Leveraging AI for ESG Performance: A Global Analysis of National AI Capabilities and Sustainability in International Business

This study examines the interplay between national AI capabilities, measured by the Oxford (161 countries), Tortoise (81 countries), and Stanford (36 countries) AI Indices, and Environmental, Social, and Governance (ESG) performance, advancing international business (IB) and sustainability scholarship. We propose AI-enabled ESG capability—a country-level construct integrating AI resources within institutional contexts—as a novel framework, synthesizing Resource-Based View, Institutional Theory, and Knowledge-Based View to address tensions between regulatory pressures and technological advantages. Employing Pearson correlation, hierarchical regression, and K-means clustering, we analyze AI pillars' influence on ESG, controlling for political stability, GDP per capita, internet penetration, and population size. Findings highlight Data and Infrastructure (Oxford, R² = 0.916), Talent (Tortoise, R² = 0.936), and Political Stability (Stanford, R² = 0.850) as primary drivers, with stronger effects in developed economies. Clustering reveals trade-offs: AI-dominant nations lag in ESG, while ESG-strong countries underutilize AI. These insights extend IB theories and guide multinational enterprises (MNEs) and policymakers in aligning AI with ESG through robust governance, digital infrastructure, and STEM education, fostering sustainable global value chains.