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What Is an Agentic Workflow? How AI Agents Get Work Done

27 June 2026 · 2 min read

Once you understand what an AI agent is, the natural next question is: how does it actually get a multi-step job done without someone scripting every step in advance? That’s an agentic workflow.

The core idea: a loop, not a script

A traditional automated workflow is a fixed sequence: step 1, then step 2, then step 3, always in that order, regardless of what happens along the way.

An agentic workflow instead runs a loop:

  1. Plan — the agent decides what needs to happen to reach the goal.
  2. Act — it takes one step, using a tool (send an email, query a system, read a document).
  3. Observe — it looks at the result.
  4. Reason — based on that result, it decides the next step — which might not be the one it originally planned.

That loop repeats until the goal is met. The workflow adapts to what it finds, instead of blindly executing a script.

A concrete example: handling a refund request

A customer emails asking for a refund on a damaged product. An agentic workflow might:

  1. Read the email and identify it as a refund request.
  2. Check the order in the order-management system.
  3. Check the refund policy for that product category.
  4. If it’s a clear-cut case: approve it, trigger the refund, and reply to the customer.
  5. If something’s ambiguous — order outside the return window, high value, prior disputes — escalate to a human with a summary, instead of guessing.

A fixed script would either fail outright on the ambiguous case or need a programmer to add a new rule for every exception. The agentic version reasons about the exception in the moment.

Why this matters for real business processes

Most real workflows aren’t perfectly clean. Customers phrase things differently, data is sometimes missing, edge cases pile up. Agentic workflows are valuable precisely because they can handle that messiness without a human babysitting every case — while still knowing when to hand off to a person.

It’s rarely just one agent

For anything beyond a simple task, you typically don’t want one agent trying to do everything. You want specialised agents handling different parts of the job and coordinating with each other — which is exactly what multi-agent orchestration is about.

Curious whether one of your processes is a good fit for this? Get in touch — we can tell you honestly whether it’s worth building.