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ISACA AAISM Exam Syllabus Topics:

TopicDetails
Topic 1
  • AI Risk Management: This section of the exam measures the skills of AI Risk Managers and covers assessing enterprise threats, vulnerabilities, and supply chain risk associated with AI adoption, including risk treatment plans and vendor oversight.
Topic 2
  • AI Technologies and Controls: This section of the exam measures the expertise of AI Security Architects and assesses knowledge in designing secure AI architecture and controls. It addresses privacy, ethical, and trust concerns, data management controls, monitoring mechanisms, and security control implementation tailored to AI systems.
Topic 3
  • AI Governance and Program Management: This section of the exam measures the abilities of AI Security Governance Professionals and focuses on advising stakeholders in implementing AI security through governance frameworks, policy creation, data lifecycle management, program development, and incident response protocols.

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ISACA Advanced in AI Security Management (AAISM) Exam Sample Questions (Q27-Q32):

NEW QUESTION # 27
A critical AI system shows biased outcomes. What is the BEST course of action?

Answer: A

Explanation:
AAISM emphasizes root cause analysis as the primary step when AI behavior deviates unexpectedly.
RCA determines whether issues stem from:
- data drift
- model drift
- poisoned data
- missing features
- logic errors
- configuration changes


NEW QUESTION # 28
Which of the following is the MOST effective way to mitigate the effects of outdated data in a large language model (LLM)?

Answer: C

Explanation:
Retrieval-augmented generation (RAG) enables the LLM to access current external information at query time instead of relying solely on static training data. This is the most effective way to mitigate outdated knowledge because it provides dynamically updated and context-relevant information without requiring full model retraining.


NEW QUESTION # 29
Which of the following should be the MOST important consideration when conducting an AI impact assessment?

Answer: C

Explanation:
AAISM defines an AI Impact Assessment (AIIA) as a structured evaluation designed to determine whether an AI system can safely and responsibly support business objectives without creating unacceptable risks.
The framework states that alignment to business objectives is the central purpose of AI adoption and therefore must be the starting point in an impact assessment.


NEW QUESTION # 30
Which strategy BEST ensures generative AI tools do not expose company data?

Answer: D

Explanation:
AAISM identifies the strongest immediate control for preventing data leakage into generative AI systems as technically restricting or blocking user entry of sensitive data.
Audits (A) are retrospective. Testing tools (C) does not prevent user error. Regulatory compliance (D) does not stop operational leakage.
References: AAISM Study Guide - Data Leakage Prevention and Input Restriction Controls.


NEW QUESTION # 31
Which strategy BEST ensures generative AI tools do not expose company data?

Answer: D

Explanation:
AAISM identifies the strongest immediate control for preventing data leakage into generative AI systems as technically restricting or blocking user entry of sensitive data.


NEW QUESTION # 32
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