<br />Artificial intelligence has become an essential component in colonoscopy, where computer-aided detection (CADe) algorithms contribute to identifying potential lesions and tumors with an accuracy that may surpass human vision. Clinical trials have demonstrated that the use of such systems increases colorectal polyp detection rates by up to 20% compared to traditional colonoscopy. Despite this achievement, an intense academic debate has emerged regarding the long-term effects on physicians’ skills.<br />One major concern is the so-called “over-reliance effect.” When physicians lean heavily on the cues provided by AI systems, their critical practice of fine visual observation may decline. This phenomenon resembles that of pilots who depend on autopilot navigation systems, potentially weakening their ability to manually intervene during emergencies.<br />On the other hand, another perspective argues that artificial intelligence can serve as a training tool. For instance, novice physicians may develop their skills more rapidly by comparing their own visual assessments with AI outputs. Furthermore, AI reduces physician visual fatigue during prolonged examinations, allowing them to better focus on comprehensive clinical decision-making.<br />Ongoing research is currently attempting to determine the “optimal dose” of AI reliance. It is unlikely that such systems will be eliminated; rather, they will be integrated into training programs that preserve physicians’ diagnostic skills through realistic simulations without full dependence on automation.<br />Thus, the central question is not whether AI diminishes physicians’ skills, but how its use can be regulated so that it strengthens rather than weakens them. Colonoscopy is a sensitive field, and any loss of visual diagnostic capability could result in serious consequences. Therefore, the key challenge remains achieving a balance between advanced technology and human expertise.<br /><br />Al-Mustaqbal University is the first one university in Iraq.<br />