Neither generative AI nor agentic AI is universally better for customer service - they serve different purposes and are most effective when deployed together. Generative AI excels at content-oriented tasks: drafting suggested agent responses, summarizing conversations, and generating knowledge content, all of which benefit from human review before finalization. Agentic AI is better suited for end-to-end task completion: autonomously resolving a customer's request by executing the necessary multi-step actions across systems without requiring human intervention at each step. Organizations focused on improving agent productivity and content quality typically prioritize generative AI applications first, since they integrate more easily into existing human-supervised workflows. Organizations focused on deflecting volume and achieving full automation for routine transactions need agentic AI capabilities. The most mature enterprise CX platforms deploy both in combination, matching each technology to the tasks it handles best.
Comparisons