Forecasting Ghanaian Medical Library Users’ Artificial Intelligence (AI) Technology’s Acceptance and Use

Abstract

Objective. This study investigated the behavioural intentions of medical students in an academic library regarding the use of AI-assisted technologies for research and learning. Method. Employing a survey research design and a quantitative approach, the study sampled 302 respondents using Krejcie and Morgan’s published table. Statistical analyses were conducted using the Statistical Package for Social Sciences (SPSS) version 26, with linear and multiple linear regressions utilised to establish relationships between variables. Results. The results of the study indicate that perceived usefulness, perceived ease of use, and self-efficacy within the extended Technology Acceptance Model (TAM) significantly influence the behavioural intention to utilise AI in an academic library in Ghana. Additionally, the results suggest that perceived usefulness plays a more significant role in influencing behavioural intention compared to perceived ease of use. Furthermore, the study reveals a direct relationship between behavioural intention and use behaviour within TAM. Conclusion. This study underscores the critical factors within the extended Technology Acceptance Model that drive the adoption of AI in academic libraries in Ghana. The results highlight the paramount importance of perceived usefulness in shaping behavioural intention, surpassing the impact of perceived ease of use. Moreover, the direct link between behavioural intention and actual use behaviour reaffirms the model’s applicability in predicting technology adoption. These insights provide a valuable foundation for developing strategies to enhance AI integration in academic libraries, ultimately improving their operational efficiency and service delivery.

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