Artificial Intelligence (AI) has rapidly evolved into a transformative tool capable of enhancing diagnostics, optimizing treatment decisions, and streamlining healthcare delivery, yet its successful integration depends on the knowledge, attitudes, and practical readiness of healthcare professionals. This study aimed to evaluate these dimensions and identify key barriers influencing AI adoption. A prospective cross-sectional study was conducted over six months among 100 healthcare professionals at a tertiary care teaching hospital in South India, using a structured questionnaire covering demographic details, AI-related knowledge, attitudes, practices, and perceived challenges; descriptive statistics were applied, and age midpoints were used to estimate mean values. The participants had an approximate mean age of 34.0 ± 12.4 years, with a male– female ratio of 1.32:1. Only 40% were familiar with basic AI principles, although 70% understood machine learning and deep learning concepts and 65% had interacted with AI tools, while formal training was received by only 45%. Despite limited foundational knowledge, attitudes were largely positive, with 84% recognizing AI’s potential to advance research and 52% acknowledging its role in improving diagnostic accuracy. Major barriers included high implementation costs (72%), lack of structured training (66%), and regulatory uncertainties (68%). Overall, the findings highlight that although healthcare professionals exhibit encouraging attitudes toward AI, substantial gaps in knowledge and training persist, underscoring the need for targeted educational initiatives, institutional support, and clearer regulatory guidelines to facilitate effective AI integration in clinical practice.
Binu K. M.*, H. Doddayya, Sagnik Ghosh, Farhan Khan, Sivapriya R., Da O. Hipaya Lyngdoh, Deljo Jose (Sun,) studied this question.