Definition
An agentic workflow is a process in which an AI agent plans and carries out several steps, using tools and data, toward a defined goal, with human checkpoints where needed.
Unlike a single prompt and response, an agentic workflow lets the system read information, decide on the next step, call a tool and check the result, repeating until the task is complete or it needs a person.
Good agentic workflows have clear boundaries: an allow-list of tools, permission levels, timeouts and a defined handoff.
Why it matters
A single prompt can draft an email. Real business tasks need several steps: find the right record, check a rule, update a system, notify someone. Agentic workflows handle that chain, which is where most of the time in operations actually goes.
The risk grows with the autonomy, so the design work is mostly about limits: which tools the agent may call, what it may change without approval, how long it may run and when it must stop and ask.
An example
A customer emails asking to change a delivery address. The agent identifies the customer and order, checks whether the order has shipped, updates the address if it has not, and confirms by email. If the order has already shipped, it opens a ticket for the logistics team with the context attached, instead of guessing.
Illustrative example, not a client project.
Common questions about Agentic workflow
How is an agentic workflow different from traditional automation?
Traditional automation follows fixed rules written in advance. An agentic workflow can read unstructured input, choose the next step and recover from small surprises, within boundaries the business sets.
Are agentic workflows safe to run in production?
They can be, when tool access is allow-listed, actions that change money or customer data need approval, every step is logged and there is a clear handoff to a person.
Related terms