By Dr. Scott Schell, PhD MD MBA, Chief Medical Officer, Cognizant
LinkedIn:Â Scott Schell
LinkedIn:Â Cognizant
Health systems face dual pressures: Increasing patient demand and flat clinical capacity. Documentation takes up to a third of a clinician’s day. Ambient scribing, using AI to capture and structure physician-patient conversations in real time, offers a potential solution.
Early results show ambient scribing can reduce documentation time by 20–30%, freeing several minutes per patient encounter. Collectively, these efficiencies mean more patients seen per clinic session, shorter wait times, and reduced after-hours charting for clinicians. Burnout, long acknowledged as a system-wide threat, eases when clinicians are freed from “pajama-time” burdens of late-night note entry.
Real-World Caveats
Peterson Health Technology Institute predicts ambient scribes will be among the fastest technology adoptions in healthcare history. However, as with any innovation in medicine, it comes with caveats. Accuracy, while high, is not absolute, requiring clinicians to be the final arbiters of what enters the patient’s medical record. This safeguard is essential for patient safety and cultural adoption by clinicians.
Integration is another challenge. Epic and Oracle Cerner have developed native offerings, focusing momentum today on smaller EHR ecosystems. For community hospitals and mid-size health systems, ambient scribing can be a differentiator, provided governance and workflow fit are carefully managed. For example, St. John’s Health uses AI agents to streamline documentation, enabling physicians to use mobile devices for ambient listening, efficiently converting conversations into concise summaries for care continuity and billing.
Adaptation: How Leaders Should Respond
C-suite leaders and CMIO/HIM executives should view ambient AI not as plug-and-play technology, but as a strategic workflow transformation. Three points stand out:
- Intentional Pilots: Launch in high-volume clinics or service lines with the greatest documentation burden. Define success metrics such as minutes saved per encounter, throughput increase, and note completion rates.
- Human Oversight: Require attestation. Ambient AI drafts the note; the clinician confirms its accuracy. This ensures data integrity and builds trust.
- Governance: Establish monitoring, incident response, and periodic review of both quality and productivity. Ambient AI should not be viewed as “set and forget.” It requires ongoing supervision, analysis, and stewardship.
Metrics that Matter
Throughput should be considered the primary metric. Efficiency gains, expressed in minutes per patient saved or additional patients seen per day, drive economics relevant to health systems. Burnout reduction is the natural second benefit. Accuracy and safety, while critical, should be considered foundational.
Revenue cycle impact is another factor. More accurate notes improve coding, reduce denials, and provide better visibility into predicted revenues. In this sense, ambient scribing extends beyond being a clinician-facing tool to broader enterprise-wide implications.
Managing Adoption
Adoption should be disciplined by goals such as measuring efficiencies gained per encounter, balancing clinician training and care throughput during rollout, ensuring clinician attestation and accountability, and establishing governance mechanisms for monitoring accuracy and responding to drift. These goals are more important than the technology itself. Ambient AI will continue to improve; what sets high-performing systems apart is their ability to implement it safely, at scale, with measurable outcomes.
The Bottom Line
Ambient scribing has evolved from being speculative to real, usable, and beneficial in pilot settings. The pros are clear: greater efficiency, reduced burnout, better revenue visibility. The cons are equally clear: accuracy limits, integration complexity, and the need for strong governance.
Leaders who take a pragmatic approach to this technology will realize its potential first. This includes piloting with purpose, keeping clinicians in control, and embedding governance from the outset. For health systems under pressure to see more patients, reduce burnout, and safeguard revenues, ambient AI is no longer a luxury. It’s fast becoming a necessity.