From Experiments to Impact: Why Enterprise AI Needs Agentic Systems

Enterprise AI reveals a critical gap: POCs succeed but production deployments fail because individual productivity gains don't translate to system efficiency. This article explains why treating AI as an ad-hoc tool inherently fails at scale and demonstrates how agentic systems—with defined roles, structured workflows, and clear ownership—unlock the real enterprise value that most AI initiatives promise but rarely deliver.