AI workflow automation vs. Zapier: what's the difference?
Zapier connects apps. AI workflows make decisions. Here's when you need each - and where the line is.
If you've used Zapier or Make, you already understand half of automation: when X happens, do Y. That's powerful, and for a lot of tasks it's all you need. But it has a ceiling - and that ceiling is where AI workflows begin.
Rules-based automation: great until it has to think
Tools like Zapier are excellent at moving data on fixed rules. The catch is that they can't handle ambiguity. The moment a task needs a judgement - 'is this invoice a duplicate?', 'which team should this go to?', 'is this reply urgent?' - a rigid rule either guesses or breaks.
AI workflows: read, decide, act
An AI workflow can read unstructured input (an email, a document, a message), apply your rules with judgement, and act - while flagging anything it's unsure about to a person. It's the difference between a wire that carries data and a teammate that handles a task.
- Use rules-based automation for simple, predictable app-to-app moves.
- Use AI workflows when the task needs reading, judgement or exceptions handled.
- Often the best system uses both - rules for the plumbing, AI for the decisions.
The right question isn't 'which tool?' - it's 'what does this task actually require?' We design around that, then build and run it, so you're not left maintaining a brittle chain of steps.