Endocrine Abstracts

JOINT3952

Aim: This study aims to evaluate the acceptance of artificial intelligence (AI) technologies by clinicians, focusing on factors influencing adoption, perceived benefits, challenges, and the impact on clinical decision-making and patient care.

Materials and Methods: A cross-sectional survey was conducted among 200 clinicians from various medical specialties across India. The survey included questions on familiarity with AI tools, perceived usefulness, ease of integration into clinical workflows, and concerns regarding AI’s role in medical practice. The Technology Acceptance Model (TAM) was used as a framework to assess clinicians’ attitudes and intentions to adopt AI. Data were analyzed to identify trends and correlations between clinician demographics, specialties, and AI acceptance levels.

Results: The study revealed that 68% of clinicians expressed a positive attitude towards adopting AI in their practice, citing improved diagnostic accuracy and efficiency as key benefits. However, 45% of respondents reported concerns about the reliability of AI tools and the potential for reduced clinical autonomy. Younger clinicians and those in tech-savvy specialties, such as radiology and pathology, showed higher acceptance rates compared to their peers. Additionally, 52% of clinicians indicated that lack of training and integration challenges were significant barriers to AI adoption.

Conclusion: While there is a growing acceptance of AI among clinicians, several barriers, including concerns about reliability, loss of autonomy, and insufficient training, hinder widespread adoption. Addressing these issues through targeted education, robust AI tool validation, and seamless integration into clinical workflows can enhance acceptance and utilization. The findings underscore the need for collaborative efforts between technology developers and healthcare professionals to ensure AI tools effectively support clinical practice and improve patient outcomes.