Agentic AI marks a significant shift in enterprise AI, moving from answering questions to doing real work. And unlike previous technology waves that offered capabilities that teams could leverage, AI agents deliver results. This changes the adoption curve. Once agents demonstrate tangible value at the task level, they proliferate quickly.
During our own AI development and adoption journey, scaling from a handful of pilot agents to nearly 2,000 AI agent instances spanning over 40 agent types happened relatively quickly. Among my peers (CTO and CIO, especially in large companies), the same pattern emerges. AI Agent proliferation is real.
As the deployment scales, the operating environment becomes more complex, often faster than most organizations expect. If this complexity is not deliberately managed, it can create hidden costs, duplicate solutions, inconsistent controls, fragmented data access, and an increasing maintenance burden that ultimately diminishes the value agents are expected to deliver.
