AI-Powered CMMC Audit Automation Course

This intensive one-day program equips Defense Industrial Base organizations with practical AI tools and strategies to automate CMMC audit preparation, reduce compliance costs, and accelerate certification readiness. Drawing from proven AI cybersecurity methodologies, participants will learn how to leverage machine learning, neural networks, natural language processing, and generative AI technologies to streamline evidence collection, automate risk assessments, and enhance continuous monitoring for CMMC Level 1 and Level 2 requirements.

The course covers discriminative and generative AI approaches, foundation models, and large language models specifically applied to compliance automation challenges facing defense contractors.

AI-Powered CMMC Audit Automation Course Benefits

• Upon completing this course, students should be able to:

  • Deploy AI tools to automate CMMC evidence collection and documentation
  • Implement AI-driven risk assessment frameworks for continuous compliance monitoring
  • Leverage generative AI to accelerate policy creation and security awareness training
  • Utilize AI-powered security operations tools for real-time threat detection and incident response
  • Apply AI governance frameworks to ensure responsible AI adoption while maintaining CMMC compliance
  • Design an AI implementation roadmap for sustainable CMMC audit automation

  Prerequisites

  Attendees should have foundational knowledge of CMMC requirements and process

AI-Powered CMMC Audit Automation Course Outline

Learning Objectives

Module 1 – AI Foundations for CMMC Automation

• Evolution of AI technology: machine learning, deep neural networks, and NLP in compliance
• AI architectures for security: CNNs, RNNs, and transformers in CMMC automation
• Foundation models vs. large language models for compliance documentation
• Mapping AI technologies to automated evidence collection and control verification

Practical Focus

• Automating CMMC Level 1 and Level 2 control verification with AI
• Identifying high-value automation opportunities across the 110 CMMC controls
• Continuous AI-powered compliance monitoring and status tracking

Lab Exercise

• Investigating Discriminative and Generative AI
• Hands-on exploration of how different AI approaches automate CMMC compliance tasks.

Module 2 – AI Risk Management in CMMC Environments

• Security, privacy, and compliance risks of AI implementations in defense contracting
• Ethical AI deployment aligned with DoD responsible AI principles
• Risks introduced by generative AI and mitigation strategies
• Defending against AI-enhanced social engineering and deepfake attacks

CMMC-Specific Focus

• Balancing AI risk mitigation with compliance objectives
• Human autonomy vs. automated system autonomy in compliance monitoring
• Data governance for AI systems handling CUI and FCI

Lab Exercises

• Protecting Sensitive Data with DLP – Implementing DLP in AI-powered compliance systems
• Conducting an AI Risk Assessment – Evaluating AI risks in defense contractor environments

Module 3 – AI-Enhanced Security Operations for CMMC

• SecOps automation using AI-based monitoring and response
• Managing hybrid IT and cloud AI environments in defense contracting
• AI security tooling: Google AI SecOps, Microsoft Cybersecurity Copilot, SIEM/SOAR integration
• AIOps, AI networking, and telemetry-driven day-2 operations

Hands-On Tools

• Google AI SecOps Unified Data Model for evidence collection
• Microsoft Cybersecurity Copilot for investigations and documentation
• AI-driven orchestration for automated incident response and compliance validation

Lab Exercise

• Defending Security with AI
  Implementing AI-powered monitoring and automated response for CMMC control verification.

Module 4 – AI Vulnerabilities and Attack Vectors

• AI algorithms, datasets, and models as attack surfaces
• OWASP Top 10 risks for AI-powered systems
• Prompt engineering threats and injection attack defenses
• AI-enhanced social engineering and deepfake exploitation

Defense Contractor Focus

• Securing AI used in CMMC compliance automation
• Protecting intellectual property from AI-enabled reconnaissance
• AI red teaming to validate secure CMMC implementations

Lab Exercises

• Penetration Testing an AI System – Identifying vulnerabilities in AI compliance tools
• Enhancing Hacking with GenAI – Understanding attacker AI techniques targeting defense contractors

Module 5 – AI Governance and CMMC Framework Integration

• Regulatory landscape: EU AI Act and NIST AI Risk Management Framework
• OWASP governance checklist for secure AI deployment
• Responsible AI and secure AI frameworks for ethical implementation
• Federated learning and zero-trust generative AI architectures

Practical Implementation

• Establishing AI governance policies for defense contractors
• Managing generative AI risk while enabling automation
• Integrating AI with existing CMMC compliance management platforms
• Evaluating vendors and assessing AI security tool risk
• Evolution of AI Technology: Machine Learning, Deep Neural Networks, and NLP applications in compliance
• AI Architectures for Security: CNNs, RNNs, Transformers and their role in CMMC automation
• Foundation Models vs. Large Language Models: Understanding capabilities for compliance documentation
• CMMC-Specific Applications: Mapping AI technologies to automated evidence collection and control verification

Practical Focus:

• Understanding AI capabilities for automating CMMC Level 1 and Level 2 control verification
• Identifying which of the 110 CMMC controls benefit most from AI automation
• AI-powered continuous monitoring for compliance status tracking

Lab Exercise

• Investigating Discriminative and Generative AI - Hands-on exploration of how different AI approaches can automate CMMC compliance tasks