Episode 14: Why Most Companies Aren’t Actually AI Ready (and What to Do About It)
Barr Moses—co-founder and CEO of Monte Carlo—thinks we’re headed for an AI reckoning. Companies are building fast, but most are still managing data like it’s 2015. In this episode, she shares high-stakes failure stories (like a $100M schema change), explains why full-stack observability is becoming essential, and breaks down how LLM agents are already transforming data debugging. From culture to tooling, this is a sharp look at what real AI readiness requires—and why so few teams have it.
High Signal: Data Science | Career | AI
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Show Notes
Barr Moses—co-founder and CEO of Monte Carlo—thinks we’re headed for an AI reckoning. Companies are building fast, but most are still managing data like it’s 2015. In this episode, she shares high-stakes failure stories (like a $100M schema change), explains why full-stack observability is becoming essential, and breaks down how LLM agents are already transforming data debugging. From culture to tooling, this is a sharp look at what real AI readiness requires—and why so few teams have it.
LINKS
- 2024 State of Reliable AI Survey – Monte Carlo
- Delphina's Newsletter
- Unity’s $100M Data Error – Schema Change Gone Wrong
- Citibank’s $400M Fine for Risk Management Failures
- Google’s AI Recommends Adding Glue to Pizza
- Chevy Dealer’s AI Chatbot Agrees to Sell Tahoe for $1
- The AI Hierarchy of Needs by Monica Rogati (HackerNoon)
- Data Quality Fundamentals by Barr Moses, Lior Gavish, and Molly Vorwerck (O’Reilly)
- Delphina's Newsletter