Action on Data Planet
Why AI Needs More Than Good Data
Action’s founder Keith Helfrich joins the Data Planet podcast to explore why enterprise AI depends on more than clean data. Discover how information architecture, business context, and deterministic agent skills can help organizations turn AI potential into reliable business outcomes.
Podcast Video Clips
Four Ideas Shaping the Future of Enterprise AI
Here are video highlights of Keith’s conversation with Working Planet’s CEO and Data Planet host, Emma Davis, on building the foundations for reliable, actionable AI.
Clean Data Isn't Enough
Why AI needs consistent business definitions, semantic models, and organizational context, not just well-structured data.
Your AI Doesn't Know What Your People Know
The hidden challenge of tribal knowledge, and why organizations must make business context accessible to AI agents.
Think Beyond Data Silos
How information architecture connects business concepts and processes across systems and departments.
How to Make AI Analytics Trustworthy
How deterministic agent skills can make analytical operations more reliable within probabilistic AI systems.
What You'll Learn
Practical perspectives on preparing your data, systems, and organization for the next generation of AI.
Build an AI-Ready Data Foundation
Understand why structured data, consistent definitions, and semantic context are essential to effective AI.
Make Business Knowledge Accessible
Learn why AI agents need explicit access to the rules, relationships, and definitions your people take for granted.
Connect Information Across Silos
Explore how information architecture helps create consistency across teams, processes, and technology platforms.
Make Agentic Analytics More Reliable
Discover how deterministic skills can connect the flexibility of LLMs with the precision required for enterprise analytics.