Wondering how today's software and data product leaders are designing ML/AI and analytics solutions that actually get used? How can UX design and product management enable data science an AI to produce economic value and human-centered solutions?

The monster in the room of data products is "low adoption." Low utility, low usability, low value.

My name is Brian T. O'Neill, and on Experiencing Data, I offer you a designer's perspective on why simply building the pipelines, models, and platforms behind AI/ML apps isn't enough to drive meaningful user and business outcomes with data. Since 2018, this show has been dedicated to data products and according to ListenNotes, it's now ranked in the top 2% of all podcasts globally—thanks to listeners like you.

Through solo episodes and interviews with AI/ML, product management, UX design, and innovation leaders, I unpack the thinking, methods, and lessons learned that you can apply to the design of your own ML/AI apps and data products.

The show also covers topics like:

• The "producty" approach to building internal AI/ML and analytics solutions for decision support
• Explorations of the differences between doing internal vs. external (e.g. SAAS) data product management
• Designing UI/UX for explainability and model interpretability
• UXR methods for uncovering the unarticulated needs and problems of stakeholders and users
• Why data visualization alone isn’t sufficient for dashboards and decision support tools
• Executive/CDO/CPO spotlights including case studies and lessons learned designing data teams to be product-oriented

Subscribe today on all major platforms or browse the episode archive.