Employees are increasingly using generative AI to draft internal memos, client summaries, and research, but errors are slipping through. What specific verification rules should our company AI policy enforce so individuals remain fully accountable for the accuracy of their work?

Question

Tyler Smith · Accepted Answer

A practical AI policy does not require dense legal jargon. It requires an uncompromising standard of individual accountability. When team members use AI to draft proposals, synthesize data, or write internal memos, they often fall into passive sign-off habits, assuming the software is always correct. Your policy must eliminate this assumption.

Establish the absolute rule of single-point accountability: the person whose name is on the document owns every word, number, and calculation inside it. Claiming that the AI hallucinated a statistic, pulled the wrong project rate, or distorted a client request is treated as personal negligence, not a technical bug. If you hit send, you own the outcome.

To enforce this standard, implement a simple verification protocol across all Core Processes:
- Zero copy-paste pass-through: Team members may not transfer raw AI text directly into client deliverables or internal leadership reports without line-by-line review.
- Fact-check all citations: Any data point, quote, or metric generated by a prompt must be verified against an original, verified internal source file before distribution.
- Transparent attribution: Internal working documents must briefly note if AI was used for synthesis, allowing reviewers to gauge where scrutiny is required.

By anchoring output quality to individual seats on your Accountability Chart, you preserve team initiative while protecting the business from sloppy hallucinations and compromised standards.