This episode explores what organizations need to get right with their data, the difference between automation and generative AI, and how agentic systems can support real workflows. We break down practical steps for readiness, governance, and using tools like MCP servers and multi-agent models effectively.

What You Will Learn:
• AI is only as good as the data behind it.
• Generative AI does not replace classic data science.
• Unstructured data is a major (and risky) part of the AI landscape.
• AI should be treated as a copilot, not an autonomous decision-maker.
• AI agents require governance and visibility.
• Not every problem needs Generative AI.
• Multi-agent systems introduce new risks.
• Education is the first layer of AI governance.