KLAS report: Suki ROI Validations 2026

An independent KLAS ROI Validation examining how leading health systems are turning ambient AI into measurable clinical, operational, and financial impact.

Health systems are under pressure to prove that AI investments can truly deliver meaningful benefits and measurable outcomes.

In this new KLAS report, three large Epic-based health systems—FMOL Health, McLeod Health, and Rush University System for Health—share what actually happened after deploying Suki’s clinical intelligence platform in real-world ambulatory and ED settings.

This report goes beyond anecdotes. KLAS independently evaluated both quantitative and qualitative ROI, examining how ambient clinical intelligence impacted clinician time, documentation quality, coding accuracy, operational efficiency, and financial performance—without forcing more visits or compromising care.

Key insights in this report:

• How organizations measured ROI using longitudinal Epic Signal data
• What changed for clinicians’ documentation burden, after-hours work, and cognitive load
• Where financial gains came from—and why they weren’t driven by productivity pressure
• Lessons learned from pilots, governance, pricing models, and enterprise-scale rollout
• What separates ambient AI tools that scale from those that stall

If you’re evaluating ambient AI—or pressure-testing an existing deployment—this report offers a grounded, third-party look at what it takes to achieve ROI that holds up under scrutiny.