Implications of Artificial Intelligence for Administrative and Management Roles Among Allied Health Occupations

This study explored how artificial intelligence (AI) technologies support the nondiagnosing/nontreatment roles of allied health workers, examining challenges and risks AI may pose for the workforce and highlighting areas for expansion as AI use grows.

We conducted 12 interviews with 14 key informants familiar with specific allied health occupations and how AI has been incorporated into their roles. Themes and gaps identified from peer-reviewed and gray literature informed our semi-structured interview guide. We used rapid content analysis to summarize findings from interviews around the following tasks: transcription, medical coding/billing, translation/interpretation, scheduling, communication, and data collection/management. We also summarized findings around ensuring AI literacy.

Allied health occupations (typically considered occupations other than physicians, nurses, and dentists) not directly involved in patient diagnosis and treatment have varying levels of interaction with AI. Positive descriptions of AI use in these allied health roles included situations where workforce demand exceeds supply and where AI can be deployed for some routine administrative tasks and may improve job satisfaction by allowing the workforce to focus on more complex and rewarding tasks. AI use was also described positively where it contributed to increased efficiency, for example, in facilitating communications. Because AI can produce biased or erroneous results, cautions about its applications included needing additional staff time to monitor outcomes and avoid negative impacts on patient safety and an organization's operations. Education that contributes to AI literacy across the health workforce is considered critical for its appropriate use.

To date, most allied health workers' jobs with administrative/management roles have not been at risk of replacement by AI. AI's rapidly expanding use, however, combined with the ongoing impacts of provider burnout and financial pressures on health systems, could incentivize increased interest in using AI to compensate for a downsized workforce, including many allied health occupations.