Enterprise AI conversations tend to converge on a chatbot: a system that answers questions well but hands the actual work back to a human. The operational value of agentic AI comes from closing that loop — an agent that can look up a record, take an action in a source system, and close out a workflow, escalating only genuine exceptions.
Designing for this means treating the agent as a workflow participant with defined permissions and observability, not a black box bolted onto a chat window. Every action it takes should be logged, traceable, and reversible where the domain allows it.