AI-driven productivity dynamics in BRICS economies: Evidence from a Malmquist Total Factor Productivity Analysis

Abstract

This study examines the impact of artificial intelligence (AI) on productivity dynamics in BRICS economies (Brazil, Russia, India, China, and South Africa) over the period 2005–2023. Using a two-stage empirical approach, productivity growth is first measured through the Malmquist Total Factor Productivity (TFP) index, decomposing changes into efficiency change (EC) and technological change (TC). In the second stage, panel regression analysis evaluates the relationship between these components and key AI penetration indicators, including AI patents, investment, robot density, and digital infrastructure. The results reveal significant divergence across BRICS economies. China and India exhibit sustained productivity growth driven primarily by technological progress, whereas Brazil, Russia, and South Africa experience stagnation or decline in both efficiency and technological advancement. The decomposition analysis shows that innovation-oriented AI activities, such as patents and research investment, are strongly associated with frontier-shifting technological change, while adoption-oriented indicators, including robot density, contribute to efficiency improvements. Digital infrastructure emerges as a critical complementary factor influencing both channels of productivity growth. Overall, the findings indicate that AI adoption is reinforcing existing structural disparities within the BRICS bloc, creating a two-tier productivity hierarchy. The study contributes to the literature by providing a comparative, frontier-based assessment of AI-driven productivity in emerging economies and by distinguishing between innovation and diffusion effects of AI. Policy implications highlight the importance of strengthening digital infrastructure, human capital, and innovation capacity to ensure inclusive productivity gains from the AI revolution.