Where workflow automation helps — and where AI is the wrong tool
A simple way to identify automation opportunities and decide between rule-based workflows and AI.
Not every repetitive task needs AI. Many of the most reliable automations are simple rules: when a form is submitted, create a record and notify a person. AI becomes useful when the input is messy language or varies too much for fixed rules.
Good candidates for automation
- The task happens often enough that time savings add up.
- The steps are consistent and can be written down.
- Mistakes are detectable and can be corrected.
- The inputs are available in digital form.
When rules are enough
Moving data between systems, sending reminders, routing approvals and generating documents from templates rarely need AI. Rule-based automation is cheaper, more predictable and easier to audit.
When AI earns its place
Extracting information from varied documents, classifying free-text requests or answering questions from a large set of internal documents are tasks where language models can help. They can also be wrong with confidence, so outputs that matter should be reviewed by a person, at least until accuracy is proven on real cases.
Design for failure
Every automation will eventually meet input it does not handle. Log what happens, alert someone when it fails, and make sure there is a manual path to finish the job. An automation that fails silently can do more harm than the manual process it replaced.