For Defense Industrial Base (DIB) organizations preparing for CMMC, AI offers several possibilities: faster answers, streamlined documentation, and reduced administrative burden.
But not all AI is created equal.
When it comes to something as specialized as CMMC, using generic AI tools can introduce more problems than solutions. To use AI effectively in your compliance journey, it’s crucial to understand both the potential and the risks.
Where AI Can Make CMMC Easier
CMMC compliance — and the NIST 800-171 framework it’s based on — is notoriously complex. Control language can be dense and ambiguous, turning preparation into somewhat of a guessing game.
AI can help in a few key ways:
- Breaking down confusing controls: Instead of guessing what a certain control or objective is asking for, AI can provide an expert-backed explanation in plain language.
- Reviewing your implementation statements: AI can offer feedback on how well your draft aligns with assessment objectives, flagging gaps or suggesting improvements.
- Speeding up documentation: You can work with AI to draft and revise SSPs, POA&Ms, and policies faster and with more accuracy.
- Answering questions in real time: AI can function as an on-demand CMMC expert, ready to answer your questions whenever needed.
- Customized control implementation: AI is able to offer tailored suggestions for implementing controls based on your organization’s unique environment and constraints.
- Cross-framework mapping: AI can help map CMMC controls to other frameworks for comprehensive compliance management.
But all this only works if the AI understands CMMC.
The Risks of Using General-Purpose AI for CMMC
It’s tempting to turn to public tools like ChatGPT or Gemini when you’re stuck on a CMMC control, but that can backfire. Most general-purpose AI models are not trained specifically on compliance frameworks. That means they may:
- “Hallucinate” information that sounds confident but is flat-out wrong.
- Pull outdated or irrelevant advice from internet sources.
- Miss critical nuances in control language, leading to incomplete or incorrect implementation.
And unfortunately, assessors won’t accept “ChatGPT said so” as justification.
For AI to be useful in the CMMC world, it needs to be accurate, trustworthy, and grounded in actual assessor knowledge, not assumptions.
Purpose-Built AI for CMMC: Why It Matters
That’s where platforms like CUIComply come in. CUIComply includes Copilot, an AI assistant created by Certified CMMC Assessors and trained exclusively on authoritative sources like NIST 800-171, CMMC assessment guides, and our assessors’ own analysis.
What makes Copilot different:
- It doesn’t guess. Copilot doesn’t pull from the open internet or scrape Reddit for answers. It only responds based on vetted content fed directly into its training environment.
- It knows the framework. Every suggestion is rooted in the language, logic, and intent of actual CMMC controls.
- It’s built for your unique environment. Copilot integrates into CUIComply’s workflows, meaning it can respond to your questions in context, not as a one-off tool.
So when you use Copilot to review an implementation statement or ask for clarification on a control, you’re not relying on AI that sounds right. You’re working with a system that knows what’s right.
The Bottom Line
AI can absolutely help streamline your CMMC journey, but only if it’s the right kind of AI. General-purpose tools are built for speed and scale, not accuracy. CMMC demands more.
Purpose-built tools like Copilot in CUIComply bring the power of AI into the world of CMMC in a way that’s grounded, accurate, and assessor-approved.
Want to test drive CUIComply for free? Sign up for a 14-day free trial today — no credit card required.