From policy framing to platform routines: AI-integrated curriculum reform in higher vocational education

Introduction AI-enabled curriculum reform has become an important issue in higher education, but strong policy incentives and rapid platform expansion do not automatically produce employability-oriented curriculum responsiveness. This study conceptualizes AI-enabled curriculum reform as a platform-mediated governance process and uses actor-network theory, especially Callon's sociology of translation, to examine how employability-oriented reform objectives are translated through problematization, interessement, enrollment, mobilization, and provisional stabilization. Methods Based on an interpretive multiple-case study of Chinese higher vocational colleges, the analysis draws on policy and institutional documents, platform-related artifacts, and interviews with college administrators, teachers, students, and industry employers. Results The findings show that policy authorities frame AI-enabled curriculum reform as a governance problem, while colleges use AI learning platforms to coordinate actors through performance indicators, standards, infrastructure, and evidence of reform implementation. Teachers and students enact reform through routine platform use, and mobilization occurs through course delivery, knowledge bases, learning analytics, dashboards, and industry-education data interfaces. The study identifies emerging and projected conditions for provisional stabilization, rather than completed institutionalization. Discussion AI-supported routines may become normalized through repeated use and evaluation but remain dependent on governance capacity, platform maturity, teachers' engagement, and sustained policy support.