The Impact of Artificial Intelligence on Labor Demand: Economic and Social Implications

Abstract

This conceptual review examines the multifaceted effects of artificial intelligence (AI) adoption on labor demand through systematic literature synthesis and comparative institutional analysis. We develop a theoretical framework analyzing how liberal market economies (LMEs) and coordinated market economies (CMEs) differentially facilitate AI innovation and labor market restructuring. Through thematic synthesis of existing theoretical and empirical research, we examine institutional mechanisms—including industrial relations, vocational training systems, corporate governance, and regulatory frameworks—that shape AI adoption patterns and employment outcomes. Our conceptual framework proposes six testable propositions linking institutional contexts to AI innovation types and labor market outcomes, suggesting that LMEs provide more adaptive ecosystems for radical AI innovation while CMEs favor incremental approaches with greater workforce protection. This theoretical contribution bridges labor economics, varieties of capitalism scholarships, and AI policy discourse, providing foundations for future empirical research. We acknowledge that our analysis primarily draws from pre-generative AI literature (2010-2022), with limited coverage of post-2022 developments in large language models and their distinct labor market implications, representing an important avenue for future conceptual and empirical work