Ideal for security professionals, compliance officers, and AI developers working on security-critical AI projects.

• Basic understanding of cybersecurity principles.
• Knowledge of networking fundamentals.
• Familiarity with programming concepts and languages (Python recommended)
• An introductory course on AI or machine learning is beneficial but not required.
• There are no mandatory prerequisites for certification. Certification is based solely on performance in the examination. However, candidates may choose to prepare through self-study or optional training offered by AI CERTS Authorized Training Partners (ATPs).

• Interpret and apply regulatory frameworks to AI systems
• Design AI workflows with privacy, security, and compliance considerations
• Conduct risk assessments, threat modeling, and control mapping for AI
• Implement explainable AI, audit trails, and bias mitigation strategies
• Prepare documentation and evidence for compliance audits
• Respond to compliance breaches and align AI systems with legal reporting
• Bridge the gap between technical AI implementation and regulatory / legal requirements

1. 1.1 Overview of Cybersecurity Compliance
2. 1.2 International Compliance Standards
3. 1.3 Developing Compliance Programs
4. 1.4 Implementing Compliance Programs
5. 1.5 AI in Cybersecurity Compliance
6. 1.6 Case Studies and Applications

1. 2.1 Risk Management Frameworks
2. 2.2 Conducting Risk Assessments
3. 2.3 AI in Risk Assessment
4. 2.4 Compliance and AI
5. 2.5 Incident Response and AI

1. 3.1 Data Classification and Protection
2. 3.2 AI in Privacy Protection
3. 3.3 Asset Management with AI
4. 3.4 Case Studies and Best Practices

1. 4.1 Secure Design Principles
2. 4.2 AI in Cryptography
3. 4.3 AI in Vulnerability Assessment
4. 4.4 Security Models and AI

1. 5.1 Network Security Fundamentals
2. 5.2 AI in Network Monitoring
3. 5.3 AI-driven Network Defense
4. 5.4 Compliance in Network Security

1. 6.1 IAM Fundamentals
2. 6.2 AI in Identity Verification
3. 6.3 Access Control and AI
4. 6.4 Threats to IAM and AI Solutions

1. 7.1 Security Testing Techniques
2. 7.2 AI in Security Testing
3. 7.3 Continuous Monitoring and AI
4. 7.4 Incident Response Planning
5. 7.5 Managing Cybersecurity Incidents
6. 7.6 Legal and Regulatory Considerations

1. 8.1 Security Operations Center (SOC)
2. 8.2 Data Classification and Protection
3. 8.3 Privacy Compliance
4. 8.4 Disaster Recovery and AI
5. 8.5 AI in Security Orchestration

1. 9.1 Secure Software Development Life Cycle (SDLC)
2. 9.2 AI in Application Security Testing
3. 9.3 AI in Secure DevOps
4. 9.4 Threat Modeling and AI
5. 9.5 Internal and External Audits
6. 9.6 Continuous Monitoring

1. 10.1 Emerging AI Technologies
2. 10.2 AI in Cyber Threat Intelligence
3. 10.3 Quantum Computing and AI
4. 10.4 Ethical Considerations and AI Governance
5. 10.5 Practical Applications

1. 1. What Are AI Agents
2. 2. Key Capabilities of AI Agents in Cyber Security Compliance
3. 3. Applications and Trends for AI Agents in Security Compliance
4. 4. How Does an AI Agent Work
5. 5. Core Characteristics of AI Agents
6. 6. Types of AI Agents