Beyond the Data: The Human Touch in AI-Driven Healthcare with Anne Pelz

How Anne Got into Product Management

Rina Alexin | 00:00–02:45

So Anne, I love to ask this question to everyone I interview because I seem to get a different answer every time. How did you get into product management—and why?

Anne Pelz | 00:15–02:45

Long time ago, I was working for a startup focused on water purification technology. When the company ran out of funding, I began searching for my next adventure. A dear friend introduced me to a role at Charles River Analytics. I had never even heard of product management at that time, but I interviewed, got the job, and immediately enrolled in a pragmatic marketing course.

I transitioned from a short career as a mechanical engineer and marketing director into product management, and I’ve stayed ever since. What excites me most is the range — getting to work with engineers, customers, and scientists, translating between teams. That collaboration and translation are incredibly rewarding.

The Transition from Engineering to Product

Anne Pelz | 02:45–05:02

My background in engineering definitely helps. I love the technical aspects of building things, but also understanding customer needs. Product management allows me to bridge those worlds — talking to PhD statisticians on one side and UX architects on the other. It’s the best of both worlds: human empathy meets technical problem-solving.

OM1’s Mission and the Role of AI in Healthcare

Anne Pelz | 05:02–07:43

At **OM1**, we work with real-world healthcare data. We partner with providers to collect electronic medical records, clean and de-identify them, and use **AI** to enrich those datasets. The goal is to help life sciences companies better understand their markets, improve patient outcomes, and accelerate clinical research.

One of our biggest focuses is helping healthcare professionals identify which patients are good candidates for certain treatments — whether that’s surgery, therapy, or medication.

Using AI to Diagnose Rare Diseases

Anne Pelz | 07:43–10:15

We develop AI models that can identify patients who may have conditions that take years to diagnose, such as **rare diseases** or **treatment-resistant depression**. These tools can spot potential matches early and help clinicians screen patients sooner, which is life-changing.

Our models also include clinical explainability, meaning they show why the AI made a specific recommendation and how adjustments might improve outcomes.

Understanding Digital Phenotypes and Patient Data

Anne Pelz | 10:15–12:26

A **digital phenotype** is a comprehensive patient profile built from electronic health records, lab results, and questionnaires. It captures not just the diagnosis but the surrounding variables that describe who the patient is. By comparing phenotypes of diagnosed and undiagnosed individuals, we can spot those who may need further screening — potentially saving years of uncertainty.

Building Trust in AI Systems and Data Privacy

Anne Pelz | 12:26–14:58

Trust is crucial. Patients share deeply personal information, and they need assurance that it’s handled ethically. We focus on de-identification, data governance, and explaining the *why* behind every algorithmic decision.

Like clinical trial participants, people contribute their data not only to seek treatment but also to help others. There’s an altruistic element — contributing to models that could shorten the path to diagnosis for countless others.

Defining Commercially Viable AI Use Cases

Anne Pelz | 14:58–17:06

AI isn’t a one-size-fits-all solution. It’s critical to ask: “What problem are we solving, and is AI the right approach?” Just like any other product, it must start with a solid **business case**. Estimate implementation costs, project returns, and validate that the ROI makes sense before scaling. That’s just good product management.

Lessons from AI Product Implementation

Anne Pelz | 17:06–19:10

Implementing AI is similar to the early app boom — everyone wanted one, but few considered long-term maintenance. You must plan for continuous iteration and change, as models, data sources, and even platforms evolve faster than ever.

Building Product Teams and Hiring for Core Skills

Anne Pelz | 19:10–22:42

When hiring, I prioritize **diplomacy**, **prioritization**, and **communication**. These are timeless skills that translate across industries. The domain expertise can be learned, but you can’t easily teach empathy or clear communication.

I also listen for how candidates make trade-offs, handle tension, and communicate decisions — that’s where true leadership emerges.

The Power of Diplomacy in Product Leadership

Anne Pelz | 22:42–25:16

Diplomacy is often overlooked but absolutely vital. Product leaders navigate complex, cross-functional relationships. It’s about persuasion, empathy, and timing — knowing when to stand firm and when to listen. Diplomacy ensures ideas move forward constructively.

Coaching and Developing High-Performing Teams

Anne Pelz | 25:16–28:33

As leaders, we must coach our teams to solve problems independently. I encourage PMs to bring solutions, not just challenges. Give feedback that’s specific and actionable — for example, “In meetings, I noticed you do X; please try Y instead.” Clear, constructive feedback drives growth.

Advice for Aspiring VPs of Product

Anne Pelz | 28:33–31:12

If you’re aiming for VP-level leadership, focus on **coaching**, **clarity**, and **strategic thinking**. Bring data, but also bring perspective. Never enter a leadership meeting without an opinion — just remain open to having it changed by new insights.

Balancing Data-Driven Decisions with Empathy

Anne Pelz | 31:12–34:50

Empathy humanizes the data. In healthcare, that balance is everything. Yes, the metrics matter — but behind every data point is a person. Blending analytics with compassion ensures we create not just efficient systems but meaningful impact.

Final Reflections and Career Advice

Anne Pelz | 34:50–End

Work on products that make a difference. For me, building something that improves lives is the ultimate motivation. No matter where your career takes you — keep your curiosity, your empathy, and your integrity. That’s the real measure of success in product management.