고객 데이터를 넘어 : CX에서 AI 에이전트가 놓치고 있는 컨텍스트의 토대

This IDC Perspective examines why AI agents deployed across customer experience (CX) functions like marketing, sales, advertising, digital commerce, customer support, and field service systems require dedicated context foundation beyond unified customer data. It defines the three architectural foundations - knowledge graphs, semantic definitions, and context management - that enable agents to reason over shared context, coordinate actions across functions, and make autonomous decisions. The document provides guidance for both business and technology buyers evaluating context readiness for AI agents in CX."Customer data platforms gave us unified profiles, but that foundation alone is not sufficient for AI agents to make autonomous decisions," said Tapan Patel, research director, AI-Enabled Customer Data and Analytics, IDC. "AI agents need a next layer - one that provides detailed understanding into CX relationships, shared business logic across functions, and runtime context that reflects customer intent, life-cycle stage, and prior actions to deliver real value."

Executive Snapshot

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Situation Overview

• Definition and characteristics of AI agents
  • Knowledge graphs for understanding relationships
  • Semantic definition as shared business logic
  • Context management for customer decisions
• CX supervisory agents and their need for context management, semantic definition, and knowledge graph

Advice for the Technology Buyer

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