AI Is Changing How Medtech Sells: Field Lessons from Medtronic's Aortic Team
Commercializing a new medical device is a long haul - often a decade from idea to FDA clearance. That timeline demands smarter execution. At Reuters' MedTech conference in Boston, Jennifer Thompson, vice president of U.S. aortic sales at Medtronic, shared how her teams are using AI to speed market development, sharpen targeting, and tighten care coordination.
From manual data mining to AI-fed market insight
When Thompson joined Medtronic in 2006, much of the work meant combing through CMS files to decide which efforts mattered and which didn't. Today, AI does the heavy lifting. Teams can analyze shifting markets, disease states, and treatment options faster and with more precision, reducing guesswork before a commercial launch.
Every market development rep now uses AI to spot where eligible patients are and help physicians connect with them. That accelerates the path from awareness to treatment, keeps patients from getting lost in the system, and gives sales leaders a clearer view of where to focus.
Finding bottlenecks in the care pathway
The biggest gains came from treating data like a field guide, not just a report. In heart failure, repeated readmissions signaled a gap. AI analysis showed hospitalists were unintentionally blocking referrals to heart failure specialists and electrophysiologists who could provide device-based options after discharge.
With that insight, Medtronic focused on educating hospitalists about when and how to refer. The result: fewer avoidable readmissions and better outcomes. It's a simple lesson - map the actual referral chain, not the one you assume exists.
Deploying sales teams with precision
Medtronic also applies analytics within Salesforce to monitor activity patterns and spot early shifts in demand. That helps leaders decide where to deploy or retrain reps - critical in a category where training is long and expensive.
As Thompson put it, trends in procedures and local talent matter. If new vascular surgeons arrive and start seeking specific cases, the data should tell you first - so your people are in the right place at the right time.
What sales leaders can do this quarter
- Audit your data sources. Combine CRM, claims, EMR signals, and public datasets to build a single view of demand. For reference, see the CMS Data Portal.
- Model eligibility and proximity. Build patient-finding and provider-matching workflows that help physicians act quickly and reduce drop-off.
- Map the referral chain end-to-end. Include hospitalists, ED teams, and coordinators - not just cardiology or vascular specialists.
- Instrument your CRM. Track activity patterns, procedure trends, and account maturity to inform territory design and training plans.
- Train the field on AI basics. Give reps practical tools for account planning, list building, and follow-up workflows. If you need a structured path, explore role-based options at Complete AI Training.
- Align with regulatory timelines. Sales motion should reflect clinical milestones and review phases. For context, see the FDA's overview of the device approval process here.
The takeaway
Data fluency is now a sales advantage. Teams that turn messy datasets into clear actions - where to focus, who to educate, and how to route patients - will ship faster, sell smarter, and serve clinicians better.
As Thompson emphasized, the companies that make their data usable will set the pace for medtech commercialization.
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