Perspectives of academic librarians on ethical challenges of AI-based bibliometric tools: a grounded theory study

Purpose The increasing use of artificial intelligence (AI)-based bibliometric tools in academic libraries raises significant ethical concerns. Existing research has largely overlooked how librarians, particularly in the Global South, experience and address these issues in practice. This study aims to investigate the perspectives and strategies of academic librarians in Nigerian federal universities, aiming to develop a grounded theoretical model that explains their approaches to balancing technological benefits with ethical responsibilities in research evaluation. Design/methodology/approach Classic grounded theory was used to guide semi-structured interviews with 18 participants (13 research support librarians and five research office staff) from six Nigerian federal universities. Interviews were conducted via Zoom between 6 January and 3 February 2025 and analysed using iterative open, axial and selective coding. Findings A core category, Balancing Accuracy with Accountability, emerged to explain how librarians reconcile the benefits of AI-powered bibliometric tools with ethical concerns. Four interrelated subcategories support this core concern: bias detection, transparency demands, consent and data ownership and trust-building practices. Together, these form the basis of the proposed mid-range theory of Contextual Accountability in Ethical AI Adoption, which emphasises librarians’ active role in shaping ethical AI integration based on institutional context, professional values and local constraints. Originality/value To the best of the author’s knowledge, this study is among the first to develop a grounded theory of ethical AI adoption in bibliometrics from the perspective of academic librarians in a Global South context. It contributes original insights into how librarians mediate the ethical implications of AI tools and offers a context-sensitive theoretical model that can inform institutional policy, tool design and professional development. The study challenges universalist assumptions about AI ethics by centring the situated knowledge and agency of librarians working in underrepresented regions.