There's one conversation about AI agents that isn't getting enough attention, and it's the one that matters most.
What happens after they're inside your systems?
Agents don't wait. They move across tools, trigger actions, and make decisions in sequence without a human in the loop at each step. That's the value proposition. It's also the risk surface.
Enterprise deployments tend to define access and stop there. What an agent is actually mandated to do, and where it stops gets treated as a detail to figure out later. An agent that can touch your systems without a clearly defined mandate is an open variable in your infrastructure, and open variables in large systems have a habit of becoming expensive problems.
A claims processing agent should be able to verify a policy, cross-reference a report, flag a discrepancy for human review. The moment it can initiate a payout above a threshold or change underlying policy terms without a second signature, the organisation has handed over a decision it probably didn't mean to. Defining that boundary is a governance decision, and it needs to be made before anything runs.
One agent is manageable. A fleet of agents is a department, and without consistency within that department, issues build quickly.
When agents don't behave predictably across a system, data drifts, decisions conflict, and the organisation inherits the mess.
Scope creep in a human team is visible. You can catch it, address it, course correct. In an agentic system, it compounds until it becomes structural.
Give agents the smallest footprint that gets the job done. The governance work feels slow upfront, but it's considerably slower to unpack later.
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