AI Agent Sprawl: Why It Happens and How to Contain It

AI agent sprawl is the uncontrolled growth of AI agents across teams, tools and clouds without a shared inventory, ownership or governance. It leaves gaps in visibility, security and accountability. The fix is to inventory every agent, assign identity and ownership, enforce policy, and monitor continuously.

What is AI agent sprawl?

AI agent sprawl happens when an organization accumulates AI agents without a shared way to track or govern them. An agent is software that takes actions toward assigned goals. The pattern resembles earlier application sprawl and shadow IT, where teams adopt tools outside central oversight. Shadow AI means AI tools used without organizational approval.

Why does AI agent sprawl matter now? 

Gartner’s 28 April 2026 press release predicts that an average global Fortune 500 enterprise will have over 150,000 agents in use by 2028, up from fewer than 15 in 2025. That is a prediction, not a measured outcome. Gartner also reports that only 13% of organizations believe they have the right AI agent governance. As enterprise AI transformation moves from pilots to production, managing agent growth becomes an operational priority.

Why does AI agent sprawl happen?

In Brillio’s view, sprawl begins because agents are easy to create and teams build them independently. Groups may choose different tools, clouds and AI agent orchestration platforms, and connect agents to data through MCP, the Model Context Protocol. Without a shared inventory, duplicate agents and unclear ownership follow. Gartner adds that blocking agents is not a long-term answer, because employees may turn to shadow AI, which carries greater risks.

What risks does agent sprawl create?

Gartner’s release names misinformation, oversharing and data loss as exposures from ungoverned sprawl. IBM’s Cost of a Data Breach Report 2025 (Ponemon Institute research across 600 organizations, 30 July 2025) found that high levels of shadow AI added USD 670,000 to average breach costs, an association rather than proof of cause. It also found that 97% of breached organizations with an AI-related security incident lacked proper AI access controls.

A SailPoint survey of 353 enterprise IT professionals by Dimensional Research (28 May 2025) found that 82% of organizations used agents but only 44% had policies to secure them. Of respondents, 80% reported unintended agent actions and 23% said agents had been tricked into revealing credentials. This is a vendor report with a small sample. OWASP’s Top 10 for Agentic Applications 2026 (9 December 2025) lists risks including Agent Goal Hijack, Tool Misuse and Exploitation, and Identity and Privilege Abuse.

How do you contain AI agent sprawl?

Gartner offers six steps. First, establish agent governance policies on who can build and share agents and which connectors are allowed. Second, build a centralized AI agent inventory, using AI TRiSM (AI trust, risk and security management) tools to discover and categorize agents, including shadow AI, then apply controls by risk level. Third, define agent identity and permissions and manage the agent life cycle, retiring redundant agents.

Fourth, govern the information agents can reach so data stays current and is not overshared. Fifth, monitor behavior, check policies, detect anomalies and correct agents that exceed their scope. Sixth, promote responsible use through training and communities of practice.

An enterprise AI governance platform should cover discovery, ownership, access, policy enforcement and monitoring, and an AI agent registry gives teams one shared record. The goal is to govern agents, not block them. These steps are Gartner’s recommendations; how to apply them depends on an organization’s risk tier and agent autonomy.

How does Brillio’s ADAM address AI agent sprawl?

Brillio sells related offerings, so weigh this section accordingly. ADAM is part of Brillio’s Enterprise AI Accelerator, and the page for Agentic Data and Application Management describes bringing agents across clouds, teams and tools under one governed platform with a single Control Tower.

The page describes a discovery scanner that maps existing AI and charts a governed path, an AI Registry that is the system of record for AI assets, agents, MCPs, prompts and skills, and governance applied while agents are built, before publishing and while they run. It also says ADAM extends existing agents, tools, models and platforms rather than replacing them. When assessing any agentic AI platform for enterprises, including ADAM, put the same questions to every provider.

Frequently asked questions

What is AI agent sprawl?

AI agent sprawl is the unmanaged growth of agents across teams, tools and clouds. Ownership, permissions, data access and behavior become hard to track when agents lack a shared inventory and consistent governance.

How do you stop AI agent sprawl without slowing teams down?

Make discovery, registration, permissions and monitoring part of normal development. Risk-based policies let teams use approved agents while the organization keeps visibility and control, instead of relying on blanket restrictions that push work into shadow AI.

Is shadow AI the same as agent sprawl?

Not exactly. Shadow AI is AI use without organizational approval, while agent sprawl is uncontrolled growth of agents. Shadow AI can feed sprawl when employees create or use agents outside approved oversight.