Actual ISACA AAISM Exam Dumps - Achieve Success In Exam

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ISACA AAISM Exam Syllabus Topics:

Topic	Details
Topic 1	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 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 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.

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ISACA Advanced in AI Security Management (AAISM) Exam Sample Questions (Q232-Q237):

NEW QUESTION # 232
An organization plans to use a natural language processing (NLP) system that processes and analyzes sensitive data. The data science team has proposed storing all raw text data indefinitely for potential model improvements and additional analytics. Which of the following is the BEST course of action?

A. Transfer encrypted data to a third-party storage service.
B. Implement differential privacy on stored data.
C. Propose data retention limits based on legitimate purpose.
D. Approve indefinite retention to improve future models.

Answer: C

Explanation:
Establishing data retention limits based on legitimate purpose ensures sensitive data is only stored as long as necessary, reducing privacy risk and aligning with data protection principles and regulatory requirements.

NEW QUESTION # 233
Which of the following reviews MUST be conducted as part of an AI impact assessment?

A. Testing, evaluation, validation, and verification
B. Identification of environmental and societal consequences
C. Evaluation of model reproducibility
D. Security control self-assessment (CSA)

Answer: B

Explanation:
The AAISM material frames an AI impact assessment as broader than a technical model review.
It emphasizes that governance of AI includes assessing societal, environmental, and human- rights impacts in addition to organizational risk. The official guidance notes that high-level impact assessments must explicitly consider "potential consequences for individuals, communities, and the environment" as part of responsible AI governance.

NEW QUESTION # 234
A large corporation has received an influx of sophisticated credential-phishing emails and wants to leverage an AI solution to detect and quarantine these messages before they reach employees. Which of the following blue-team AI features is BEST suited to this task?

A. Large language model (LLM)
B. Natural language processing (NLP)
C. Natural language generation (NLG)
D. Retrieval-augmented generation (RAG)

Answer: B

Explanation:
For pre-delivery phishing detection and classification, the most appropriate capability is NLP-- tokenization, feature extraction, semantic similarity, and supervised classifiers (e.g., transformer- based classifiers) tuned on phishing corpora and indicators. NLP models score messages and drive automated quarantine policies.

NEW QUESTION # 235
When creating a use case for an AI model that provides sensitive decisions affecting end users, which of the following is the GREATEST benefit of using model cards?

A. Data collection requirements are reduced
B. Technical instructions for model deployment are created
C. Ethical considerations of the model are documented
D. Model type selection is documented

Answer: C

Explanation:
AAISM highlights that model cards are a governance tool designed to document ethical considerations, limitations, fairness constraints, data sources, and suitability of use cases for AI models--especially when they affect individuals' rights, opportunities, or access to services.
Their greatest value is providing transparency and ethical clarity, ensuring stakeholders understand risks, bias considerations, and how decisions impact users.

NEW QUESTION # 236
When preparing for an AI incident, which of the following should be done FIRST?

A. Establish recovery processes for AI system models and data sets
B. Create containment and eradication procedures for AI-related incidents
C. Implement a communication channel to report AI incidents
D. Establish a cross-functional incident response team with AI knowledge

Answer: D

Explanation:
AAISM incident response guidance states the first foundational step is forming a cross-functional AI-aware incident response team, including model developers, data stewards, security leads, and compliance officers.
Without the team established, recovery (C), containment (D), or communication channels (A) cannot be effectively designed or executed.
References: AAISM Study Guide - AI Incident Response; Establishing Cross-Functional Teams.

NEW QUESTION # 237
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