Artificial intelligence in Greek libraries: Perceptions, challenges, and readiness for adoption
This study examines how Greek librarians understand, engage with, and perceive Artificial Intelligence (AI) technologies. Using a cross-sectional online survey, data were collected on AI-related knowledge and familiarity, personal and professional use, perceived impact across operational domains, challenges to adoption, institutional and individual readiness, and the provision of AI literacy instruction. Respondents reported moderate to good overall understanding, with higher familiarity and use in personal contexts than in workplace settings. Common personal applications included text generation, editing, translation, and information seeking, while professional use focussed on assisting user queries, suggesting search terms, plagiarism detection, and developing instructional materials. Adoption of chatbots and AI-supported cataloguing remained limited. Perceived impact was strongest in areas related to user and staff training, as well as frontline services. Most challenges were rated above the midpoint—particularly infrastructure limitations, funding constraints, staff training needs, and ethical or legal concerns—while fear of job loss was relatively low. AI literacy instruction was infrequent across institutions. Comparisons by library type revealed no significant differences in perceived impact or challenges, though small but significant differences emerged in readiness and professional use. Based on these findings, the authors propose targeted actions to support the successful integration of AI in library services.
Authors
- Ασπασία Τόγια (ORCID: https://orcid.org/0000-0002-6228-7356)
- Nikolaos Tsigilis
- Eleftheria Koseoglou
Institutions
- International Hellenic University (GR)
- United Arab Emirates University (AE)
- Aristotle University of Thessaloniki (GR)
Publication Details
- Journal
- Journal of Librarianship and Information Science
- Published
- 2026-02-02
- DOI
- https://doi.org/10.1177/09610006251410240
- Primary Topic
- Artificial Intelligence in Healthcare and Education
- Type
- article
- Field-Weighted Citation Impact
- 0.00