Readiness for AI-Enabled Healthcare Systems: Insights from Healthcare Professionals

Authors

  • Mamoona Afzal Department of Clinical Medicine (MBBS), Medical School of Hebei University of Engineering (HUE), Handan, Hebei, China.
  • Muhammad Asyab Afzal Department of Clinical Medicine (MBBS), Medical School of Hebei University of Engineering (HUE), Handan, Hebei, China.
  • Sara Zaib Department of Clinical Medicine (MBBS), Medical School of Hebei University of Engineering (HUE), Handan, Hebei, China.

DOI:

https://doi.org/10.70749/ijbr.v4i1.2827

Keywords:

Artificial Intelligence, AI-Enabled Healthcare Systems, Healthcare Professionals, Readiness Assessment, Attitudes toward AI, Clinical Decision Support, Digital Health, Healthcare Technology Adoption, Ethical Challenges, Medical Education.

Abstract

Background: Artificial intelligence is a gradually advancing field that is being integrated into healthcare to help with clinical decision-making, improve patient safety, and operational efficiency. Even though AI-supported healthcare systems are becoming more popular, it is important to note that successful adoption of the technology depends significantly on the readiness of healthcare professionals who should apply these technologies in the clinics. To create a sustainable, efficient, and effective AI implementation into a healthcare environment, their awareness, attitudes, readiness, and perceived challenges need to be evaluated. Objective: This study was aimed at assessing the awareness, attitudes, preparedness and perceived challenges and future expectation of the healthcare professionals with regard to AI-enabled healthcare systems. Methods: The survey was a quantitative cross-sectional survey design. The sample population used in this research was 350 health care workers who were represented through medical doctors, nurses, pharmacists, allied health professionals, health care administrators. The data was collected with the help of a structured self-administered questionnaire comprising of demographic variables, knowledge regarding AI in healthcare, beliefs about AI-enabled systems, willingness to use AI, perceived barriers to implementation, and future expectations. Descriptive statistical analysis was carried out with frequencies and percentages and results were given in tables and figures. Results: The findings revealed a great awareness of the topic of artificial intelligence in healthcare, and the majority of the respondents were familiar with the concept of AI and clinical use. The reactions towards the healthcare systems that were AI-enabled were largely favorable, particularly regarding the improvement in the quality of the diagnoses and patient safety. Majority of the interviewees indicated that they would not hesitate to implement AI systems and accept the technological development. Organizational readiness, however, was described as moderate, and a smaller number of respondents indicated that their organizations were technologically ready to integrate AI. The key challenges that were identified were issues with data privacy, expensive implementation, ethical considerations, and insufficiency of technical expertise. Nevertheless, despite the difficulties, the respondents showed an optimistic attitude to the future of AI and gave strong support to the adoption of AI in medical education and the creation of clear regulations. Conclusion: It is concluded that healthcare providers have positive attitudes and intentions towards AI-enabled healthcare systems, yet effective application must be supported by better organizational preparedness, specific training opportunities, and strong ethical and regulatory actions. The presence of these factors is important to address in order to achieve the responsible and successful introduction of artificial intelligence to a healthcare practice.

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Published

2026-01-30

How to Cite

Afzal, M., Afzal, M. A., & Zaib , S. (2026). Readiness for AI-Enabled Healthcare Systems: Insights from Healthcare Professionals. Indus Journal of Bioscience Research, 4(1), 79-86. https://doi.org/10.70749/ijbr.v4i1.2827