Pressures, politics, possibilities: how AI might transform the research ecosystem

Abstract

This paper aims to examine how the growing adoption of artificial intelligence (AI) tools in research might transform the wider research ecosystem. Three plausible scenarios are discussed with major implications for the future role of universities and publishers, individual skill requirements, career development, and power relations between Global North and Global South. The paper focuses on the interplay of technology affordances, industry dynamics, practice shifts and strategic moves by powerful actors to explain variations of how and how much AI might transform the research ecosystem. The paper argues that while AI has a “democratizing effect” in making research tasks less costly and more convenient for scholars worldwide, it simultaneously increases skill requirements, efficiency pressures and thresholds for what counts as valuable data and knowledge. Investments by powerful institutions and corporations, particularly in the USA, Western Europe and China, reinforce and exploit these dynamics, leading to three plausible future scenarios: a higher-pressure version of today’s system, augmented by AI and dominated by resource-rich universities; a more distributed system driven by co-specialized clients and providers of proprietary data and knowledge services; and a platform-based system of semi-automated knowledge production dominated by big tech firms. While most studies focus on technicalities of AI use in research, this paper shifts focus to the wider research ecosystem and the role powerful actors might play in driving these changes. It also discusses how increasing AI adoption may promote a shift from individual authorship and peer-to-peer exchange to more demand-driven, AI-based knowledge production and dissemination.