The hard truth about enterprise AI? According to industry research, some 88% of AI pilots never reach production. And by 2027, roughly 40% of AI projects may be canceled entirely. The problem isn't the AI models; it's the data.

While organizations rush to implement generative AI, they're hitting a fundamental wall: AI agents can't deliver reliable business value without clean, governed, and context-rich enterprise data. The result? Non-deterministic outputs that change from run to run, black box decisions that leaders can't defend, and brittle integrations that break at enterprise scale.

Register for this episode of DM Radio to learn about the next stage of AI adoption: bridging enterprise data to AI with trust and governance built from the ground up. Sami Akbay and Terrence Sheflin of insightsoftware will discuss:
- Why AI projects fail in production
- The path to production-ready AI
- How to eliminate hallucinations at the source

Stop treating AI hallucinations as an acceptable trade-off. Learn how to deliver consistent, verifiable, and auditable AI outcomes that move your organization from experimental pilots to production-ready intelligence that drives real business value.