The role of generative artificial intelligence on labor market: literature review

The purpose of the study. This systematic literature review examines the role of AI in the labor market and its effectiveness in terms of productivity and employment outcomes.

Methodology. We reviewed recent studies from 2020 to 2025 across global and regional contexts to assess how AI adoption influences job creation, displacement, and workforce composition. The objective was to synthesize current evidence on whether AI augments human labor or automates it away, and under what conditions. Using a systematic methodology, we analyzed 17 key publications from peer-reviewed academic journals.

Originality / value. Our review finds that AI’s net impact on employment has so far been modest, with no clear evidence of mass unemployment caused by AI. However, AI-driven automation has uneven effects: it displaces certain routine and low-skill jobs while creating new possibilities for high-skill tasks, thus contributing to labor market polarization. Notably, AI tends to complement and enhance the productivity of skilled employees, whereas low-skilled roles face significant automation risk.

Findings. In our discussion, we highlight the following findings: agreement that AI demands workforce upskilling and policy support, alongside divergent results, for example, conflicting evidence on net job creation in different contexts. A meta-analysis of the literature reveals surging research interest in 2023–2025 and a focus largely on advanced economies. Finally, we discuss implications: while AI can enhance labor productivity and create value, proactive measures are needed to ensure these gains translate into broad-based employment benefits. The review identifies research gaps such as limited studies in low-income countries and long-term generative AI effects and underscores the importance of policies to manage AI’s workforce transition.

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