Actionable companion · School leadership and instructional improvement
From leadership research to district action: Faculty development and institutional readiness for incorporating AI in health professions education- A narrative review
AI-assisted editorial implementation guide. Proposed district actions are separate from the original authors’ findings and recommendations. Independent peer review of this guide is not asserted.
Evidence and transfer
Education-related source: verify which participants, institutions and outcomes were actually studied before district adoption. Source publication type: review-article. License and identity checks do not establish study quality or causality.
Original authors’ abstract, reproduced under the source license:
Abstract Artificial Intelligence (AI) is presently reshaping higher education in a rapid way, due to the high engagement of students with AI. The study's aim was to explore strategies driving transformation in higher education at large and particularly dental education. This article is a narrative review adopting a structured approach for literature search, study selection, and data extraction. A comprehensive search of electronic databases, including PubMed, Scopus, Google Scholar, and ScienceDirect for studies published between 2015 and 2025 was conducted. The review is discussed under the themes of transformative education, institutional readiness, including resistance to change, ethical considerations and global perspectives in health professions, and dental education. Further, transformative education explores faculty development, including micro-credentials and lifelong learning, a safe learning environment, infrastructure, and assessment. AI is well acknowledged in both health profession education and clinical practice. While GenAI has the potential to improve creativity, feedback, and collaborative learning, the issues of plagiarism, assessment validity, and authorship transparency are also discussed. AI encounters limitations in gauging psychomotor dexterity and clinical reasoning. Ethical concerns about algorithmic prejudice, data privacy, monitoring, and the deterioration of human-centered learning are also included. To conclude, transformative strategies for institutional readiness to be considered under the domains of governance and policy, curriculum integration and faculty training, academic integrity and assessment reforms, and leadership and change management to ensure proper integration of AI and to prepare competent, adaptable, and socially responsible health professionals. Maintenance of human oversight at the center of higher education is essential, and universities should treat AI as a catalyst for modernization rather than a threat. Keywords: artificial intelligence, dental education, ethics, faculty development, global perspectives, health professions education, higher education institutions
Study methods
This article is a narrative review adopting a structured approach for literature search, study selection, and data extraction, to enhance transparency and methodological clarity. (Figure 1) Given the heterogeneity of the included studies, the findings were synthesized narratively (35, 36).
Limitations
No passage was selected automatically. Inspect the complete source before adopting a practice.
A 90-day district inquiry
- Days 1–15 · Appraise. Read the source methods, recruitment, comparator, outcomes and limitations. Record how the study setting differs from your district and which claim the design can support.
- Days 16–30 · Design. Choose one school improvement question with teachers. Protect a short shared planning cycle, agree an instructional change and use a common rubric for examining student work. Agree participation, privacy protections, baseline and stopping rules before starting.
- Days 31–60 · Observe. Collect the pre-agreed measures, keep a log of implementation changes and invite confidential voluntary feedback. Preserve existing support for staff and learners.
- Days 61–90 · Decide. Review implementation fidelity, teacher time and independently scored student work against a recorded baseline. Examine access differences and competing explanations before attributing changes to leadership. Make a dated decision to stop, revise or extend the inquiry.
Board decision brief
Present the local problem, source setting, evidence limits, intervention, responsible owner, total cost, measured changes and uncertainty. Separate staff perceptions, implementation measures and student learning outcomes.
Attribution and reuse
Prathibha Prasad; Mahinour Amin; Elizabeth Fitriana Sari; Lovely M Annamma; Jayaraj Narayanan; Dinesh Yasothkumar; Mehzabin Ahmed. Faculty development and institutional readiness for incorporating AI in health professions education- A narrative review. Frontiers in Dental Medicine (2026-07-22). https://doi.org/10.3389/fdmed.2026.1874590
Prepared 2026-11-07. Source authorship and DOI are preserved. The abstract and source passages are attributed extracts; this editorial guide is offered under the same CC BY 4.0 license.