Operationalize Your Enterprise AI

5 Requirements for Moving From Experimentation to Trusted, Scalable Enterprise Operations

AI adoption is widespread, but few enterprises have turned pilots into repeatable business value. As AI shifts toward agents that retrieve information, invoke tools, and join operational workflows, the gap between a promising demo and a production-grade capability grows wider. Gartner forecasts that more than 40% of agentic AI projects will be canceled by the end of 2027 because of escalating costs, unclear business value, or inadequate risk controls.

This point of view introduces a five-part foundation for operational enterprise AI: understand, deploy, scale, control, and protect. It explains how governed business context, integrated deployment, workload-aware compute, sovereignty beyond data residency, and strong security and resiliency work together to shorten the path to production. You’ll also find a practical framework for identifying your biggest constraint and choosing a next step. Download the POV to learn how to operationalize AI with confidence.