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What is the difference between AI automation and workflow automation?

Workflow automation follows fixed rules — if this happens, do that. AI automation handles work that needs judgement or language, such as reading an unstructured email or classifying a request. Most business automation is workflow automation, and using AI where a rule would do makes the system more expensive, slower and less predictable.

Workflow automation
Deterministic. Same input, same output, every time
AI automation
Probabilistic. Handles ambiguity, can be wrong
Cost difference
AI adds per-use cost; rules do not
Rule of thumb
If you can write the rule down, do not use AI

Use workflow automation for

  • Moving data between systems on a schedule or trigger
  • Sending an invoice when a job is marked complete
  • Matching a payment to an invoice by reference
  • Escalating anything untouched after 24 hours
  • Generating a document from a template

Use AI for

  • Reading an unstructured email and extracting the request
  • Classifying enquiries where the categories overlap
  • Drafting a first response for a human to approve
  • Pulling figures out of inconsistent PDFs and scans
  • Summarising a long thread for whoever picks it up next

Why the distinction matters commercially

A rule-based automation runs at effectively no marginal cost and behaves identically every time. An AI step costs money per run and can produce a different answer to the same input. In a finance process, that difference is the whole argument. Use AI where ambiguity is genuinely present, and ordinary code everywhere else.

What most real systems look like

A mix. AI reads the messy input at the front, then hands structured data to deterministic rules that do the actual work. That gives you the flexibility where you need it and predictability everywhere else.

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