AI workflow
Definition
An AI workflow is a fixed series of steps, set in advance by a person or by code, in which an AI model handles one or more of the steps. The steps run in the same order every time, which makes a workflow easy to test and check.
By Ronan Liedmeier, fractional head of growth and course author · Published 17 October 2026 · Last updated 17 October 2026
Also called: AI automation, LLM workflow
Most of the AI that pays off in daily work looks like this: something triggers it, a saved prompt does the work, and a person checks the result before anything goes out.
How it differs from an AI agent
Anthropic defines workflows as systems where models and tools are "orchestrated through predefined code paths". In an AI agent, the model decides its own steps as it goes. The same guide says workflows suit well-defined tasks where you want consistency.
A workflow can be as simple as a saved prompt you run by hand after each meeting, or a no-code automation in a tool like n8n that fires when a form is submitted.
Example
An operations lead spends about 30 minutes after every client meeting writing the recap. She sets up one workflow: the meeting transcript lands in Notion, a saved prompt drafts the recap and action items, and she reviews it before it is sent. On the first real run, her review catches an action item assigned to the wrong teammate.
Common mistake
People set up ten workflows in the same week, and most of them are forgotten within a month. Add one at a time, attach it to a habit you already have (after each call, Monday morning planning), and keep a human check on anything that sends or deletes.
Learn it in AI Academy
- Everyday AI Workflows: The Recipe BookBeginner · 12 min
- The Agentic Build PatternExpert · 8 minFree
Related terms
- AI agent
- An AI agent is an AI system that works toward a goal by choosing its own next steps: it picks a tool, uses it, looks at the result and repeats until the task is done. You set the goal and the limits, and the agent works out the path.
- No-code automation
- No-code automation is building workflows that move data between apps by connecting visual blocks instead of writing code. Each workflow starts with a trigger, like a new email, and runs a set of steps, like creating a task, every time that trigger fires.
- Human in the loop
- Human in the loop is a setup where an AI system pauses at set points so a person can approve or correct its work before it takes effect. It is used for actions that are hard to undo, such as sending emails to customers or moving money.
- AI orchestration
- AI orchestration is coordinating the steps around an AI model so a task runs reliably from start to finish: what starts it, which tools and data it gets, what happens when a step fails, and when a person must approve. The model is one step in that chain.