The Age of Agentic AI (2025–2035): Jobs, Growth, and the New Macroeconomic Playbook

This paper examines the macroeconomic, labor-market, and productivity effects of large-scale adoption of agentic artificial intelligence systems between 2025 and 2035. Drawing on synthesis from OECD, IMF, ILO, WEF, IEA, BIS, and Stanford AI Index projections, combined with micro-level randomized and quasi-experimental productivity evidence, the study estimates a realistic base case of sustained global labor-productivity gains of approximately 0.45–0.53 percentage points annually through the mid-2030s. The analysis emphasizes that AI’s economic impact is fundamentally mediated by institutional complements—human capital development, data quality, process redesign, infrastructure capacity, energy availability, governance frameworks, and competition policy. Rather than widespread technological unemployment, employment effects are likely to be net positive by 2030 through task reallocation and augmentation, with localized displacement concentrated in routine clerical and administrative work. Using a staged diffusion framework (2025–2035) and Monte-Carlo scenario modeling (20,000 trials), the paper evaluates adoption trajectories, productivity distributions, sector-specific transitions, and systemic risks including energy and water bottlenecks, vendor concentration, safety failures, financial-system fragility, and policy fragmentation. The core conclusion is that AI functions as an economic amplifier rather than a deterministic disruptor: when paired with effective institutions and governance capacity it supports broad-based growth; absent those complements, it magnifies inequality, environmental strain, and systemic risk. Policy recommendations focus on targeted workforce upskilling, infrastructure investment, transparent safety evaluation regimes, competitive compute markets, and coordinated regulatory implementation to ensure that agentic AI adoption yields durable and inclusive economic gains.