Abstract
This paper develops a new theoretical framework titled Digital Developmentalism, which explains how governments in the age of artificial intelligence (AI) and data-driven technologies are reshaping the mechanisms of economic growth and structural transformation. Integrating insights from developmental state theory, institutional economics, and general-purpose technology (GPT) theory, the study conceptualizes AI not merely as a technological innovation but as a transformative governance capability. The framework positions the state as a computational orchestrator, leveraging algorithmic coordination, data infrastructures, and public–private digital ecosystems to guide innovation and policy learning. Four key mechanisms underpin digital developmentalism: (1) algorithmic coordination, (2) data as developmental infrastructure, (3) AI-enhanced policy feedback, and (4) public–private digital synergy. Together, these mechanisms explain how AI governance capacity enables governments to manage complexity, enhance productivity, and foster inclusive development. The study also explores ethical and political challenges such as algorithmic opacity, surveillance, and inequality, emphasizing the need for transparent, accountable, and human-centered AI governance. By uniting governance theory and GPT theory into a single conceptual model, this paper contributes to the emerging discourse on how digital technologies redefine state capacity and the future of development. It concludes by proposing pathways for empirical testing and comparative research on AI-driven governance and economic performance across different national contexts.