Artificial Intelligence For Economic Growth and Development
Abstract
The rapid diffusion of artificial intelligence (AI) across industries and national economies has brought renewed scholarly attention to the impact of technological innovation on economic growth. This paper provides a systematic narrative review of the peer-reviewed empirical and theoretical literature on how-adoption of AI leads to growth at macroeconomic scale contributions to human development across key sectors, and the structural challenges that condition these distributional effects. Based on a SPAR-4-SLR protocol, 47 studies from the Scopus, Web of Science, EconLit and Google Scholar databases were identified, and results show that AI mainly affects economic growth via TFP increase, innovation speed-up, labour market transformation and financial sector extension. As a result, AI shows documented promise in agriculture, health, education and governance at the development level but the evidence base remains patchy across LMIC contexts. There are still deeper structural risks that remain, such as labour displacement, infrastructure gaps and inequality(both across and within economies), algorithmic bias and the concentration of AI economic rents in advanced economies. This paper makes two important contributions: it advances a unified cross-disciplinary conceptual framework, which is considered appropriate to policy contexts in both developed and developing economies; and identifies priority areas for further causal empirical research.
