Integrating artificial intelligence into medical laboratories: A structured implementation framework

This article presents a structured framework for integrating artificial intelligence (AI) into medical laboratory workflows. As laboratories face increasing demands, workforce shortages, and technological complexity, AI offers promising solutions to enhance efficiency, diagnostic accuracy, and predictive capabilities. The paper outlines key benefits of AI, including automation, quality assurance, and administrative optimization, while also addressing critical challenges such as bias, legal and ethical concerns, workforce disruption, and over-reliance on automated systems. A multi-level implementation strategy is proposed, spanning international, national, and organizational domains, with emphasis on standards, guidelines, training, and oversight. Importantly, the article underscores that AI is a supportive tool, not a replacement for laboratory professionals, whose expertise remains essential for validation and interpretation. The framework aims to guide responsible AI adoption while safeguarding quality and patient safety.