Purpose This column aims to examine how advances in artificial intelligence (AI) raise the salience of thinking about patron data. It explores how AI’s scale, low cost and capacity to aggregate and cross-reference data from diverse sources impact vendor relations and library-housed patron information. Design/methodology/approach This is a viewpoint column that synthesizes recent research and reporting. It was copy-edited with Claude Sonnet 5, Claude Opus 5, ChatGPT Sol 5.6, Gemini 3.1 Pro and Gemma 4. Findings AI lowers the cost and raises the scale of cyberattacks. The column recommends libraries prepare for a world where synthetic impersonation and data breaches are increasingly common. It notes that even modest amounts of retained data can carry meaningful risk. Vendor data-sharing practices are highlighted. Libraries already possess considerable collaborative infrastructure that can be applied to conducting private data inventories, mitigating risk and planning for worst case scenarios. Originality/value This column underscores the need to apply libraries’ rich tradition of privacy tools to pro-active preparation for a world where AI changes how data works online.
Purpose This paper aims to address the problem of chronically understaffed academic libraries, using Ghanaian Colleges of Education as the case, and develops a practical framework for using low-code and no-code workflow automation to lift routine work without new hires. Design/methodology/approach The framework is developed through a conceptual synthesis of the general automation, library-practice and African library-technology literatures, adapted to the resource-constrained College of Education setting. Findings The paper sets out a four-stage framework – identify suitable workflows, select a tool, build along a maturity model, and govern the result – supported by a task taxonomy, an impact-and-effort prioritisation method, a tool-selection guide, a maturity model, and explicit boundary conditions for when not to automate. Originality/value Existing work is either not about libraries, code-heavy, tied to costly subscription platforms, or frames automation as expensive artificial intelligence. To the best of the authors’ knowledge, this is the first framework to treat low-code workflow automation as a deliberate, affordable strategy for the understaffed, resource-constrained academic library, built on self-hostable tools and within reach of a single capable librarian.
Purpose This paper aims to examine library technology initiatives that underperformed on first deployment and traces how library staff diagnosed and redesigned them. It argues that the redesign phase, rather than the launch phase, is where the more transferable practitioner lessons reside. Design/methodology/approach Five technology initiatives from three Indonesian public library agencies are examined, drawing on field research conducted between 2020 and 2023 and on institutional documentation published between 2024 and 2026. Findings Four recurring diagnostic patterns emerged: infrastructure assumptions that did not match user conditions; provision without programming; instruments that could not measure their own use; and announced features that never shipped. In each sustained case, the corrective action addressed service design rather than technology specification. Originality/value Published library technology case studies overwhelmingly report successes. This paper reports first-attempt shortfalls and the specific diagnostic reasoning that followed, offering practitioners a set of failure signatures they can recognise in their own services.
Purpose The purpose of the paper is to highlight that while they may be in a hurry to feed the growing giant of AI, they must also thoughtfully consider the consequences. The black-box nature of AI raises concerns about transparency and trust and as long as they do not fully understand how AI reaches its conclusions, questions about the reliability of AI-driven decision-making will continue. Design/methodology/approach A qualitative secondary research approach, using content analysis of evidence collected from newspapers, research papers and recent books to critically compare AI-driven and traditional approaches to knowledge and decision-making. Findings The findings reveal that AI-driven decisions cannot be trusted blindly, as they may reinforce existing vulnerabilities and discrimination in society. Therefore, AI must be used mindfully, with continuous human oversight, transparency and accountability, to reduce rather than exacerbate disorder and inequality in the information society, while building public trust instead of creating fear. Originality/value The paper is original, offering a critical perspective on AI-driven decision-making, trust and the need for mindful human oversight in the information society.
Purpose The purpose of this paper is to examine how libraries can leverage artificial intelligence (AI) to improve access to information, enhance service delivery and remain relevant in an increasingly digital and data-driven world. Design/methodology/approach This study adopts a qualitative and descriptive approach based on a review of existing literature, recent developments in AI and current practices in library and information science. Relevant scholarly articles, reports from professional organisations, policy documents and case studies of AI applications in libraries were examined to identify emerging trends and best practices. Findings This study finds that AI can significantly enhance library services by improving information discovery, automating routine tasks and providing personalised user support. AI enables libraries to offer seamless, anytime-anywhere access to resources while allowing librarians to focus on knowledge curation and user engagement. However, its successful adoption requires attention to ethical, technical and privacy considerations. Overall, AI strengthens the role of libraries as modern, user-centred knowledge hubs. Originality/value This study highlights the evolving role of AI in libraries and demonstrates how it can enhance access to information, improve services and support the future of user-centred librarianship.
