Artificial intelligence and international business: Theoretical challenges, strategic implications, and research agenda

This perspective article explores how artificial intelligence (AI) is reshaping the theoretical foundations and strategic dynamics of international business (IB). We distinguish between predictive AI, generative AI, and agentic AI, examining how each transforms the behavior of multinational enterprises (MNEs). Moving beyond viewing AI as merely transactional or infrastructural technology, we conceptualize it as a cognitive substrate that transforms how MNEs learn, innovate, develop resources and capabilities, and make decisions across borders. By augmenting and partially substituting managerial cognition, AI reconfigures firm-specific and location-specific advantages, while challenging core assumptions of established IB frameworks and altering the governance of cross-border activities. AI also transforms global value chains through enhanced coordination, resilience, and transparency, yet it simultaneously introduces new risks related to algorithmic bias, sustainability, and dependency on digital infrastructures. The paper discusses the implications of AI adoption for MNEs and argues that existing IB theories may need to be complemented by new perspectives to account for AI disruption. The paper concludes by proposing a research agenda that integrates theoretical, strategic, institutional, and methodological insights for understanding AI’s transformative impact on IB.