An AI draft can sound complete while leaving important questions unanswered. Is the company actually certified? Is the named person available? Does a delivery promise match the operating plan? Clear sentences make these gaps harder to notice if the reviewer reads only for style.
Use AI to accelerate a first draft, then give the human review a defined job. The review should check the response against the solicitation, the underlying evidence, and the commitments the team is prepared to make.
1. Check the requirement, not just the paragraph.
Keep the solicitation open beside the draft. Does the response answer the actual question, use the requested structure, and include the required supporting material? A polished explanation of a nearby topic is still an incomplete answer.
Where federal negotiated procurement rules apply, FAR 15.305 anchors evaluation to the factors and subfactors stated in the solicitation. Use those criteria to frame the review rather than relying on a generic “looks good” assessment.
2. Separate facts from proposed commitments.
Mark factual statements about experience, qualifications, certifications, and results. Then mark promises about timing, staffing, service levels, or price. Facts need sources. Commitments need both a credible basis and approval from the person responsible for delivery.
For example, a past project may demonstrate that a team has completed similar work. It does not automatically establish that the team can meet a different schedule or operate in a new location. Treat that bridge as a decision to review.
3. Inspect the source itself.
A citation is a route to evidence, not proof that the evidence supports the sentence. Open the document. Check the entity, dates, scope, and context. Ask whether the wording in the proposal is narrower, equal to, or broader than what the source actually establishes.
Replace an unsupported number with a substantiated description. Confirm the named entity before reusing an affiliate’s experience. Remove an expired qualification rather than allowing the draft to present it as current.
4. Test the response for contradictions.
Review the executive summary, technical approach, staffing plan, schedule, and pricing together. Look for different versions of the same commitment. A change made in one section may leave the rest of the response inconsistent.
A short cross-section check is often more useful than another pass for adjectives. The buyer needs one coherent plan, not five individually persuasive versions.
5. Name the person who approves release.
Use a clear disposition for each issue: accepted with support, revised, removed, or escalated. Record who resolved it. The final approver should see the remaining exceptions and the exact package being submitted.
“Reviewed by AI” should never stand in for the business owner’s acceptance of the commitments. Human review works best when the reviewer has authority, source access, and time to change the response.
Use risk guidance as a starting point.
NIST’s Generative AI Profile describes risks and risk-management actions for organizations using generative AI. It provides useful context for building a review practice; it is not a certification of IntentBid or a guarantee that a particular draft is accurate.
NIST AI Risk Management Framework and Generative AI Profile · FAR 15.305