Agentic AI and Labor Market Polarization: Who Gains, Who Loses, and How Fast?

The rapid advancement of agentic artificial intelligence (AI) systems capable of autonomous reasoning, decision-making, and multi-step task execution marks a transformative shift in the global labor landscape. Unlike previous automation waves, agentic AI can independently coordinate workflows, integrate with enterprise tools, and generate complex outputs, expanding its impact beyond routine tasks to mid-level cognitive occupations. This research investigates how agentic AI accelerates labor market polarization by identifying which workers gain, which face displacement, and the expected speed of these transitions. Through a mixed-method approach combining occupation-level task analysis, economic modeling, and sectoral case studies, the study reveals that high-skill strategic and creative roles stand to benefit significantly from productivity amplification, while many middle-skill analytical and administrative jobs face heightened substitution risk. Low-skill roles may experience mixed outcomes, with some benefiting from technology-enabled upskilling and others from downward competitive pressure. Findings suggest that the pace of change will be faster than prior technological shifts due to reduced deployment costs, scalable agentic ecosystems, and expanding enterprise adoption. The study concludes by outlining critical policy considerations for reskilling, labor protections, and inclusive AI governance to mitigate widening inequality.