Artificial Intelligence, Institutional Governance, and Green Industrial Transformation: A Comparative Analysis of Indonesia’s Digital Manufacturing Transition and Malaysia’s Smart Industrial Ecosystem

Abstract

This article examines the relationship between institutional governance, artificial intelligence (AI)-driven industrial transformation, and sustainable economic development through a comparative analysis of Indonesia’s digital manufacturing transition and Malaysia’s smart industrial ecosystem. The study argues that the economic consequences of AI adoption in emerging economies are shaped not merely by technological capability, but by institutional coordination, industrial governance, regulatory coherence, financial systems, and sustainability-oriented policy frameworks. Drawing upon institutional economics, comparative business systems theory, and innovation governance literature, the article investigates how state capacity, industrial policy coordination, digital infrastructure, and corporate adaptation influence industrial competitiveness and socio-economic resilience. Using comparative institutional-economic analysis supported by data from BPS Statistics Indonesia, Bank Indonesia, OECD, IMF, World Bank, ASEAN industrial datasets, ESG governance reports, and productivity indicators, the findings reveal substantial divergence between Indonesia and Malaysia in industrial digitalization pathways. Indonesia demonstrates strong digital-market expansion and manufacturing digitization potential, particularly in labor-intensive sectors and MSME-linked production chains, yet continues to face institutional fragmentation, technological capability disparities, and uneven regional industrial readiness. Malaysia exhibits stronger technological governance integration, industrial automation capability, and sustainability-oriented industrial coordination, although industrial concentration and external technological dependence remain structural vulnerabilities. This article contributes to the literature by integrating AI governance, industrial transformation, and comparative business systems analysis within the Southeast Asian context. It proposes a conceptual model linking institutional capacity, AI-enabled innovation coordination, industrial adaptability, and sustainable economic resilience. The study further demonstrates that inclusive and sustainable AI-driven industrial transformation requires governance systems capable of balancing technological upgrading, labor adaptation, environmental sustainability, and long-term socio-economic competitiveness.