Organizations deploying AI agents may face significant financial exposure if systems are allowed to consume computing resources, model tokens, or external services without effective limits. OWASP identifies unbounded consumption as the sixth risk in its Top 10 for Large Language Model Applications.
The issue can arise when an AI-enabled application repeatedly calls a language model, initiates long-running tasks, processes unusually large inputs, or triggers costly third-party tools. In agent-based environments, the risk may increase because a system can autonomously chain together actions and requests in pursuit of an assigned goal.
Unlike a conventional application with predictable transaction volumes, an agent may generate variable workloads depending on user prompts, available tools, retry behavior, and the complexity of its reasoning process. A poorly constrained workflow could therefore create unexpectedly high usage charges or place pressure on internal infrastructure.
Potential business impact
Runaway consumption can affect more than an organization's cloud or AI API bill. Excessive requests may reduce service availability for other users, exhaust rate limits, and make it harder for security and operations teams to distinguish legitimate activity from abuse. Attackers could also attempt to exploit expensive model operations or automated tool calls to cause financial harm.
Controls to consider
- Set spending, token, request, and execution-time limits for AI workloads.
- Apply rate limiting and quotas by user, tenant, workflow, and agent.
- Require approval or additional checks before high-cost actions are performed.
- Monitor model usage, tool invocations, retries, and abnormal task duration.
- Design agents to stop safely when budgets, time limits, or error thresholds are reached.
As enterprises expand use of autonomous and semi-autonomous AI systems, cost governance is becoming a security and resilience concern as well as a financial one. Clear boundaries and continuous monitoring can help reduce the chance that an AI agent turns an otherwise useful automation into an uncontrolled expense.