How to scope an AI automation pilot for a manufacturing business

Choose a narrow task

An RFQ summary, a search over approved procedures or a draft customer reply can be easier to evaluate than an assistant expected to run the whole office. Describe the input and the output in plain language. If the task is fully rule-based, consider whether a conventional automation can do it more predictably.

Agree on data boundaries

List which documents and fields the workflow needs. Check provider handling, retention and access before sending confidential drawings, pricing or customer information. Give the pilot only the permissions it requires. Customer-controlled text and attachments are source material, not instructions that should override the workflow’s rules.

Keep important decisions with a reviewer

A useful pilot can prepare a draft while a person approves the price, delivery commitment or customer message. Require review before changing business records or issuing production instructions. Make missing evidence visible: the system should be able to ask for clarification rather than produce a confident guess.

Test failure as well as success

Use normal enquiries, incomplete documents, conflicting revisions and misleading text in attachments. Compare results with a human-reviewed baseline. Record accuracy, review effort and the consequences of errors rather than assuming every saved click creates a saving. Define who monitors the workflow and how to stop it when it behaves unexpectedly.

A checklist to take back to your team

• One task and a clear success measure
• Approved sources and limited access
• A reviewer for consequential actions
• Tests for missing, conflicting and malicious input
• A documented fallback and off switch