IN DEPTH ‘‘


Beth Montague-Hellen is Head of Library and Infor- mation Services at the Sir Francis Crick Institute.


AI has a tendency to make everything more extreme. It can make some things much easier and much faster, but it rarely fixes our most persistent problems.


Academic publisher AI tools – a librarian’s view


AI research tools are being sold by academic publishers direct to researchers. What could this mean for research quality, open access and libraries themselves? Beth Montague-Hellen, former genetics post-doc researcher and now head of library and information services at the Sir Francis Crick Institute takes a look.


EVERYWHERE you look today, someone is talking about AI. Vendors are weaving it into services we’ve been using for years, charg- ing extra for it, and telling us that students and businesses are already using AI for everything, so we might as well get on board. Of course, as librarians we know that it’s not always as simple as just “getting on board”. AI has a tendency to make everything more extreme. It can make some things much easier and much faster, but it rarely fixes our most persistent problems. Instead, it often amplifies them. Added to that are the well-documented ecological and ethical concerns that sit uncomfortably alongside the hype.


General AI versus publisher AI


One area where AI has a particularly strong impact on academic librarianship is journals and resource discovery. The perils of using general-purpose large language models, ChatGPT, Claude, and the like, to search for articles and books are now well known. Made-up references, hallucinated citations, and entirely fictional “top 10” reading lists have become familiar territory. But what about the tools designed to be a step up from this: platforms specifically designed for searching and navigating the scholarly literature? These tools are less prone to outright hallu- cination, but that doesn’t mean they are problem-free. There have always been layers, middle-men, sitting between researchers and students, and the journal content they want to access. Sometimes this layer is


26 INFORMATION PROFESSIONAL


a discovery platform with resources carefully selected and configured by academic librarians. Sometimes it takes the form of external databases or search tools such as Scopus, Web of Science, or Google Schol- ar. Increasingly, that middle layer is some form of AI. Over the last couple of years, as AI has become embedded in everyday life, librarians have found that not only are new AI-driven discovery platforms appearing, but long-standing services are also add- ing AI functionality. Google Scholar now has Labs, Dimensions has its own Research GPT, and Elsevier, the owner of Scopus, has introduced LeapSpace. On the surface, these are simply new ways of finding information. Dig a little deeper, though, and a host of headaches for librarians quickly emerges.


LeapSpace


I’ve been doing some of that digging recently to see whether any of these tools live up to the hype, most recently through a trial of LeapSpace, Elsevier’s AI dis- covery platform. The positives are easy to see. Creating a good search strategy is difficult and time-consuming. Using LeapSpace, a simple natural-language ques- tion not only returns answers but also generates the corresponding Boolean search for Scopus. It provides a range of additional material: easy-to-read bullet-point summaries, citation analysis indicating whether a paper is broadly supportive, mixed, or negative, and confidence analysis showing how aligned the literature appears to be. The time savings, and the easier access to dense and technical literature, are obvious benefits.


April-May 2026


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