This 2-page brief positions Agentic Data Management (ADAM) for Customer Support as a way to fix traditional IVR limitations such as weak conversational personalization, long wait times, inconsistent interactions, manual effort for agents, and low visibility for proactive service. It proposes a set of AI agents to automate and optimize support, including a Routing Agent to improve workforce allocation and call routing, sentiment analysis to adapt responses to customer emotion, a personalization agent to tailor replies using past interactions, an auto-transcript agent to capture and summarize conversations for future retrieval, and predictive analytics to recommend next-best actions that reduce call volumes. It also describes “superhuman agents” that support human reps with real-time suggest

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