AI Application Delivery Breaks Down Between Experimentation and Production
theCUBE, Wednesday, March 25th, 2026
According to industry research, only about 5% of enterprise AI pilots reach full production, while the majority stall in experimentation. As organizations accelerate investments in AI, a growing gap is emerging, not in model capability, but in the ability to operationalize AI systems reliably at scale.
In this episode of AppDevANGLE, I spoke with Ketan Umare, Co-Founder and CEO at Union.ai, about why AI projects fail to transition from proof-of-concept to production, and what needs to change in how developers build, iterate, and operationalize AI-driven applications.
Our conversation explored the shift from deterministic software to non-deterministic AI systems, the growing importance of rapid iteration, and why infrastructure and orchestration models must evolve to support AI-native development.