Agent sprawl is what happens when teams create many AI agents with no shared inventory, ownership, or rules. For agencies, it puts client data and brand accounts in the hands of software nobody is tracking.
Also known as agent proliferation, rogue agents
Agent sprawl is the uncontrolled growth of AI agents inside an organization. It follows the same pattern as shadow IT and spreadsheet sprawl: building an agent is easy, so people build many, and no one keeps a list of what exists, what it can access, or who is responsible for it.
Each agent may be small and useful on its own. The problem is the sum. Overlapping agents contradict each other, abandoned ones keep running with old permissions, and nobody can answer the basic question of which agents are touching which systems right now.
Agencies work across many client accounts, tools, and logins, which makes sprawl riskier than it is in a single-product company.
Access creep. An agent connected to one client’s ad account for a test often stays connected long after the test ends, with the same permissions.
Inconsistent output. Three account teams each build their own reporting agent. Each calculates a metric a little differently, and the client sees three versions of the truth.
Cost and accountability. Unused agents still consume tokens and tool calls. When one posts something wrong, no one is sure who owns it.
Six months into AI adoption, an agency audits what its teams have built and finds 41 agents. Eleven do roughly the same job, a weekly performance summary. Four still hold credentials to a client account that left the roster in the spring. One, built by an intern, is posting draft captions to a shared Slack channel that nobody reads. The agency now keeps a simple register with an owner, a purpose, the systems each agent touches, and a review date, and retires anything without a named owner.
The automations and agents module of the workshop teaches you how to build AI workflows that compress the busywork without taking the craft out of the studio.