Agentic AI

Agentic AI refers to artificial intelligence systems characterized by autonomy, goal-directedness, and the capacity to take sequential actions over time to accomplish objectives. The term distinguishes systems that actively pursue goals — planning, using tools, adapting to feedback, and persisting across multiple steps — from passive AI models that simply respond to individual inputs. Agentic systems typically combine reasoning, memory, tool use, and some form of self-monitoring or reflection to navigate toward a desired outcome.

For commerce and enterprise technology, agentic AI represents a shift from AI as a productivity enhancer to AI as an operational actor. Agentic systems can manage catalog enrichment pipelines, execute A/B pricing experiments, process returns end-to-end, or coordinate across ERP, CRM, and OMS systems to fulfill complex business rules — all with limited human initiation. This shift introduces new architectural requirements (reliable tool integrations, guardrails, audit trails) and new governance questions around accountability when an AI takes consequential actions on behalf of an organization. Understanding agentic AI is foundational for leaders planning how to responsibly scale automation across their commerce stack.