Work laid out as a sequence
A workflow organizes the steps between the start and completion of a job, together with their order and conditions.
Receive an enquiry, classify it, notify the right person, draft a reply — that sequence is a workflow. It can be a procedure a person follows or something a tool runs automatically.
What AI adds
Traditional automation is good at repeating a fixed rule precisely: if A, then B. Adding AI brings in steps that fixed rules handled badly — reading the meaning of a message, classifying it, drafting a reply, examining an image.
- Transcribe a meeting recording, summarize it, and file it
- Classify incoming enquiries and send a draft answer to the owner
- Collect news, remove duplicates, and organize it into article candidates
- Build a document from form input and send it after review
Tools such as n8n and Power Automate let you wire apps, APIs, and AI models together visually to build these.
How it differs from an AI agent
A workflow follows a path decided in advance. An AI agent decides what to do next itself, based on the goal it was given.
Real systems often combine them: fix the order of steps and the safety checks as a workflow, and delegate specific judgments — how to write something, how to research it — to an agent. That is more predictable than handing everything to the model.
Building one safely
A long workflow built in one go is hard to debug when it fails. Start with one input and one output, watch the logs, and add steps.
Put a human check before anything hard to undo — sending mail, publishing, deleting, paying. Also settle how API keys and credentials are stored, what data goes to outside services, what happens on retry, and how costs scale.