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DOI: 10.15862/01FAOR425 (https://doi.org/10.15862/01FAOR425)

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Matveenko V.A. The impact of digitalization and artificial intelligence on labor productivity in developed and developing economies. Russian journal of resources, conservation and recycling. 2025; 12(s4). Available at: https://resources.today/PDF/01FAOR425.pdf (in Russian). DOI: 10.15862/01FAOR425

The impact of digitalization and artificial intelligence on labor productivity in developed and developing economies

Matveenko Valery Aleksandrovich
Financial University under the Government of the Russian Federation, Moscow, Russia
E-mail: V89299294420VV@gmail.com

Academic adviser: Kapustina Nadezhda Valerievna
Financial University under the Government of the Russian Federation, Moscow, Russia
E-mail: NVKapustina@fa.ru
RSCI: https://elibrary.ru/author_profile.asp?id=584779

Abstract. This study provides a comprehensive analysis of the impact of digitalization and artificial intelligence technologies on labor productivity dynamics in the context of differential economic development across countries. The contemporary economic reality is characterized by unprecedented acceleration in digital technology adoption, with implementation scales varying significantly between developed and developing nations. The research subject encompasses mechanisms through which artificial intelligence technologies affect labor productivity across various economic sectors, considering institutional environment specificity and countries’ technological readiness levels. The study employs comparative analysis of empirical data from international organizations including OECD, IMF, World Bank, and UNCTAD, covering the period 2020–2025. Analysis of theoretical approaches evolution demonstrates transition from Solow’s exogenous growth models to Romer-Lucas endogenous models, incorporating technological progress as an internal factor of economic development. Key findings indicate uneven impact of artificial intelligence on labor productivity: developed countries demonstrate potential productivity growth of 0,4–1,3 percentage points annually, while developing economies face substantial implementation barriers. The developed conceptual model identifies critical factors for successful digital transformation, including human capital levels, digital infrastructure quality, and institutional readiness. Scientific novelty lies in systematizing mechanisms of artificial intelligence’s differentiated impact on labor productivity depending on economic development level and identifying threshold values of technological readiness for realizing positive effects. Practical significance is determined by the possibility of using results in developing national digital transformation strategies and labor market adaptation policies to technological changes.

Keywords: artificial intelligence; digitalization; labor productivity; economic growth; digital transformation; automation; human capital; technological progress; developed economies; developing countries

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