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MINI-REVIEW

Challenges in incorporating artificial intelligence into daily healthcare practice

Aref Zribi1* ,  Omar Ayaad1
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1 Sultan Qaboos Comprehensive Cancer Care and Research Centre, University Medical City, Muscat, Oman
AIH, 025350070 https://doi.org/10.36922/AIH025350070
Received: 25 August 2025 | Revised: 28 September 2025 | Accepted: 9 October 2025 | Published online: 3 November 2025
© 2025 by the Author(s). This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution 4.0 International License ( https://creativecommons.org/licenses/by/4.0/ )
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Abstract

Artificial intelligence (AI) holds huge potential in improving diagnosis and streamlining workflows in health care. However, several challenges remain, hampering the widespread adoption in clinical settings, such as for assessing data quality, bias, interoperability, and privacy, as well as for use in regulation and clinician training. Potent data channels are vital for assuring the exactness and trustworthiness of diagnostic performance. They boost the transmission of high-quality information, which is essential for expert annotations. Interoperable electronic health record integration and federated or privacy‑enhancing training approaches allow real‑time analytics while guarding patient data. Regulatory indecision and the comprehensive and continuous supervision of the process require transparent, explainable AI and shared accountability among developers, doctors, and institutions. In addition, prospective clinical validation, physician education, and governance are paramount to building trust and guaranteeing safe AI deployment in health care. This review outlines the difficulties faced when integrating these technological advancements into everyday clinical practice.

Graphical abstract
Keywords
Artificial intelligence
Health care
Data quality
Data security
Ethics
Regulatory compliance
Clinical validation
Funding
None.
Conflict of interest
The authors declare that they have no competing interests.
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Artificial Intelligence in Health, Electronic ISSN: 3029-2387 Print ISSN: 3041-0894, Published by AccScience Publishing
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