teams. AI tools have facilitated a reduction in completion time by as much as 80%11 for certain tasks, with most administrative, standardized and basic analytical tasks being hollowed out. By 2030, more than 40% of skills have changed, surpassing earlier forecasts.12 Labour markets show higher mobility and job fluidity, with stronger demand for problem-solving, social, managerial and uniquely human skills. The hybrid roles that combine AI knowledge and narrow domain expertise have expanded. The share of gig workers and entrepreneurs has also risen, with broadening access to AI and societal readiness spurring experimentation. However, job quality varies widely: improving where workers lead AI, and deteriorating where AI shrinks human creativity and agency. –Economic outlook: Human–AI complementarity has succeeded in breaking the tepid GDP growth patterns of the preceding decades. Without an automation shock, productivity gains accumulate steadily, with annual labour productivity growth spiking above 1.5% recorded in the early 2020s.13 The uptick in dynamism and augmentation- accelerated innovation across sectors strengthens consumer and investor confidence. Higher margins and lower cost pressures have somewhat stabilized inflation, but intensifying competition and a tight labour market keep volatility risks high. Businesses and geographies with transparent AI adoption frameworks enjoy lower risk premiums, trust and investment inflows. Differences in AI infrastructure maturity and energy costs fuel divergence between AI- ready economies and the rest of the world. –Value chains: Businesses reorganize around more modular, digitized and AI-augmented workflows, with human workers in core loops and decision- making roles. Automation density has also risen, primarily affecting highly standardized processes. –Inequality and polarization: Inequality widens between workers who can adapt dynamically to the evolving AI landscape and those locked out by lower access to education, digital infrastructure or supportive employers. However, with AI tools lifting skills floors, wage gaps narrow slightly among mid- and high-skilled workers. The rise of remote, flexible work and entrepreneurship has also widened economic opportunities across peripheral regional and marginalized communities. With AI-generated content overtaking human content,14 polarization and misinformation concerns grow. Trust shifts towards curated sources, verified platforms and human intermediaries. –Policy and regulatory landscape: AI standards and data privacy regulations multiply but vary widely across jurisdictions. Some geographies and sectors invest in harmonization and interoperability of AI and data systems. Others focus on restrictive approaches and nationalization of AI tools, networks and infrastructure. Talent mobility frameworks also oscillate between borderless digital talent pipelines and talent protectionism. 1 No authoritative or standardized global measure of “AI literacy and adjacent skills” currently exists. Notes: The arrows denote a directional change in a given scenario characteristic. All values are at the global level, unless specified otherwise. The analysis is based on scenario narratives and extrapolations from similar existing research. The directionality is illustrative and for scenario-building purposes only. Incremental AI advancement, limited workforce readinessSteady AI progress meets a workforce lacking critical skills. Productivity growth is patchy, and businesses lean on automation to backfill scarce talent. Gains concentrate within businesses and geographies with AI expertise, while others face eroding competitiveness. Displacement hits primarily routine roles, while the value of skilled trades and manual occupations increases. The hope of AI-enabled prosperity fades into frustration, as adoption gaps fuel inequality, create a bifurcated economy and limit growth. AI capability, top five models average MMMU Baseline: 84.2 (Xiang, Y. et al., 2025) AI literacy and adjacent skills Baseline: N/A1 Labour productivity growth, % annual Baseline: 1.5% (International Labour Organization, 2020–2025 annualized) Unemployment rate, % Baseline: 5% (International Labour Organization, 2025) Consumer confidence index Baseline: 48.8 (Ipsos, 2025) Scaling of agentic AI, % of businesses Baseline: 23% (McKinsey, 2025) Wage polarization, D9/D1 earners ratio Baseline: 16.8 (International Labour Organization, 2025) S&P 500 operating margin, % quarterly Baseline: 12.6% (S&P , 2025 average) Scenario 4: Stalled Progress Four Futures for Jobs in the New Economy: AI and Talent in 2030 12

Four Futures for Jobs in the New Economy AI and Talent in 2030 2025