Governing AI-driven industry-education integration: A cross-national systematic review of China, Germany, and the United States

Abstract

Against the backdrop of the Fourth Industrial Revolution and the rapid iteration of generative AI, industry-education integration (IEI) is undergoing a profound paradigm transformation. This study systematically reviews academic literature on AI-driven IEI published between 2018 and 2025 across China, Germany, and the United States, constructing a tripartite analytical framework of "state guidance social coordination market drive." Following the PRISMA 2020 statement, we searched Web of Science, Scopus, CNKI, ERIC, and IEEE Xplore, supplemented by OECD, UNESCO, and WEF policy documents. From an initial pool of 2,847 records, 186 core studies were included after deduplication, title-abstract screening, full-text review, and MMAT quality assessment (inter-rater Kappa = 0.87). Findings reveal that AI-driven IEI exhibits significant "techno-political embeddedness" the same technology is assigned divergent functional roles across different institutional environments. China deploys AI as a state governance instrument; Germany treats it as a subject of social negotiation; the United States positions it as a vehicle for capital appreciation. Despite these divergences, all three models are converging toward "hybrid governance." Varieties of Capitalism (VoC) theory and National Innovation Systems (NIS) theory provide effective explanatory frameworks for understanding cross-national variation. Future governance of IEI is likely to move toward a dynamic balance among state guidance, social coordination, and market mechanisms, with AI literacy and ethical norms emerging as central concerns.