Conceptualization of the Use of Artificial Intelligence by Clinical or Research Laboratory Professionals: Challenges for Its Implementation in Mexico.

Introduction: Artificial intelligence (AI) is revolutionizing the healthcare sector via advanced tools to improve diagnostic accuracy, operational efficiency, and decision-making. In clinical laboratories (CLs), the integration of AI automates the processing and analysis of large volumes of data, enables the early detection of diseases, and supports personalized medicine. Determining how personnel involved in the use of AI in CLs conceptualize AI can enable the identification of challenges and difficulties impeding its implementation. Methods: An observational, prospective, cross-sectional, and comparative study was performed using an online survey for CL or research professionals in public or private CL throughout Mexico. The survey had 36 questions aimed at obtaining sociodemographic information and conceptualization of different aspects of AI, namely, familiarity, use, concerns, limitations, and useful applications. Results: Overall, 125 men and 237 women (aged 19-81 years) participated in this study. The survey results showed that CL or research professionals were familiar with AI in general. They preferred to use AI to reduce pre-analytical errors (67%) and save time (65%). Lack of knowledge and training (74%) and fear of being replaced (66%) were identified as major AI-related concerns; the ethical aspects of AI were also a main concern. Only 4.7% of respondents had received formal AI training, but 84.8% were willing to take AI courses. Conclusion: The findings highlight opportunities and priorities to promote AI-related public and educational policies, regulate AI adoption in CLs, develop optimal training strategies, as well as foster ethics, avoiding the exclusion of particular social groups.