Implications of artificial intelligence for academics' work: a sociotechnical perspective based on podcast episodes

Purpose The increasing adoption and use of artificial intelligence (AI) is transforming how academics perform core activities, ranging from research to teaching and academic services. This paper empirically examines this phenomenon and its implications through a sociotechnical systems lens, analyzing changes in core activities and the multilevel factors that shape them. Design/methodology/approach This study adopts a qualitative design, employing a Podcast analysis. Based on 66 publicly available podcast episodes, we explore changes in academic knowledge work and examine the factors shaping them. Findings The findings show that the use of AI is changing academic work in ways that go beyond altering day-to-day activities. By interpreting the results with sociotechnical systems theory, this research identifies factors and emerging tensions at the individual, technology, organization and societal levels that together shape how AI changes academia. Originality/value Analyzing these sociotechnical factors, we introduce the academic AI-transformation framework (AAITF), offering a novel lens for understanding the consequences of AI for academics. Building on existing research, this study goes beyond the focus on single activities or levels of analysis, offering a more holistic understanding of how academic work is changing with AI.