Artificial intelligence integration in allied health professions: A comprehensive review of educational, research, and clinical applications.

BackgroundArtificial intelligence (AI) is rapidly transforming healthcare delivery across multiple disciplines. Allied health professions-including diagnostic medical sonography (DMS), health informatics (HI), medical billing and coding (MBC), midwifery (MW), occupational therapy (OT), physical therapy (PT), and physician assistant (PA) practice-represent critical yet understudied domains of AI integration. Understanding of how AI technologies are adopted across these professions is essential for supporting ethical and effective implementation.ObjectiveThis review synthesizes the current literature on AI integration across seven allied health professions, examining applications in education, research, and clinical practice while identifying implementation challenges, and ethical considerations.MethodsA structured literature review of peer-reviewed articles, systematic reviews, and professional practice guidelines published between 2018 and 2025 was conducted. Articles were selected based on relevance to AI applications in allied health professions and discussion of educational, research, or clinical implementations. Particular attention was given to applications where AI augments rather than replaces clinical judgment and therapeutic relationships.ResultsAI integration demonstrates several cross-disciplinary trends. In education, simulation platforms, adaptive learning systems, and virtual patient support competency development and personalized instruction. In research, AI enhances large-scale data analysis, predictive modeling, and evidence synthesis. Clinically, AI improves diagnostic accuracy, workflow efficiency, and decision support across professions. However, implementation raises concerns regarding data privacy, algorithmic bias, automation complacency, and inequitable access to technology.ConclusionsAI is reshaping allied health education, research, and clinical practice. Responsible integration requires discipline-specific validation, ethical governance, and interprofessional collaboration to ensure AI strengthens- rather than replaces-professional expertise and patient-centered care.