AI creates measurable value in medical device service when adoption translates into better operational, workforce, customer, and financial outcomes. Track first-time fix, resolution time, warranty costs, technician time to competency, and customer experience alongside usage. Together, these measures help service executives and finance partners assess whether AI is improving performance and whether the benefits justify its total cost.

During a 2026 Service Next Medical conversation, Jennifer Cota, Director, Customer Support Global Service & Repair at Arthrex, emphasized building measurement into technology projects from the outset. When seeking approval, she stressed having "a plan for the things that you were going to measure." Applied to AI, that approach gives service leaders a clear starting point for connecting adoption with operational improvements and validating the benefits over time.

A separate 2026 discussion described an AI-enabled service organization that recorded lower call abandonment, shorter call times, and faster technician development after implementation. The practitioner also cautioned against attributing all warranty-cost improvements to the technology, reinforcing the need to distinguish observed progress from benefits that AI demonstrably caused.

Build a baseline before deployment, then select a small set of measures tied to the workflow being changed. A troubleshooting pilot could track answer accuracy, resolution time, repeat visits, and warranty expense, while an onboarding initiative could measure time to independent work and escalation frequency. Review results with finance and quality colleagues, account for implementation and operating costs, and document other changes that may have influenced performance.

Join Service Next Medical to compare how medical device service leaders measure AI adoption, validate operational improvements, and build credible investment cases.