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ISACA AAISM Exam Syllabus Topics:

Section	Weight	Objectives
AI Technologies and Controls	38%	- AI Assurance and Safety 1. Model validation and testing 2. Bias mitigation 3. Ethical AI controls - AI Security Architecture 1. Secure AI system design 2. Model lifecycle security - Data and Model Controls 1. Monitoring and runtime controls 2. Privacy-preserving techniques 3. Data protection and governance
AI Governance and Program Management	31%	- AI Strategy and Policy 1. AI strategy development 2. Responsible and acceptable use 3. Policies and procedures - AI Governance Foundations 1. Stakeholder considerations 2. Roles and responsibilities 3. Organizational structure and governance - Frameworks and Compliance 1. Privacy and ethics considerations 2. Industry frameworks and standards (e.g., NIST AI RMF, ISO/IEC 42001) 3. Regulatory requirements
AI Risk Management	31%	- AI Risk Assessment 1. Risk thresholds and treatment 2. Risk identification and analysis - AI Threats and Vulnerabilities 1. Adversarial AI and ML attacks 2. Data poisoning and model manipulation 3. Supply chain and vendor risks

Section

Weight

Objectives

AI Technologies and Controls

38%

- AI Assurance and Safety

1. Model validation and testing
2. Bias mitigation
3. Ethical AI controls

- AI Security Architecture

1. Secure AI system design
2. Model lifecycle security

- Data and Model Controls

1. Monitoring and runtime controls
2. Privacy-preserving techniques
3. Data protection and governance

AI Governance and Program Management

31%

- AI Strategy and Policy

1. AI strategy development
2. Responsible and acceptable use
3. Policies and procedures

- AI Governance Foundations

1. Stakeholder considerations
2. Roles and responsibilities
3. Organizational structure and governance

- Frameworks and Compliance

1. Privacy and ethics considerations
2. Industry frameworks and standards (e.g., NIST AI RMF, ISO/IEC 42001)
3. Regulatory requirements

AI Risk Management

31%

- AI Risk Assessment

1. Risk thresholds and treatment
2. Risk identification and analysis

- AI Threats and Vulnerabilities

1. Adversarial AI and ML attacks
2. Data poisoning and model manipulation
3. Supply chain and vendor risks

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ISACA Advanced in AI Security Management (AAISM) Exam AAISM Prüfungsfragen mit Lösungen (Q332-Q337):

332. Frage
What is the PRIMARY purpose of a dedicated AI management system policy?

A. Optimizing AI model accuracy
B. Minimizing environmental impact
C. Complying with external regulations
D. Providing a framework to set AI objectives

Antwort: D

Begründung:
AAISM states that an AI management system policy provides organizational structure by:
* defining AI objectives
* aligning governance
* outlining accountability
* defining roles, responsibilities, and guiding principles
Regulatory compliance (C) is a part of governance but not the overall purpose. Accuracy (B) and environmental impact (A) are narrower focus areas.
References: AAISM Study Guide - AI Management System Policies; Governance Framework Requirements.

333. Frage
In managing the life cycle of agentic AI systems, which of the following would be the GREATEST concern during the destruction phase of AI models and associated data?

A. Absence of verifiable audit trails confirming secure elimination of residual AI models and data
B. Delays and challenges encountered in reassigning new AI models and data
C. Incomplete records of AI model specifications and version histories
D. Inability to preserve explainability and transparency for agentic AI systems following secure disposal

Antwort: A

Begründung:
The greatest concern during the destruction phase is the inability to verify that AI models and associated data were securely and completely eliminated. Without verifiable audit trails, residual models or sensitive data may remain accessible, creating significant security, privacy, and compliance risks.

334. Frage
A school district contracts a third-party provider for AI-based curriculum recommendations. Which of the following is the BEST way to ensure the vendor uses AI responsibly?

A. Confirming the AI solution supports single sign-on (SSO)
B. Ensuring the vendor offers 24/7 technical support
C. Verifying the vendor has updated terms of service
D. Requiring the vendor to provide the model card

Antwort: D

Begründung:
AAISM emphasizes transparency artifacts from vendors to enable due diligence and assurance. A model card documents intended use, data sources, limitations, performance across subgroups, known risks, and evaluation procedures-information necessary to assess safety, fairness, and compliance for sensitive contexts like education. SSO and support are useful operational features; generic ToS updates are insufficient without model-specific disclosures.
References: AI Security Management (AAISM) Body of Knowledge - Third-Party & Supply Chain Governance; Transparency Artifacts (Model Cards, Datasheets). AAISM Study Guide - Vendor Due Diligence Requirements; Documentation for Risk, Fairness, and Intended Use.

335. Frage
Which of the following is the BEST way to ensure role clarity and staff effectiveness when implementing AI- assisted security monitoring tools?

A. Increase training budgets for business staff to obtain vendor-neutral AI certifications.
B. Transition responsibilities for AI tools to external consultants for improved scalability.
C. Update the security program to include cross-functional AI-specific responsibilities.
D. Defer implementation until the security team can be expanded with data scientists.

Antwort: C

Begründung:
AAISM directs that AI adoption in security operations be governed through explicit operating models and RACI-mapped responsibilities spanning security operations, data science/ML, platform engineering, privacy, and compliance. Role clarity comes from updating the security program to codify AI-specific responsibilities (model monitoring, incident handling for AI failures, data governance, change control for models, bias/fairness reviews, supplier assurance) rather than deferring implementation, outsourcing core accountability, or relying on generic certifications. This ensures measurable accountability, reduces hand-off risk, and aligns day-to-day SOC practices with AI control objectives.
References:* AI Security Management (AAISM) Body of Knowledge: AI Governance Operating Model; Roles & Responsibilities; RACI for AI-enabled Security Operations* AAISM Study Guide: Program Governance, Control Objective Mapping to SOC Workflows; Cross-Functional Ownership for AI Controls

336. Frage
A pharmaceutical organization uses an AI solution from a third-party vendor to analyze confidential research and development data. Which of the following controls is MOST essential to ensure the vendor's AI solution complies with the organization's security requirements?

A. Review the vendor's independent security audit report.
B. Implement a private instance of the solution.
C. Communicate security requirements to the vendor.
D. Minimize sensitive data being used by the vendor's AI solution.

Antwort: A

Begründung:
Reviewing the vendor's independent security audit report provides objective assurance that the vendor's AI solution and related controls have been evaluated against recognized security standards and requirements. This is essential for validating compliance with the organization's security expectations when handling confidential research data.

337. Frage
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