Introduction: Artificial intelligence (AI) and digital health technologies are increasingly integrated into diabetes care. However, data on awareness and adoption among endocrinologists in Malaysia remain limited. Methodology: A cross-sectional survey was conducted among endocrinologists in Malaysia using a structured online questionnaire. Items assessed awareness of AI-based diabetes technologies, attitudes toward AI in clinical care, perceived barriers, and willingness to adopt AI tools. Multiple responses were permitted for selected items. Results: The cohort (N = 65) comprised 60% junior endocrinologists and 40% senior endocrinologists (72% governmentbased). Recognition was higher for monitoring and screening technologies, particularly continuous glucose monitoring (CGM) data analytics (66.2%) and automated retinopathy screening (33.8%) versus therapeutic AI tools, such as lifestyle coaching applications (43.1%) and insulin titration algorithms (30.8%). While approximately 60% endocrinologists reported familiarity with AI in diabetes care, 15.4% of them had no prior recognition of AI tools. Attitudes toward AI were largely positive; 76% agreed that AI improves diabetes outcomes, 60% believed it reduces clinician workload, and 90% agreed that AI would complement diabetes care systems. However, approximately 50% remained neutral regarding its reliability and expressed concerns about ethics and data security. In practice, only 40% endocrinologists reported using AI tools, most commonly CGM analytics with automated insights (46.4%), with generally low frequency of use. The main barriers to adoption were lack of formal training (78.5%) and high implementation costs (60%). Despite this, 90% expressed willingness to adopt AI in future practice. Conclusion Awareness of AI technologies in diabetes care among Malaysian endocrinologists is variable, with stronger recognition of tools already embedded in routine practice. While attitudes toward AI are favorable, significant educational and structural barriers must be addressed to facilitate broader implementation.
Artificial Intelligence ; Endocrinologists ; Malaysia ; Diabetes Mellitus