AI product teams don’t look like traditional product teams anymore.

Designers and software engineers are now joined by data scientists, ML engineers, and research-heavy roles — and for many Product Managers, this shift can feel intimidating.

In this episode of Product Bakar, Rishikesh Kankal breaks down how PMs can work effectively with data-heavy AI teams — without being data scientists themselves.

You’ll learn:

• The real difference between data scientists, ML engineers, and software engineers

• Where PMs add the most value in AI product teams

• How to frame problems instead of prescribing technical solutions

• Why data availability and feasibility matter more than flashy AI ideas

• How to define success beyond model accuracy — focusing on adoption, trust, and business impact

• Practical ways to build strong collaboration and protect your team from “AI magic” expectations

If you’re a PM working with AI teams — or about to — this episode will help you lead with clarity, credibility, and confidence.

Episode Tags / Keywords

Product Management, AI for PMs, Data Scientists, Machine Learning Engineers, AI Product Teams, Generative AI, Product Leadership, AI Strategy, PM Skills, AI Collaboration