The Economic Value of Agentic AI: A Comparative Analysis of Its Impact on Growth and Business Productivity in Developed and Emerging Economies

Agentic AI has strong potential to boost productivity and growth, but current evidence suggests it is more likely reinforcing existing core–periphery inequalities than fundamentally reshaping the global economic order, due to uneven access, capabilities, and institutional readiness across countries. This study examines the economic value of Agentic Artificial Intelligence (AI), defined as advanced AI systems capable of autonomous decision-making and task execution, by analysing its impact on firm-level productivity, financial performance, and macroeconomic growth across developed and emerging economies. While existing literature has extensively examined general AI adoption, limited empirical evidence exists on how more autonomous, agent-like systems contribute to economic outcomes and whether their benefits are evenly distributed across different economic contexts. To address this gap, the study employs a quantitative panel data approach using data from the World Bank (World Development Indicators and Enterprise Surveys) and OECD AI indicators for the period 2015 to 2024. An AI Adoption Index is constructed using indicators of AI investment, business adoption, and innovation output, serving as a proxy for the diffusion of advanced AI capabilities, including agentic features. Fixed effects regression, mediation analysis, and quantile regression are used to estimate firm-level and macroeconomic relationships. The results show that AI adoption significantly improves firm-level productivity (β = 0.18, p < 0.01) and influences economic growth primarily through a productivity channel (β = 0.35, p < 0.01), with a comparatively weaker direct effect (β = 0.09). However, the magnitude of these effects varies across economic contexts, with developed economies experiencing substantially stronger growth impacts (approximately 0.33) than emerging economies (approximately 0.15). These findings suggest that while Agentic AI enhances economic performance, its benefits are mediated by structural conditions and are unevenly distributed across countries. The study contributes to the literature by providing an integrated micro to macro empirical framework and highlighting the role of advanced AI capabilities in reinforcing global economic disparities. Policy recommendations emphasise the need for investment in digital infrastructure, human capital development, and inclusive technology diffusion strategies to ensure more equitable distribution of AI-driven economic value.