High Signal: Data Science | Career | AI Episode 14: Why Most Companies Aren’t Actually AI Ready (and What to Do About It)
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Apr 10, 2025 Barr Moses, co-founder and CEO of Monte Carlo, shares insights on the AI readiness crisis many companies face. She reveals high-stakes data disasters, including a shocking $100M schema change. The discussion emphasizes the necessity of data quality and observability, as organizations struggle to align their ambitions with reality. Barr also highlights the transformative role of LLM agents in improving data debugging. Overall, it's a sharp critique of the disconnect between current data practices and the demands of AI.
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Costly Data Errors
- One schema change cost Unity $100 million and a 37% stock drop.
- Citibank was fined $400 million for poor data quality practices.
AI Mishaps
- Google's AI suggested using superglue on pizza to prevent cheese slippage.
- A Chevy dealer's AI chatbot agreed to sell a Tahoe for $1.
Data Readiness Gap
- All data leaders feel pressured to build with AI, but only 60% believe their data is ready.
- Your competitive advantage lies in your data, not just the model.
