AI Automation
AI automation is a workflow where an AI model handles a step that used to need a person, like reading an email and deciding what to do with it.
AI automation means letting an AI model handle a step in a workflow that used to need a person to read something and decide.
Example
A customer emails: "I got charged twice, please fix this." A plain automation can forward every email containing the word "charged" to billing. An AI automation reads the email, understands it's a refund request, pulls out the order number, and drafts a reply for someone to check.
How it differs from regular automation
Regular automation follows fixed rules: if this field says X, do Y. That breaks when the input is messy, like a free-form email, a scanned PDF or a photo.
AI automation adds a step where a model, usually a large language model, reads the messy input and turns it into something the rest of the workflow can use: a label, a summary, a filled-in record or a draft.
The parts
- Trigger: the event that starts the workflow, like a new email or a form submission.
- AI step: the model reads, sorts, pulls out data or writes something.
- Actions: what happens with the result, like updating a CRM, posting in Slack or adding a row to a sheet.
- Review: a person checks the cases the model isn't sure about.
The workflow doesn't get better on its own. It gets better when someone looks at the mistakes and changes the prompt or the rules.
Common uses
Sorting email, drafting content, pulling data out of documents, customer support, qualifying leads and processing documents.
To build one, start with how to build your first AI automation.