This project explores how artificial intelligence (AI) is transforming academic knowledge production within the broader context of shifts in the global economy and digital governance. As AI systems become increasingly integrated into research workflows—from literature reviews and proofreading to coding and data analysis—they are redefining how knowledge is generated, validated and disseminated.
AI infrastructures are not neutral. They actively shape academic productivity, labour and practice, often reinforcing or exacerbating existing hierarchies related to access to resources, academic disciplines, and institutional prestige. This comparative study examines how varying models of AI governance in the EU, China, the US, and Canada structure the conditions under which academic work is performed. Particular attention is given to how competing visions and strategies of digital sovereignty, privacy, and control influence the politics and possibilities of academic knowledge production.
To understand both policy-level logics and everyday academic practices, this research employs a range of qualitative methods, including document analysis, expert interviews, focus group discussions, and digital ethnography. It aims to understand how researchers and different stakeholders at several leading research organizations across these four regions perceive and navigate the ongoing AI transformation. In particular, it focuses on three interrelated domains: data management, AI applications in research, and research policy frameworks. By critically analyzing AI as a site of epistemic, economic, and political contestation, the project contributes to debates on digital sovereignty, epistemic justice, and the future of research.