting instead that AI-driven transformation creates economic opportunities that ultimately expand workforce needs, though the nature of work fundamentally changes. The companies thriving in this environment are those orchestrating the transformation strategically rather than allowing it to happen to them.
Industry performance reflects varying capacities to harness AI for human amplification. Technology, media and telecommunications led AI-driven job creation last year at 11 percent growth, followed by professional services at 6 percent, while healthcare lagged significantly at under 1 percent. This variation partly reflects sector maturity in AI adoption and partly the different ways industries are deploying the technology. Sectors that have successfully positioned AI as an enabling tool for professional expertise are experiencing robust growth, while those struggling to integrate AI into existing service delivery models are advancing more slowly.
The productivity implications are equally striking. Companies with the highest AI exposure posted 34 percent productivity growth between 2018 and 2025, compared with 24 percent for those least exposed. Even more dramatic, the top 20 percent of companies by AI adoption achieved labour productivity gains of 163 percent relative to 2018 levels—nearly five times the average for AI-exposed firms overall. These figures suggest that the competitive advantage in a post-AI economy flows less to those who cut costs aggressively and more to those who harness AI to amplify human productivity and innovation capacity.
For Malaysian and Southeast Asian businesses, these findings carry urgent strategic implications. Regional economies increasingly competing in global labour markets and technology sectors cannot afford to fall behind the curve in AI adoption, yet deploying the technology purely for cost reduction may actually create long-term disadvantages. The research suggests that success requires integrating AI into business models that enhance rather than eliminate human expertise, creating a dual challenge: identifying and retaining talent capable of working effectively alongside advanced technology while simultaneously building organisational capabilities to implement such augmentation strategies.
The transformation underway extends beyond recruitment and compensation into fundamental questions about workforce development and competitive positioning. As Joe Atkinson, PwC's global chief AI officer, notes, companies achieving greatest returns are using AI to amplify human expertise, accelerate innovation and create new value sources—characteristics that require sustained investment in workforce development rather than cost reduction. This philosophical shift from automation-as-cost-cutting to AI-as-enabler represents perhaps the most consequential finding for business leaders contemplating their AI strategies and investment priorities in coming years.
