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AAISM Exam Topics and Domains
AAISM is organized into 3 weighted domains. Expect to work with NIST AI RMF, SIEM, Data Lakes, ETL Tools, and more.
AI Governance and Program Management
Stakeholder Considerations, Industry Frameworks, and Regulatory Requirements
- Collaborate on charter, roles, and responsibilities for governance and management of AI to align with business objectives
- Ensure the responsible use of AI by utilizing leading practices, ethical principles, regulatory requirements, and industry frameworks
AI-Related Strategies, Policies, and Procedures
Establish and maintain AI-specific security policies and procedures to inform the development and implementation of AI standards and guidelines
AI Asset and Data Life Cycle Management
Manage AI assets and data throughout their life cycles to ensure security, quality, and compliance
AI Security Program Development and Management
Develop and manage comprehensive AI security programs aligned with organizational objectives and risk appetite
Business Continuity and Incident Response
Ensure business continuity and effective incident response for AI systems to minimize impact and enable rapid recovery
AI Risk Management
AI Risk Assessment, Thresholds, and Treatment
- Participate in or oversee the AI risk management life cycle, including impacts on enterprise risk
- Assess and manage AI risks through systematic identification, analysis, and treatment processes
AI Threat and Vulnerability Management
Identify and manage threats and vulnerabilities specific to AI systems throughout their lifecycle
AI Vendor and Supply Chain Management
Manage security risks associated with AI vendors and supply chains through comprehensive assessment and monitoring
AI Technologies and Controls
AI Security Architecture and Design
Design and implement secure AI architectures that incorporate security principles throughout the system lifecycle
AI Life Cycle (Model Selection, Training, and Validation)
Secure the AI model lifecycle from selection through training, validation, deployment, and monitoring
Data Management Controls
Implement comprehensive data management controls throughout the AI data lifecycle
Privacy, Ethical, Trust and Safety Controls
Implement privacy, ethical, trust, and safety controls to ensure responsible AI deployment
Security Controls and Monitoring
Implement and monitor security controls to protect AI systems from threats and enable effective incident response
How do I earn this certification?
Passing AAISM earns the ISACA Advanced in AI Security Management (AAISM) certification. It sits in the AI Security and Governance track.
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How to study for this exam?
The most effective way to prepare for AAISM is by using the PlanetCert Simulator to practice questions and review detailed explanations.
What's changed on this exam?
- ACTIVE
- Last content update: 2025-01-01
- Announcement date: 2025-01-01
- NIST AI Risk Management Framework 1.0 Core framework for AAISM Domain 2 (AI Risk Management) • Release date: 2023-01-26
- ISO/IEC 42001 1.0 International standard for AI management systems - key reference for AAISM • Release date: 2023-12-15
- EU AI Act Final Major regulatory framework affecting Domain 1 (AI Governance) • Release date: 2024-03-13
- MITRE ATLAS 4.0 Primary framework for AI threat landscape in Domain 2 • Release date: 2024-01-01
Who should take this exam?
This exam is typically taken by CISM and CISSP certified professionals and IT security managers and directors.
- Experience in security or advisory roles
- Expertise assessing, implementing, and maintaining AI systems
- Understanding of enterprise risk management
- Familiarity with AI technologies and architectures