If our team uses generative AI to produce client deliverables, research briefs, or project estimates, where does the machine work end and human accountability begin so we never deliver flawed work to a client?

Question

Tyler Smith · Accepted Answer

AI can assemble information, draft raw copy, structure research tables, and calculate preliminary formulas. It cannot take responsibility for being wrong. That burden belongs exclusively to a named seat on your Accountability Chart.

To protect client trust and brand reputation, establish a permanent operational boundary between automated production and human verification. Treat generative output the same way you would treat raw work handed in by an entry-level intern: useful as a starting draft, but completely unready for client eyes without senior review.

Operationalize this standard through three explicit rules:
- The machine drafts, the human signs. Every AI-assisted deliverable, estimate, or technical brief must have a human reviewer who verifies every fact, citation, and dollar amount. That person is 100 percent accountable for the final product.
- Fact-check raw numbers against source databases. AI tools frequently hallucinate math, distort contract terms, or miscalculate margins. Mandate that all financial formulas and project timelines are manually validated against verified internal spreadsheets before presentation.
- Enforce GWC for the review seat. The employee responsible for reviewing automated drafts must have the capacity and skill to spot subtle errors. If a team member does not Understand, Want, and have the Capacity to do the work manually, they cannot be trusted to inspect machine output.

Clients pay for judgment, risk management, and accountability. Let technology accelerate your preliminary research and formatting, but never allow an automated output to leave your company without rigorous human sign-off.