Readiness of Administrative Staff to Adopt Artificial Intelligence in Healthcare Management at Al-Zulfi General Hospital
DOI:
https://doi.org/10.56830/WRBA10202603Keywords:
Administrative Staff, Artificial Intelligence, Healthcare ManagementAbstract
The current study aimed to identify the readiness of administrative staff to adopt artificial intelligence in healthcare management at Al-Zulfi General Hospital, using a descriptive-analytical approach. The research sample consisted of the entire study population of (57) administrative staff members at Al-Zulfi General Hospital, selected through a comprehensive survey. A questionnaire prepared by the researcher was applied, consisting of four axes (knowledge and dealing with data, organizational support and professional environment, language barriers, and psychological attitudes skills) with a total of (28) statements. The results of the study showed that the readiness of the administrative staff to adopt artificial intelligence in the health administration at Al-Zulfi General Hospital was high for the axis of knowledge and dealing with data, and moderate for the axis of organizational support and professional environment, and the axis of language barriers, while the axis of psychological attitudes received a high score. The results also showed that there were no statistically significant differences at the significance level between the average degree of readiness of administrative staff to adopt artificial intelligence in health management at Al-Zulfi General Hospital attributable to the variable (gender, age, job title, years of experience, academic qualification). Considering the study’s findings, a set of recommendations was presented, including Continuously encouraging administrative staff to adopt artificial intelligence in health management to improve medical work at all levels.
References
Alowais, S. A., Alghamdi, S., Alsuhebany, N., Alqahtani, T., Alshaya, A., Almohareb, S. N., Aldairem, A., Alrashed, M., Bin Saleh, K., Badreldin, H., Al Yami, M. S., Al Harbi, S., & AlBkairi, A. M. (2023). Revolutionizing healthcare: The role of artificial intelligence in clinical practice. BMC Medical Education, 23(1), 689. https://doi.org/10.1186/s12909-023-04698-z
Al-Marzouqi, z, Al-Shidi, A., Al-Reesi, H., Al-Dhoani, A., Al-Sinani, H. (2025). Healthcare Professionals’ Readiness for Artificial Intelligence Applications in Healthcare Institutions in Oman. East Journal of Human Science, 1(5), 25-38. https://doi.org/10.63496/ejhs.Vol1.Iss5.151
Chan, C. K. Y. (2023). A comprehensive AI policy education framework for university teaching and learning. International journal of educational technology in higher education, 20(1), 38-49. https://link.springer.com/content/pdf/10.1186/s41239-023-00408-3.pdf
Chaodeethirathkul, P., & Pankham, S. (2023). Developing a model of actual adoption technology and innovation for health in Thailand. Academic Journal of Interdisciplinary Studies, 12(5), 168-181. https://doi.org/10.36941/ajis-2023-0135
Echefu, G., Batalik, L., Lukan, A., Shah, R., Nain, P., Guha, A., & Brown, S. A. (2025). The digital revolution in medicine: applications in cardio-oncology. Current treatment options in cardiovascular medicine, 27(1), 2. https://doi.org/10.1007/s11936-024-01059-x
Hafize Boyacı , & Selma Söyük. (2025). Healthcare workers' readiness for artificial intelligence and organizational change: a quantitative study in a university hospital. Boyacı and Söyük BMC Health Services Research, 25(813), 1-16. https://doi.org/10.1186/s12913-025-12846-y
Ido, R., & Ruth, W. (2016). Evolution and Revolution in Artificial Intelligence in Education. International Artificial Intelligence in Education Society. 26(2), 38-49. https://link.springer.com/content/pdf/10.1007/s40593-016-0110-3.pdf
Kozier, B., Erb, G., & Blais, K. (2018). Fundamentals of Nursing: Concepts, Process, and Practice. Pearson Education Limited. https://2u.pw/LUeh8a
Lucy, Shinners., Christina Aggar., Sandra Grace., Stuart Smith. (2020). Exploring healthcare professionals’ understanding and experiences of artificial intelligence technology use in the delivery of healthcare: An integrative review: Health Informatics Journal 26(2), 1226-1236. https://doi.org/10.1177/1460458219874641
Madubueze, M. H., Madubueze, C., Onyekwelu, R., Nweke, A., Ananti, M. (2025). Artificial intelligence in healthcare administration: A survey databased assessment of adoption, barriers, and opportunities in Nigeria: International Medical Science Research Journal. 5(9), 305-317. https://doi.org/10.51594/imsrj.v5i9.2098
Martínez Quinteros, A. S., Treviño Acosta, F. A., Ramirez Calvillo, D. S., Astudillo González, P. C., Mármol Muñoz, T. R., & Franco Vaca, A. J. (2025). Impact of artificial intelligence-guided cardiac ablation techniques on the management of complex arrhythmias: A systematic review. Ibero-American Journal of Health Science Research, 5(1), 2–8. https://doi.org/10.56183/iberojhr.v5i1.702
Moustaq, K. R., Khadiza, A., Latifun, N., MdTawhidul, I., Fateha, J., Fazila, A. f., Muhammad, J., Abdun, N., Sumon, A., Sabren, M., Tahmina, K., Shuvashish, D., & Rina, P. (2024). Healthcare workers' knowledge and attitudes regarding artificial intelligence adoption in healthcare: A cross-sectional study: Heliyn 10, 1-15. https://pmc.ncbi.nlm.nih.gov/articles/PMC11650294/pdf/main.pdf
Mukherjee, S., Chittipaka, V., Baral, M. M., Pal, S. K., & Rana, S. (2022). Impact of artificial intelligence in the healthcare sector. In Artificial Intelligence and Industry 4., 23-54. https://doi.org/10.1016/B978-0-323-88468-6.00001-2
Rony, M. K , Akter, K., Nesa, l., Islam, M., Johra, F Akter, F., Uddin, M., Sumon, A., Tanha, S., Rina, P,. (2024). Healthcare workers’ knowledge and attitudes regarding artificial intelligence adoption in healthcare: A cross-sectional study: journal homepage:. (10), 1-15. https://doi.org/10.1016/j.heliyon.2024.e40775
Suharnoko, A. (2024). "Hospital Readiness and Management Capabilities in Implementing Electronic Health Systems." UI Scholars Hub, Healthcare Operations Review.








