Evaluating Artificial Intelligence Competency Needs and Priorities Among Medical College Professionals: A Cross-Sectional Analysis
DOI:
https://doi.org/10.25751/rspa.46778Keywords:
Artificial Intelligence, Attitude of Health Personnel, Health Knowledge, Attitudes, PracticeAbstract
Introduction: Artificial intelligence (AI)-based tools are rapidly entering clinical workflows. Understanding clinicians’ perceptions, the areas in which they expect AI to be beneficial, desired competency levels, and ethical concerns is essential for planning training initiatives and ensuring safe implementation.
Methods: A cross-sectional, anonymized online survey administered through Google Forms was distributed to healthcare workers at a medical college. Data were collected between 16 and 23 January 2026. The questionnaire explored perceived benefits of AI, current clinical challenges that AI could address, workflow areas that AI could optimize, reasons why clinicians should understand AI, key ethical concerns, desired competency levels, and a measurable outcome that AI training could improve.
Results: Ninety-nine respondents from a wide range of specialties participated: Anesthesiology, General Surgery, General Medicine, Pediatrics, Radiology, Pulmonology. The mean clinical experience was 10.6 years. The most frequently selected potential benefits were earlier disease detection (74/99, 74.7%) and improved diagnostic accuracy (72/99, 72.7%). The workflow areas most commonly identified for AI implementation were optimization of clinical documentation and notes (85/99, 85.9%) and imaging interpretation (65/99, 65.7%). Desired AI competency levels were practical use/safe application of AI tools (46/99, 46.5%), advanced competency (designing and evaluating AI models) (40/99, 40.4%), and basic literacy (13/99, 13.1%). The leading ethical concerns were clinician accountability/liability (41/99, 41.4%), patient safety (31/99, 31.3%), transparency (22/99, 22.2%), bias (16/99, 16.2%), and data confidentiality (15/99, 15.2%).
Conclusion: Clinicians across career stages expect AI to improve early disease detection and diagnostic accuracy and express a strong interest in AI training focused on the safe and accountable use of these technologies.
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Copyright (c) 2026 Nazia Nazir, Shivi Mishra, Rohit Singh
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