Quality Assurance for AI-Generated Proposal Content Under CMMC

AI-assisted proposal writing is becoming standard practice in GovCon. Tools can draft past performance narratives, generate technical approach sections, and produce management plans in a fraction of the time manual writing requires. But speed without quality control creates two risks: submitting inaccurate content that loses evaluations, and creating compliance gaps that fail CMMC assessment.

This article extends our Compliant AI Proposal guide with a practical QA framework for AI-generated content.

The Two Risk Categories

Quality Risks

• Hallucinated facts: AI may invent contract numbers, inflate metrics, or fabricate past performance details
• Generic language: AI output often reads as plausible but generic, lacking the specificity evaluators reward
• Inconsistency across sections: Different AI-generated sections may contradict each other on team size, approach, or timeline
• RFP non-compliance: AI may miss specific RFP instructions about format, page limits, or required content

Compliance Risks

• CUI in AI training: If CUI was sent to a non-compliant AI service, the content was generated in violation of CMMC
• No audit trail: If you can't demonstrate how AI content was generated and reviewed, you have an accountability gap
• Cross-program contamination: AI accessing data from one program may leak information into content for another

The QA Process

Step 1: Pre-Generation Verification

Before generating any content, verify:

• The AI tool is approved for CUI processing (within your CMMC boundary)
• RAG sources are isolated to the relevant program (see RAG isolation requirements)
• Source documents are current and authorized for use in this proposal

Step 2: Factual Accuracy Review

Every factual claim in AI-generated content must be verified against source documents:

• Contract numbers, values, and dates match official records
• Performance metrics are accurate and sourced from CPARS or internal records
• Team member qualifications and certifications are current
• Referenced past performance is from your verified database, not AI-generated

Step 3: RFP Compliance Check

• Content addresses every evaluation criterion in the RFP
• Page limits and formatting requirements are met
• Cross-references between sections are consistent
• Required certifications and representations are accurate

Step 4: Audit Trail Documentation

For CMMC compliance, document the AI content generation process: