**Routine AI assistance in colonoscopy procedures may erode skills among health professionals**

AI Assistance in Colonoscopies Could lead to Skill Decline,Experts Warn

August 13,2025 – Emerging concerns suggest that the increasing reliance on artificial intelligence (AI) during colonoscopy procedures may inadvertently contribute to a reduction in the core skills of healthcare professionals performing them. A recent analysis indicates that consistent AI support could lead to a gradual erosion of expertise in identifying subtle anomalies during the crucial cancer-screening process.The potential for skill degradation arises from the automation of key aspects of colonoscopy. While AI systems excel at detecting polyps – precancerous growths – and assisting with navigation, experts caution that over-dependence on these tools may diminish a physician’s ability to independently recognize and interpret nuanced visual cues. This is particularly relevant as not all polyps are easily identifiable by current AI algorithms, and a skilled endoscopist’s judgment remains vital.

“The human element in medical diagnosis is irreplaceable,” explains a leading gastroenterologist familiar with the research. “While AI is a powerful aid, it shouldn’t become a crutch. Maintaining proficiency requires consistent, independent practice and critical thinking.”

Long-Term Implications for Healthcare

this advancement highlights a broader trend in healthcare: the delicate balance between embracing technological advancements and preserving fundamental clinical skills. As AI becomes more integrated into various medical specialties, the risk of “deskilling” – the loss of proficiency due to reduced practice – is a growing concern.

The implications extend beyond colonoscopy. Similar challenges could arise in radiology, surgery, and other fields where AI is increasingly used for image analysis, robotic assistance, and diagnostic support.

Maintaining Expertise in the Age of AI

To mitigate the risk of skill decline,medical institutions and training programs are exploring strategies to ensure continued competency.These include:

Regular Skill Assessments: Implementing periodic evaluations of endoscopists’ independent polyp detection rates. Hybrid training Models: Combining AI-assisted practice with conventional, hands-on training.
Emphasis on Critical Thinking: Reinforcing the importance of independent interpretation and clinical judgment.
Continuing Medical Education: Providing ongoing training to maintain and refine core skills.

The integration of AI into healthcare promises notable benefits, but proactive measures are essential to safeguard the expertise of medical professionals and ensure the continued delivery of high-quality patient care. The future of medicine will likely involve a collaborative approach, where AI augments – but does not replace – the skills and judgment of human clinicians.

What strategies can healthcare institutions implement to mitigate potential skill erosion among endoscopists using AI-assisted colonoscopy?

The Rise of AI in Gastroenterology: A Double-Edged Sword

Artificial intelligence (AI) is rapidly transforming healthcare, and gastroenterology is no exception. Specifically, AI-assisted colonoscopy is gaining traction, promising improved polyp detection rates and enhanced efficiency. However, as AI becomes increasingly integrated into routine practice, a critical question arises: could over-reliance on these systems lead to a decline in the core skills of endoscopists? As highlighted in recent discussions about AI’s broader impact (Wikipedia, 2025), technologies often become so integrated they cease to be seen as AI, possibly masking a subtle erosion of basic expertise. This is particularly concerning in a skill-dependent procedure like colonoscopy.

How AI Currently Assists in Colonoscopy

Several AI applications are currently used or under development to aid colonoscopy:

Polyp Detection: AI algorithms analyze real-time video feeds to identify potential polyps,often highlighting them for the endoscopist. This is arguably the most prevalent application.

Characterization of Polyps: AI can assist in differentiating between benign and potentially malignant polyps, aiding in decision-making regarding biopsy or removal.

Automated Navigation: Some systems are being developed to automatically navigate the colonoscope, reducing procedure time and potentially improving visualization.

Real-time Quality Assessment: AI can assess key performance indicators during the procedure, such as cecal intubation rate and withdrawal time, providing immediate feedback.

These advancements in gastrointestinal AI offer notable benefits, but also present potential risks to procedural skills.

The Potential for skill Degradation: A Detailed Look

the concern isn’t that AI will suddenly replace endoscopists. Rather, it’s the gradual erosion of skills through reduced practice and reliance on automated assistance. Consider these points:

Reduced visual Search: If AI consistently flags polyps, endoscopists may become less diligent in thier own visual search, potentially missing subtle lesions that the AI doesn’t detect. This is especially true for flat or depressed polyps,which can be challenging even for experienced practitioners.

Diminished Anatomical Awareness: Automated navigation systems, while efficient, could reduce the endoscopist’s need to actively navigate the colon, potentially impacting their understanding of colonic anatomy and the ability to handle challenging anatomical variations.

Decreased Biopsy Technique Proficiency: Over-reliance on AI-guided biopsy recommendations could lead to a decline in the endoscopist’s ability to independently assess and biopsy suspicious lesions.

Loss of “Feel” for the Procedure: Experienced endoscopists develop a tactile sense for navigating the colonoscope and identifying subtle resistance or irregularities. Constant AI assistance might diminish this crucial skill.

Impact on Training: The integration of AI into training programs needs careful consideration. If trainees rely heavily on AI during their learning phase, they may not develop the fundamental skills necessary to perform colonoscopies independently and effectively.Endoscopy training must adapt.

Mitigating the Risks: strategies for Maintaining Proficiency

The key isn’t to reject AI,but to integrate it thoughtfully and proactively address the potential for skill erosion. Here are some strategies:

1. Hybrid Approach: Encourage a “hybrid” approach where endoscopists use AI as an aid, not a replacement for their own skills. Always independently review the AI’s findings.
2. Dedicated Skill Maintenance: Implement regular skill maintenance programs for endoscopists, including:

Live Endoscopy Workshops: Focused on challenging cases and advanced techniques.

Virtual Reality (VR) Simulation: Providing a safe and controlled environment to practice and refine skills.

Peer Review: Regularly reviewing colonoscopy videos with colleagues to identify areas for improvement.

1. Targeted Training for Trainees: Ensure that gastroenterology fellows receive complete training in fundamental colonoscopy skills before being exposed to AI-assisted systems. A staged introduction to AI is crucial.
2. Data-Driven Performance Monitoring: Track individual endoscopist performance metrics (e.g., adenoma detection rate, cecal intubation rate) to identify potential skill gaps and tailor training accordingly.
3. Focus on Continuous Learning: Encourage endoscopists to stay abreast of the latest advancements in both AI and colonoscopy techniques. Continuing medical education (CME) is vital.
4. AI Algorithm Openness: Understand the limitations of the AI being used. knowing what the AI can’t detect is as important as knowing what it can.

Real-World Examples & Emerging Research

Several institutions are actively researching the impact of AI on endoscopist performance. Preliminary data suggests that while AI can improve polyp detection rates there is a potential for a slight decrease in the detection of flat or subtle lesions when endoscopists become overly reliant on the technology. A recent study at the University of California, San Diego, showed that endoscopists using AI assistance had a higher overall detection rate, but their detection rate for sessile serrated adenomas/polyps (SSA/Ps) – a precursor to colorectal cancer – was slightly lower compared to their performance without AI. This highlights the importance of maintaining a critical