For enterprise CX, the key difference between agentic AI and generative AI lies in autonomy and action. Generative AI produces content - drafting a response, summarizing an interaction, generating a knowledge article - in reaction to a specific prompt, with a human typically reviewing or approving the output before it takes effect. Agentic AI operates with greater independence, making sequential decisions and executing multi-step actions across systems to accomplish a defined goal, such as fully resolving a customer's account change request without human review at each step. Enterprise CX platforms increasingly combine both: generative AI handles content-oriented tasks like summarization and response drafting, while agentic AI handles end-to-end transaction execution for autonomous resolution use cases. The governance requirements differ significantly as well, since agentic AI's autonomous actions require more rigorous scope definition, validation, and audit logging than generative AI's content suggestions.
Comparisons