Analyzing the adoption of Artificial Intelligence in modern library services
a Technology Acceptance Model perspective
DOI:
https://doi.org/10.1590/1808-5245.32.148462Palabras clave:
artificial intelligence, modern library services, technology acceptance model, digital libraries, human-AI interactionResumen
The primary purpose of this research is to analyze the adoption of artificial intelligence in modern library services through the lens of the Technology Acceptance Model. The incorporation of Artificial Intelligence technologies into library operations has the prospect to revolutionize the pattern information is managed, retrieved, and conveyed to users. This methodology outlines a structured approach to qualitatively analyze existing literature on the adoption of Artificial Intelligence in modern library services through the Technology Acceptance Model perspective. By synthesizing findings from various studies, this research aims to provide valuable insights into the factors influencing Artificial Intelligence adoption and the application of Technology Acceptance Model in this context. This study investigates the adoption and acceptance of Artificial Intelligence-driven solutions in a contemporary library setting, utilizing the Technology Acceptance Model as a theoretical framework. The research explore the insights and attitudes of librarians, staff, and patrons in relation to Artificial Intelligence-support systems in libraries, with a special focus on perceived usefulness, perceived ease of use, behavioral intentions, and actual usage. The study also ruminate on regulating factors and external variables that may stimulate Artificial Intelligence adoption in the library environments. Through a broad analysis of Technology Acceptance Model factors in the context of Artificial Intelligence and library services, this research provides valuable insights for libraries looking to implement and enhance Artificial Intelligence technologies to better serve their communities. This study provides libraries with actionable insights and practical guidance for effectively integrating Artificial Intelligence technologies into their services, ultimately leading to enhanced efficiency, effectiveness, and user satisfaction. The originality of this research lies in its innovative application of the Technology Acceptance Model to the adoption of Artificial Intelligence in modern library services. By addressing a contemporary issue with a robust theoretical framework and providing empirical data, this study contributes valuable insights to both the academic community and practical field of library science. It stands out by exploring uncharted territories, addressing unique variables pertinent to Artificial Intelligence, and providing a holistic view of technology adoption in libraries.
Descargas
Citas
ABDUL RAHMAN, A. R.; MOHEZAR, S. Ensuring continued use of a digital library: a qualitative approach. The Electronic Library, Leeds, v. 38, n. 3, p. 513-530, 2020. Available at: https://doi.org/10.1108/EL-12-2019-0294. Access: Feb. 20th 2026.
ADETAYO, A. J. Artificial intelligence chatbots in academic libraries: the rise of ChatGPT. Library Hi Tech News, Leeds, v. 40, n. 3, p. 18-21, 2023a. Available at: https://doi.org/10.1108/LHTN-01-2023-0007. Access: Feb. 20th 2026.
ADETAYO, A. J. ChatGPT and librarians for reference consultations. Internet Reference Services Quarterly, London, v. 27, n. 3, p. 131-147, 2023b. Available at: https://doi.org/10.1080/10875301.2023.2203681. Access: Feb. 20th 2026.
AFFUM, M. Q.; DWOMOH, O. K. Investigating the potential impact of artificial intelligence in librarianship. Library Philosophy and Practice, Lincoln, p. 1-12, 2023.
AL-ADWAN, A. S. et al. Extending the technology acceptance model (TAM) to predict university students’ intentions to use metaverse-based learning platforms. Education and Information Technologies, New York, v. 28, p. 15381-15413, 2023. Available at: https://doi.org/10.1007/s10639-023-11816-3. Access: Feb. 20th 2026.
AL-AS’DI, A.; MILLER, D. Exploring the impact of artificial intelligence language model ChatGPT on the user experience. International Journal of Technology, Innovation and Management, Dubai, v. 3, n. 1, p. 1-8, 2023. Available at: https://doi.org/10.54489/ijtim.v3i1.195. Access: Feb. 20th 2026.
AMIN, M.; REZAEI, S.; ABOLGHASEMI, M. User satisfaction with mobile websites: the impact of perceived usefulness (PU), perceived ease of use (PEOU) and trust. Nankai Business Review International, Leeds, v. 5, n. 3, p. 258-274, 2014. Available at: https://doi.org/10.1108/NBRI-01-2014-0005. Access: Feb. 20th 2026.
BARSHA, S.; MUNSHI, S. A. Implementing artificial intelligence in library services: a review of current prospects and challenges of developing countries. Library Hi Tech News, Leeds, v. 41, n. 1, p. 7-10, 2024. Available at: https://doi.org/10.1108/LHTN-07-2023-0126. Access: Feb. 20th 2026.
BOGINA, V. et al. Educating software and AI stakeholders about algorithmic fairness, accountability, transparency and ethics. International Journal of Artificial Intelligence in Education, New York, v. 32, p. 808-833, 2022. Available at: https://doi.org/10.1007/s40593-021-00248-0. Access: Feb. 20th 2026.
BOZKURT, Z. Changing context of the workplace in the post-pandemic period: user-centric design and modern solutions. 2023. Tesi (Dottorato) - Scuola di Architettura Urbanistica Ingegneria delle Costruzioni, Milano, 2023.
CHAI, C. S. et al. Perceptions of and behavioral intentions towards learning artificial intelligence in primary school students. Educational Technology & Society, New Zealand, v. 24, n. 3, p. 89-101, 2021.
CHEN, Z. Artificial intelligence-virtual trainer: innovative didactics aimed at personalized training needs. Journal of the Knowledge Economy, New York, v. 14, n. 2, p. 2007-2025, 2023. Available at: https://doi.org/10.1007/s13132-022-00985-0. Access: Feb. 20th 2026.
EL RAYESS, M. A quick, accurate, and free-of-cost inventory and shelf-reading solution. Journal of Access Services, London, v. 12, n. 3-4, p. 104-117, 2015. Available at: https://doi.org/10.1080/15367967.2015.1096209. Access: Feb. 20th 2026.
ENHOLM, I. M. et al. Artificial intelligence and business value: a literature review. Information Systems Frontiers, New York, v. 24, p. 1709-1734, 2022. Available at: https://doi.org/10.1007/s10796-021-10186-w. Access: Feb. 20th 2026.
FERNANDEZ, P. Through the looking glass: envisioning new library technologies: understanding artificial intelligence. Library Hi Tech News, Leeds, v. 33, n. 3, p. 20-23, 2016. Available at: https://doi.org/10.1108/LHTN-03-2016-0013. Access: Feb. 20th 2026.
GRAZIA MELCHIONDA, M. Librarians in the age of the internet: their attitudes and roles: a literature review. New Library World, Leeds, v. 108, n. 3-4, p. 123-140, 2007. Available at: https://doi.org/10.1108/03074800710735339. Access: Feb. 20th 2026.
GUPTA, S. et al. Digital analytics: modeling for insights and new methods. Journal of Interactive Marketing, Amsterdam, v. 51, n. 1, p. 26-43, 2020. Available at: https://doi.org/10.1016/j.intmar.2020.04.003. Access: Feb. 20th 2026.
HIENERTH, C.; KEINZ, P.; LETTL, C. Exploring the nature and implementation process of user-centric business models. Long Range Planning, Amsterdam, v. 44, n. 5-6, p. 344-374, 2011. Available at: https://doi.org/10.1016/j.lrp.2011.09.009. Access: Feb. 20th 2026.
HONG, W. et al. Determinants of user acceptance of digital libraries: an empirical examination of individual differences and system characteristics. Journal of Management Information Systems, London, v. 18, n. 3, p. 97-124, 2002. Available at: https://doi.org/10.1080/07421222.2002.11045692. Access: Feb. 20th 2026.
HUSSAIN, A. Use of artificial intelligence in the library services: prospects and challenges. Library Hi Tech News, Leeds, v. 40, n. 2, p. 15-17, 2023. Available at: https://doi.org/10.1108/LHTN-11-2022-0125. Access: Feb. 20th 2026.
ISLAM, M. N.; ISLAM, M. M.; HOSSAIN, M. A. Exploring the role of public libraries in Bangladesh in the fourth industrial revolution era: readiness, challenges, and opportunities. Internet Reference Services Quarterly, London, v. 27, n. 4, p. 233-245, 2023. Available at: https://doi.org/10.1080/10875301.2023.2251470. Access: Feb. 20th 2026.
IZUAGBE, R. et al. Effect of perceived ease of use on librarians’ e-skills: basis for library technology acceptance intention. Library & Information Science Research, Amsterdam, v. 41, n. 3, art. 100969, p. 1-9, 2019. Available at: https://doi.org/10.1016/j.lisr.2019.100969. Access: Feb. 20th 2026.
IZUAGBE, R.; POPOOLA, S. O. Social influence and cognitive instrumental factors as facilitators of perceived usefulness of electronic resources among library personnel in private universities in South-west, Nigeria. Library Review, Leeds, v. 66, n. 8-9, p. 679-694, 2017. Available at: https://doi.org/10.1108/LR-09-2016-0086. Access: Feb. 20th 2026.
KATO, A.; KISANGIRI, M.; KAIJAGE, S. A review development of digital library resources at university level. Education Research International, New Jersey, v. 2021, p. 1-13, 2021. Available at: https://doi.org/10.1155/2021/8883483. Access: Feb. 20th 2026.
KELLY, S.; KAYE, S. A.; OVIEDO-TRESPALACIOS, O. What factors contribute to the acceptance of artificial intelligence? A systematic review. Telematics and Informatics, Amsterdam, v. 77, art. 101925, p. 1-33, 2023. Available at: https://doi.org/10.1016/j.tele.2022.101925. Access: Feb. 20th 2026.
KOMOSANY, N. B. A.; ALNWAIMI, G. R. Emerging technologies in academic libraries: artificial intelligence and big data. International Transaction Journal of Engineering, Management & Applied Sciences & Technologies, Thailand, v. 12, n. 4, p. 1-17, 2021. Available at: https://doi.org/10.14456/ITJEMAST.2021.74. Access: Feb. 20th 2026.
KUMAR, V.; RAJAN, B.; VENKATESAN, R.; LECINSKI, J. Understanding the role of artificial intelligence in personalized engagement marketing. California Management Review, Thousand Oaks, v. 61, n. 4, p. 135-155, 2019. Available at: https://doi.org/10.1177/0008125619859317. Access: Feb. 20th 2026.
LARCKER, D. F.; LESSIG, V. P. Perceived usefulness of information: a psychometric examination. Decision Sciences, New Jersey, v. 11, n. 1, p. 121-134, 1980. Available at: https://doi.org/10.1111/j.1540-5915.1980.tb01130.x. Access: Feb. 20th 2026.
LI, R. et al. AuRoSS: an autonomous robotic shelf scanning system. In: IEEE/RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS, 2015, Hamburg. Proceedings [...]. New York: IEEE, 2015. p. 6100-6105.
LINS, S. et al. Artificial intelligence as a service: classification and research directions. Business & Information Systems Engineering, New York, v. 63, p. 441-456, 2021. Available at: https://doi.org/10.1007/s12599-021-00708-w. Access: Feb. 20th 2026.
MIKALEF, P.; GUPTA, M. Artificial intelligence capability: conceptualization, measurement calibration, and empirical study on its impact on organizational creativity and firm performance. Information & Management, Amsterdam, v. 58, n. 3, art. 103434, p. 1-20, 2021. Available at: https://doi.org/10.1016/j.im.2021.103434. Access: Feb. 20th 2026.
MOHR, S.; KÜHL, R. Acceptance of artificial intelligence in German agriculture: an application of the technology acceptance model and the theory of planned behavior. Precision Agriculture, New York, v. 22, n. 6, p. 1816-1844, 2021. Available at: https://doi.org/10.1007/s11119-021-09814-x. Access: Feb. 20th 2026.
MORRAR, R.; ARMAN, H.; MOUSA, S. The fourth industrial revolution (Industry 4.0): a social innovation perspective. Technology Innovation Management Review, Ottawa, v. 7, n. 11, p. 12-20, 2017. Available at: https://doi.org/10.22215/timreview/1117. Access: Feb. 20th 2026.
OKUNLAYA, R. O.; SYED ABDULLAH, N.; ALIAS, R. A. Artificial intelligence (AI) library services innovative conceptual framework for the digital transformation of university education. Library Hi Tech, Leeds, v. 40, n. 6, p. 1869-1892, 2022. Available at: https://doi.org/10.1108/LHT-07-2021-0242. Access: Feb. 20th 2026.
ONGSULEE, P. Artificial intelligence, machine learning and deep learning. In: INTERNATIONAL CONFERENCE ON ICT AND KNOWLEDGE ENGINEERING, 15., 2017. Proceedings [...]. New York: IEEE, 2017. p. 1-6.
PANDA, S.; CHAKRAVARTY, R. Adapting intelligent information services in libraries: A case of smart AI chatbots. Library Hi Tech News, Leeds, v. 39, n. 1, p. 12-15, 2022. Available at: https://doi.org/10.1108/LHTN-11-2021-0081. Access: Feb. 20th 2026.
PIERRE-ROBERTSON, P. #SuperLibrarian - the evolving role of librarians in technology spaces. Digital Library Perspectives, Leeds, v. 39, n. 4, p. 620-627, 2023. Available at: https://doi.org/10.1108/DLP-04-2023-0026. Access: Feb. 20th 2026.
RAFI, M.; JIAN MING, Z.; AHMAD, K. Estimation of the knowledge management model for performance measurement in university libraries. Library Hi Tech, Leeds, v. 40, n. 1, p. 239-264, 2022. Available at: https://doi.org/10.1108/LHT-11-2019-0225. Access: Feb. 20th 2026.
SADRIWALA, M. F.; SADRIWALA, K. F. Perceived usefulness and ease of use of artificial intelligence on marketing innovation. International Journal of Innovation in the Digital Economy, Hershey, v. 13, n. 1, p. 1-10, 2022. Available at: https://doi.org/10.4018/IJIDE.292010. Access: Feb. 20th 2026.
SCHWITZGEBEL, E. AI systems must not confuse users about their sentience or moral status. Patterns, Amsterdam, v. 4, n. 8, p. 1-4, 2023. Available at: https://doi.org/10.1016/j.patter.2023.100818. Access: Feb. 20th 2026.
SHAHEEN, M. A.; KHURSHID, A. Perceptions and experiences of artificial intelligence (AI) use in libraries: a study of library users in Pakistan. Library Philosophy and Practice, Lincoln, n. 7905, p. 1-13, 2023.
SILVA, P. Davis’ technology acceptance model (TAM) (1989). In: AL-SUQRI, Mohammed Nasser; AL-AUFI, Ali Saif (ed.). Information seeking behavior and technology adoption: theories and trends. Hershey: IGI Global Scientific, 2015. p. 205-219.
SINGAMANENI, K. K. et al. An enhanced dynamic nonlinear polynomial integrity-based QHCP-ABE framework for big data privacy and security. Security and Communication Networks, New Jersey, p. 1-13, 2022. Available at: https://doi.org/10.1155/2022/4206000. Access: Feb. 20th 2026.
SLATER, R. Why aren’t e-books gaining more ground in academic libraries? E-book use and perceptions: a review of published literature and research. Journal of Web Librarianship, London, v. 4, n. 4, p. 305-331, 2010. Available at: https://doi.org/10.1080/19322909.2010.525419. Access: Feb. 20th 2026.
SUBAVEERAPANDIYAN, A. Application of artificial intelligence (AI) in libraries and its impact on library operations review. Library Philosophy and Practice, Lincoln, n. 7828, p. 1-19, 2023.
SUKI, N. M.; SUKI, N. M. Exploring the relationship between perceived usefulness, perceived ease of use, perceived enjoyment, attitude and subscribers’ intention towards using 3G mobile services. Journal of Information Technology Management, Baltimore, v. 22, n. 1, p. 1-7, 2011.
TSAI, T. H.; LIN, W. Y.; CHANG, Y. S.; CHANG, P. C.; LEE, M. Y. Technology anxiety and resistance to change behavioral study of a wearable cardiac warming system using an extended TAM for older adults. PLoS ONE, San Francisco, v. 15, n. 1, p. 1-24, 2020. Available at: https://doi.org/10.1371/journal.pone.0227270. Access: Feb. 20th 2026.
USMAN, O.; SEPTIANTI, A.; SUSITA, M.; MARSOFIYATI, M. The effect of computer self-efficacy and subjective norm on the perceived usefulness, perceived ease of use and behavioural intention to use technology. Journal of Southeast Asian Research, Pennsylvania, v. 2020, p. 1-11, 2020. Available at: https://doi.org/10.5171/2020.753259. Access: Feb. 20th 2026.
WANG, C. et al. An empirical evaluation of technology acceptance model for artificial intelligence in e-commerce. Heliyon, Amsterdam, v. 9, n. 8, p. 1-20, 2023. Available at: https://doi.org/10.1016/j.heliyon.2023.e18349. Access: Feb. 20th 2026.
WANG, T. et al. Exploring the potential impact of artificial intelligence (AI) on international students in higher education: generative AI, chatbots, analytics, and international student success. Applied Sciences, Basel, v. 13, n. 11, p. 6716, 2023. Available at: https://doi.org/10.3390/app13116716. Access: Feb. 20th 2026.
XU, M.; DAVID, J. M.; KIM, S. H. The fourth industrial revolution: opportunities and challenges. International Journal of Financial Research, Ontario, v. 9, n. 2, p. 90-95, 2018. Available at: https://doi.org/10.5430/ijfr.v9n2p90. Access: Feb. 20th 2026.
Publicado
Cómo citar
Número
Sección
Licencia
Derechos de autor 2025 Oluwole Olumide Durodolu, Ganiyu Ojo Adigun
Esta obra está bajo una licencia internacional Creative Commons Atribución 4.0.
Autores que publican en esta revista están de acuerdo con los siguientes términos:
Los autores mantienen los derechos autorales y ceden a la Revista el derecho de la primera publicación, con el trabajo licenciado bajo la Licencia Creative Commons Attribution (CC BY 4.0), que admite compartir el trabajo con reconocimiento de la autoria.
Los autores tienen autorización para asumir contratos adicionales en forma separada, para la distribución no exclusiva de la versión del trabajo publicada en esta Revista, como para publicar en repositorio institucional, con reconocimiento de autoria y publicación inicial en esta Revista.
Los artículos son de acceso abierto y gratuitos. Según la licencia, usted debe dar crédito de manera adecuada, brindar un enlace a la licencia, e indicar si se han realizado cambios. No puede aplicar términos legales ni medidas tecnológicas que restrinjan legalmente a otras a hacer cualquier uso permitido por la licencia.
