Agent sprawl: How to manage agent proliferation in the enterprise

Enterprise AI tools are enabling more employees and teams to independently create agents, encouraging experimentation and potentially producing reusable solutions, but this decentralized growth can lead to “agent sprawl” when organizations lack visibility, governance, and discovery mechanisms for their expanding agent portfolios. Companies commonly address the issue through centralized, federated, or hybrid operating models supported by agent registries that track ownership, usage, and permissions, although strict efforts to eliminate duplicate agents may inhibit innovation. The article proposes allowing temporary “challenger” variants to compete with existing agents through time-bounded, evidence-based evaluations using measures such as reliability, task quality, token cost, and latency. In a commercial lending example, a lower-cost specialized agent could replace an incumbent, be retired, or coexist if it performs best on a distinct subset of work. This approach aims to preserve decentralized experimentation while ensuring that agents remain only when they demonstrate a meaningful advantage.

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