ISACA Advanced in AI Security Management (AAISM) Cert Prep
6h 30mAdvanced2026-09-01
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Course details
Learn how to govern, manage, and protect AI systems in an enterprise environment. This course covers AI governance and strategy, regulatory alignment, risk management, data security, secure AI lifecycle practices, incident response, vendor risk, responsible AI, and continuous monitoring. Get equipped to translate AI-related risks into effective security controls and business-focused decisions.
Concepts
Introduction
- About the AAISM exam
- AAISM exam information
- What can the AAISM certification do for you
AI Governance, Strategy, and Regulatory Frameworks
- AI governance foundations
- Steering committees and charters
- Stakeholder identification and accountability
- Risk appetite and risk tolerance
- Framework selection and regulatory alignment
- AI business use case governance
- AI strategy - Consumer vs. enterprise
AI Risk Management and Data Security
- Buy vs. build decision governance
- AI policy and responsible use
- Procedures and manuals governance
- AI asset inventory and documentation
- Model cards and documentation standards
- Data classification and discovery
- Data augmentation and cleaning
- Secure data storage and protection
AI Lifecycle Security and Program Management
- Data destruction and retention
- Developing AI security program plan
- Aligning AI security with InfoSec
- AI security team and proficiencies
- AI-enabled security tools
- AI security metrics, KPIs, and KRIs
- Executive management reporting
- AI incident detection and notification
AI Threat Landscape and Resiliency Planning
- Incident classification and severity
- AI resiliency and BCP
- Red-button and break-glass controls
- AI RTO, RPO, and disaster recovery
- AI risk assessment and impact
- Risk documentation and treatment
- Pen testing and vulnerability testing
- Red teaming and adversarial threats
Incident Response, Vendor Risk, and AI Ethics
- Threat intel and AI attack chains
- Deepfakes, insider threat, and agents
- Vendor due diligence and contracts
- Provider vs. deployer accountability
- 3rd, 4th, and 5th-party risk
- IP ownership and liability
- Vendor monitoring and risk changes
- AI sec architecture and change mgmt
AI Security Controls and Continuous Monitoring
- Model testing, regression, and TEVV
- Data management and data poisoning
- Privacy, ethical, and trust controls
- Control selection and lifecycle
- Security monitoring and threat mapping