Applied AI in Endoscopy is moving from novelty to necessity. In GI circles, the focus is less on generic “AI” promises and more on tools that improve quality, reduce documentation burden, and make endoscopy units run more predictably.
From “polyp detection” to end-to-end performance
Early clinical momentum for AI in GI centered on colonoscopy support, where computer-aided detection and quality metrics showed measurable value. But thought leadership today emphasizes a broader view: AI that supports both clinical decisions and the non-clinical work that shapes outcomes.
After all, as mentioned by Vivek Kaul, MD, FACG, FASGE, AGAF, NYSGEF, in a recent panel discussion on Applied AI in Endoscopy, “it really isn’t really a buzzword anymore.”
The biggest opportunities are often outside the scope image itself: scheduling, room turnover, supply readiness, follow-up workflows, and the many small steps that create delays and variability.
Documentation is the fulcrum—and it’s getting harder
Documentation has become one of the most immediate and measurable AI use cases in endoscopy. The burden has grown with procedure complexity, payer expectations, and regulatory requirements. Clinicians are asked to capture more fields and more justifications — often after an already demanding day.
GI leaders increasingly frame applied AI as a way to preserve documentation integrity while reducing cognitive load. The goal isn’t to replace physician judgment; it’s to prevent omissions, standardize key elements, and make it easier to tell the clinical story accurately.
This is where structured information matters. In practice, structured data enables AI to reliably recognize what happened (finding vs diagnosis, device use, quality checks, indications) and to support downstream actions like coding, analytics, and follow-up.
ROI shows up in more than one place
Endoscopy leaders evaluate AI through a mix of financial return and operational performance.
On the financial side, AI-supported documentation can improve billing capture and reduce revenue leakage by making sure critical elements aren’t missed—particularly in complex procedures where reimbursement depends on complete, compliant documentation.
On the operational side, AI can improve throughput and utilization by helping teams anticipate what’s next: predicting procedure duration, surfacing needed equipment, and supporting smoother room turnover. Provation’s own Chief Technology Officer, Paul Snider, has said, “The best AI is embedded into a day-to-day activity.”
Scalability matters because capacity can’t be expanded indefinitely by adding people or hours.
Advanced endoscopy raises the bar for applied AI
Advanced endoscopy is where applied AI is likely to prove its enterprise value—because complexity, cost, and risk are all higher. Procedures increasingly resemble “endosurgical” care: longer cases, more devices, more decision points, and greater coordination across specialties.
GI leaders highlight two needs:
- More faithful documentation of clinical reasoning — As cases become more individualized, the “why” behind decisions becomes essential—for referring clinicians, auditors, patients reading open notes, and medico-legal protection.
- Reducing cognitive load without losing nuance — AI must help with the repeatable parts (templates, safety checks, required fields, coding cues) while still allowing clinicians to document the unique anatomy, decision-making, and steps that define advanced cases.
Even within one health system, units operate differently, and successful AI must fit local workflows while enabling standardization.
Global scaling: training and research collaboration
Applied AI’s impact in endoscopy is also global. GI thought leaders see AI enabling training and education through recorded cases and remote proctoring, and enabling research collaboration built on large, centralized datasets to develop better tools for dysplasia detection and early cancer diagnosis.
Choosing where AI helps — and where it doesn’t
As applied AI continues to shape endoscopy, one theme remains consistent across GI thought leadership: success depends on knowing where technology meaningfully supports care — and where it risks adding noise.
Not every task should be optimized by AI. The real opportunity lies in guiding teams toward the right applications: reducing friction in documentation, workflow, and operations so clinicians can stay focused on clinical judgment, patient communication, and procedural excellence.
This is where experience matters. As the industry’s long-standing leader in GI documentation, Provation brings deep medical understanding of endoscopy workflows, data structure, and clinical nuance. That perspective helps GI teams evaluate applied AI realistically, identifying where it can deliver measurable value and where it may complicate care delivery.
Provation’s goal is not to replace the human elements of medicine, but to help teams use technology more intentionally, so that physicians can refocus their time and attention on patient care.