Generative AI becomes operationally valuable when it can use trusted context and complete a bounded workflow. Agentic AI extends that idea by allowing a system to plan and call tools, but additional autonomy also creates additional failure modes.
Define the agent’s operating envelope
Specify the tools an agent may call, the data it may read, the actions it may take and the conditions that require approval. An agent may draft a supplier response, but it should not send a contract or change a payment record without approval.
Ground answers in enterprise context
Retrieval quality, document freshness and access controls matter as much as model choice. Use source-aware retrieval, record citations where appropriate, and keep role boundaries intact. A fluent answer that uses the wrong policy is still an operational failure.
Evaluate the workflow, not just the response
Include tool selection, plan quality, refusal behaviour, latency, cost and recovery from partial failure. Test adversarial prompts and ambiguous requests, and keep a trace of every model call and tool action.
A safe default
Start with read-only tools and recommendation mode. Add write access only after stable evaluations, clear rollback paths and an accountable owner are in place.
