What does it actually take to prepare your organization for AI? Is training your own AI model realistic? And why are data governance and process audits becoming more important than ever?
In this episode of The AI on AI Podcast, Trent sits down with Brian Kuenzi to demystify open-weight AI models, model training, and the practical steps organizations should take before implementing AI at scale. They discuss why clean, well-governed data is the foundation of successful AI adoption, how process audits can uncover opportunities for automation, and why simply connecting AI to messy systems won't solve underlying business problems. Whether you're an internal auditor, business leader, or AI practitioner, this episode offers practical guidance on building an AI-ready organization—from strengthening data governance to designing workflows that allow AI agents to deliver real value.
In this episode:
What open-weight AI models are and who should use them
What AI model training actually involves
Why clean, structured data is essential for AI success
How process audits prepare organizations for AI automation
The importance of AI and data governance
Why disconnected systems limit AI's potential
Security, guardrails, and safely deploying AI agents in the enterprise
Practical advice for building an AI-ready organization
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