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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 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.
Topic 3
  • 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.

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ISACA Advanced in AI Security Management (AAISM) Exam Sample Questions (Q326-Q331):

NEW QUESTION # 326
Which BEST addresses hallucination risk in AI systems?

Answer: C

Explanation:
AAISM states that human oversight is the strongest control for hallucination risks, especially in high-impact decisions. Humans validate outputs, correct errors, and override unsafe model responses.
Automated validation (C) helps but cannot fully detect hallucinations. Chunking (B) improves information handling but not hallucination mitigation. Content enrichment (D) does not reduce hallucinations.
References: AAISM Study Guide - Human-in-the-Loop (HITL) Controls; Hallucination Mitigation.


NEW QUESTION # 327
When developing organizational generative AI policies, the FIRST step is to:

Answer: B

Explanation:
Inventorying the current state of AI systems, use cases, and processes is the first step because an organization must understand where and how generative AI is being used before it can effectively define governance, assess risks, establish ethical expectations, or apply regulatory requirements.


NEW QUESTION # 328
Which of the following presents the GREATEST challenge to gaining an understanding of how a deep learning system operates?

Answer: C

Explanation:
Deep learning systems rely on highly complex non-linear relationships among large numbers of features, hidden layers, and parameters. These interactions make it difficult to understand, interpret, and explain how the model reaches specific decisions or outputs.


NEW QUESTION # 329
The PRIMARY purpose of adopting and implementing AI architecture within an organizational AI program is to:

Answer: A

Explanation:
AAISM describes AI architecture as a strategic alignment framework, ensuring AI systems, data pipelines, governance processes, and capabilities match organizational business goals and regulatory requirements.
While threat identification (B) and scalability (D) are advantages, the primary purpose is business alignment.
Option A is not a core architectural objective.
References: AAISM Study Guide - AI Architecture and Business Alignment.


NEW QUESTION # 330
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?

Answer: C

Explanation:
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.


NEW QUESTION # 331
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