AI agents need to mature through careful experimentation and structured governance to prevent agent sprawl, which parallels shadow IT in enterprise software by causing inefficiencies and multiplying risks. Without proper oversight, agents proliferate in isolation, leading to duplicated efforts, wasted resources, and compliance gaps. To tackle this, organizations must enforce governance, assign clear ownership, standardize processes, and audit usage to consolidate redundancies and optimize resources. Centralized control, clear accountability, and consistent measurement ensure agents deliver measurable business value and scalable innovation. Lifecycle management, including validation and operationalization, is crucial for transforming agents from isolated experiments into strategic, scalable resources.