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How to build an AI-assisted approval workflow

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Written by Errin Veney

Before you begin

  • Start with one workflow, one source of information, and a named reviewer.

  • Use sanitized sample data while you are testing the structure and review loop.

Build the workflow

An approval workflow should not simply say yes or no.

It should show

  • The request

  • The rule that applies

  • The recommended decision

  • The evidence used

  • Missing information

  • The person responsible for the final decision

Starter prompt

“Build an approval app for [role]. The user submits [request]. Compare it with [policy or rule set]. Recommend approve, needs more information, or reject. Show the exact rule and evidence. Any exception or low-confidence case must go to [reviewer]. Do not execute the action automatically.”

This pattern works for access requests, vendor reviews, expenses, contracts, exceptions, and operational decisions.

Start in shadow mode: let the app recommend while the existing process remains in control. Compare the recommendations before automating any action.

Common mistakes

  • Automating approval before measuring recommendations.

  • Returning only yes or no without the rule and evidence.

  • Leaving exception ownership undefined.

Frequently asked questions

Can I use this template for a different industry?

Yes. Replace the role, input, rule set, output, reviewer, and prohibited actions. Keep the first workflow bounded and inspectable.

When should I use production data?

After the structure works with safe examples and the required permissions, security, retention, and review controls are in place.

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