Factors Influencing Researchers' Adoption of AI-Powered Digital Library Services for Sustainable Academic Research Productivity: A Conceptual Review

Abstract

Academic digital libraries are no longer limited to databases, catalogues and electronic collections. In many universities, they now include intelligent search, recommendation tools, chatbots, analytics, mobile access, repositories and preservation systems. These services can help researchers find literature more quickly, manage information more confidently and make institutional research outputs more visible. Yet researchers do not adopt such services simply because a university has introduced them. Their use depends on whether the services are useful, easy to access, trustworthy, well supported and clearly connected to research work. This conceptual review examines the factors that influence researchers' adoption of AI-powered digital library services and considers how such adoption may support sustainable academic research productivity. The paper draws only on a delimited set of studies on smart digital libraries, artificial intelligence in academic libraries, electronic resources, user satisfaction, digital preservation, mobile libraries, institutional support and scholarly communication. The synthesis identifies five central adoption factors: AI service quality and personalization; ease of use, accessibility and mobile access; AI readiness and information literacy; institutional support, infrastructure and policy; and trust, privacy, ethics and transparency. It also explains five productivity pathways: access, discovery, workflow, collaboration and visibility. The paper argues that AI-powered digital libraries should be treated as research infrastructure rather than as isolated technical projects. Their value depends on the combined strength of technology, librarians' expertise, user skills, ethical governance and long-term institutional commitment.