A decade of transformation in MASLD: from nomenclature to novel therapies

Key Takeaways for GI Nurses

• Artificial intelligence (AI) tools are increasingly being integrated into endoscopy suites, particularly for real-time polyp detection during colonoscopy, and nurses will play a key role in supporting these systems during procedures.
• AI-assisted documentation tools may help streamline charting and procedure reporting, potentially reducing the administrative burden on endoscopy nursing staff.
• Workflow management technology powered by AI could impact scheduling, room turnover, and patient flow in GI units, requiring nurses to adapt to new operational processes.
• As AI becomes more embedded in practice, nurses will need ongoing education to understand how these tools function, their limitations, and how to communicate AI-assisted findings to patients and physicians.

Clinical Relevance

The integration of AI into endoscopy practice represents a meaningful shift in how GI units operate day to day. For nurses working directly in the procedure room, AI-assisted polyp detection systems change the dynamic of the colonoscopy itself—these computer-aided detection (CADe) tools flag suspicious lesions in real time, which means nurses must be prepared to assist physicians in confirming, biopsying, or resecting additional findings that may not have been previously flagged. This has downstream implications for procedure time, specimen handling, and patient counseling regarding surveillance intervals.

Beyond the bedside, AI-driven documentation tools have the potential to reduce the charting burden that often falls to endoscopy nurses, freeing up time for direct patient care, pre-procedure assessment, and post-procedure recovery monitoring. However, nurses will need to remain vigilant in verifying that AI-generated documentation accurately reflects the clinical encounter, as accountability for the medical record remains a nursing and physician responsibility even when technology assists in its creation.

At the unit level, AI-supported workflow management may reshape scheduling practices, room utilization, and staffing allocation. Nurses in leadership or charge roles should anticipate a learning curve as these systems are piloted and adopted, and should advocate for adequate training time before full implementation. Professional development opportunities around AI literacy—understanding how these algorithms work, their evidence base, and their limitations—will become increasingly relevant for GI nurses seeking to stay current in a rapidly evolving field, and may also inform how nurses discuss these tools with patients who ask about their use during procedures.

Bottom Line

AI is steadily becoming part of everyday endoscopy practice—from real-time polyp detection to documentation and workflow support—and GI nurses should proactively seek education on these tools to ensure safe, efficient integration into patient care without compromising the clinical judgment and oversight that remain central to the nursing role.