These sources examine the emergence of agentic AI, which consists of autonomous systems capable of reasoning and executing complex workflows without constant human oversight. Research highlights a critical governance crisis known as agent sprawl, where the rapid proliferation of unmanaged AI tools leads to redundant costs and security vulnerabilities. To address this, experts propose the Agentic AI Governance Maturity Model (AAGMM), a framework designed to help organizations move from disorganized, ad-hoc deployments to optimized, self-improving systems. Leading technology firms are already shifting toward an Agent-as-a-Service (AaaS) business model, emphasizing outcome-based pricing over traditional software subscriptions. Real-world implementations, such as Cisco’s MyAgent rollout to 90,000 employees, demonstrate how internal orchestration layers can coordinate specialized sub-agents while maintaining strict safety guardrails. Ultimately, the literature suggests that successful adoption requires a strategic move toward centralized control and formal oversight to turn technological potential into measurable business value.

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