The Observatory's institutional research library brings together reports, policy and research papers, external publication summaries, and downloadable outputs.
China is becoming an important test case for what comes after AI adoption: how companies redesign processes, develop people and build workforce systems around the technology. The article examines signals from Chinese enterprises, career development research and China’s emerging employment policy response to AI-driven workforce transformation.
AI workforce transformation is moving beyond tool adoption. This policy brief explains why enterprises need workforce architecture — integrating strategy, workflows, roles, capabilities, governance, and trust — to scale responsible, human-centered AI adoption
As AI adoption accelerates across sectors, the central challenge is no longer access to tools but the ability of institutions to redesign workflows, governance, and workforce systems around them. This flagship brief from the Global AI Governance and Workforce Transformation Policy Observatory examines why many organizations remain trapped in fragmented experimentation and outlines a practical framework for moving toward governed, scalable implementation.
A flagship policy brief arguing that AI education, assessment, governance, and workforce transformation should not be treated as separate debates, but as one institutional transition sequence connecting classrooms, learning systems, and the future of work.
China’s AI education transition illustrates a broader global shift: the central challenge is no longer whether schools can access AI tools, but whether education systems can redesign institutions fast enough to use them well. This brief examines how assessment pressure, teacher readiness, governance capacity, and uneven implementation shape China’s AI education pathway. By connecting China’s case with comparative insights from five countries, it argues that meaningful AI adoption requires moving beyond pilots and technology enthusiasm toward institutional change, evidence systems, and human-centered implementation.
