For the last twenty years, the enterprise has had a fairly stable shape.
People sat behind laptops. Software lived in the cloud or on the network. We bought tools to make humans faster and more efficient at knowledge work. CRM, collaboration tools, ticketing systems, analytics dashboards, and identity systems existed to reduce friction for the person behind the keyboard.
That model is breaking down. Not because humans are going away, but because AI agents are changing how work gets done.
We are moving into what I call the agentic enterprise. And the most important shift is not that AI can now “do tasks.” It’s that humans are no longer the primary execution layer of knowledge work. They are becoming the managers of execution.
The Old Enterprise Optimized Human Throughput
In the cloud-enabled enterprise, software amplified people. The mental model was straightforward: humans think, software assists.
Even automation fit inside that frame. Scripts, workflows, and rules existed to remove repetitive steps, but the human still sat at the center. They initiated work, made decisions, and handled exceptions.
Identity and security followed the same pattern. Access controls existed to support people doing their jobs, with periodic reviews to clean up the mess after the fact. That world assumed a bounded number of actors, mostly humans, operating at human speed. That assumption no longer holds.
In the Agentic Enterprise, Humans Manage Agents
In an agentic enterprise, humans are managing fleets of AI agents that do knowledge work on their behalf.
The best analogy is an air traffic controller: A single human oversees many agents simultaneously. They set objectives, define constraints, and monitor outcomes. They review outputs. They intervene when needed. Occasionally they provide explicit approval before an action is taken.
Most of the time, the agents just operate.
This is not a future scenario. It is already happening in engineering, security, finance, support, and operations. The number of “actors” in the system is exploding, and most of them are non-human.
The limiting factor is no longer how fast a person can work. It is how effectively they can direct, govern, and trust autonomous systems operating at machine speed.
Efficiency Is the Wrong Goal
A common mistake is to frame this shift as an efficiency story. That misses the point.
You do not manage AI agents to make a human marginally faster. You manage them to increase human efficacy. One person can now direct work that previously required entire teams.
But that only works if three things are true:
- Inputs are controlled
- Outputs are observable
- Actions are constrained and accountable
Without those, you just get chaos.
This is where many early agent deployments fall apart. The models work. The demos are impressive. But once agents touch real systems, real data, and real permissions, the risk surface expands dramatically.
Identity Becomes the Control Plane
In a world of infinite agents, identity stops being a support function and becomes core infrastructure.
Every agent needs identity.
Every action needs authorization.
Every decision needs traceability.
This is how you prevent your own systems from working against you. The old model of identity assumed infrequent changes and periodic review. That model cannot keep up with agents that are created dynamically, act continuously, and interact across dozens of systems.
What you need instead is real-time, policy-driven identity governance that can operate at the same speed as the agents themselves.
What This Unlocks Next
If you get this right, the upside is real:
You unlock scale without linear headcount growth.
You unlock faster execution without sacrificing control.
You unlock systems that can adapt continuously instead of relying on quarterly cleanups.
But you only get there if you treat identity, security, and governance as foundational infrastructure for the agentic enterprise, not bolt-ons.
The enterprises that win will not be the ones with the most agents. They will be the ones that can safely operate them.
