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. In this scenario, AI advances at a breakneck speed, but workforce readiness remains limited. Education and training systems, entangled in traditional approaches, have failed to produce the adaptive and cross-functional talent needed for an AI-native economy. A culture of accelerationism takes hold, and automation becomes pervasive. Governments and businesses race to automate as a stopgap to scarce talent, deepening dependence on technology and displacing workers at scale. Rising capital commitments to AI CapEx in the late 2020s have drastically lowered barriers to AI deployment across industries. Competing models, AI agents and fully autonomous systems scale fast. Automation has become significantly cheaper than mass upskilling and reskilling of workers. Some governments and sectors attempt to regulate mass AI deployment to mitigate societal risks, but competition renders restrictions economically and politically untenable. –Occupations and tasks: Labour markets have been severely disrupted by mass displacement and tightening employment pathways across all skill levels. AI and end-to-end automation are taking over key tasks across sectors. Workforce displacement is no longer transitory. In many sectors, entire occupational families have shrunk or disappeared. New AI- complementary occupations have emerged, but the workforce has struggled to reskill and adapt to capture emerging opportunities. The share of tasks absorbed by technology has surpassed 50%, approaching 90% in high- exposure sectors. Talent shortages have pushed some businesses to fully outsource decision- making to AI agents with limited to no oversight from human workers. Labour mobility has nearly dried out by 2030. Human-centric jobs and gig work have attracted displaced talent, but cannot absorb all displaced workers. Additionally, these roles are not immune to automation as AI acceleration absorbs new tasks, and there are further advancements in robotics. –Economic outlook: Although AI breakthroughs have delivered immense productivity gains, the global economy has been strained by the depth of disruption. Volatility and uncertainty have increased. Corporate profit margins increase, driven by a handful of state-like companies controlling foundational models, compute and proprietary datasets. They gain unchecked influence in the global economy, determine the cost of automation and control access to – and governance of – AI. Consumer confidence ebbs globally, falling below the historical low of 44.10 The scale of AI deployment and data centre workloads grows faster than grid capacity, intensifying energy and the environmental impact of automation. Exponential AI advancement, limited workforce readinessExponential AI advancement outpaces the capacity of the workforce to adapt. Businesses race to automate as a stopgap, displacing workers faster than education and reskilling systems can respond. Agentic AI takes over key processes, creating a productivity upsurge, but also new risks. Economies race ahead technologically but fracture socially: unemployment spikes, consumer confidence erodes and governments face mounting societal risks and instability. 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 2: The Age of Displacement Four Futures for Jobs in the New Economy: AI and Talent in 2030 10

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