Our employees are using AI to draft client deliverables, but nobody is checking the work before it goes out the door. How do we build an internal AI policy that mandates human verification without slowing delivery to a crawl?

Question

Tyler Smith · Accepted Answer

Establish a strict principle on your Accountability Chart: every output generated by AI must have a named human who owns complete accountability for its accuracy. If an employee uses an AI tool to draft a technical memo, audit report, or customer deliverable, that employee remains one hundred percent liable for errors, hallucinations, and tone.

Your internal AI policy should fit on one page and establish three clear rules:
- The Source Rule: Never paste raw, non-anonymized client proprietary data or trade secrets into public tools that retain data for model training.
- The Review Rule: AI is a junior assistant, not a manager. The human whose name appears on the deliverable must inspect every fact, link, and calculation.
- The Accountability Rule: Blaming an AI model for an incorrect deliverable is treated exactly like blaming a spreadsheet error. It is human negligence.

To keep this from slowing delivery down, standardize where AI fits in your documented Core Processes. Require team members to use AI for initial outlines, raw research aggregation, and formatting, but institute a ten-minute verification checklist before release. If an employee cannot verify the work within that checklist, the workflow is flawed. You do not need a twenty-page policy manual. You need unambiguous personal accountability anchored directly into your operating process.