How Can You Pass The ISACA AAISM Exam?

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ISACA AAISM Exam Syllabus Topics:

SectionWeightObjectives
AI Technologies and Controls38%- Security monitoring, testing, and continuous assurance for AI systems
- AI lifecycle security: model selection, training, validation, and deployment
- AI security architecture and secure design principles
- Data management and protection controls for AI
- Privacy, ethics, trust, and safety controls
AI Risk Management31%- AI risk assessment, thresholds, and treatment strategies
- Regulatory compliance and ethical considerations in AI
- AI threat and vulnerability management
- AI vendor and supply chain risk management
AI Governance and Program Management31%- AI security policies, standards, and procedures
- AI asset and data lifecycle management
- AI security program development and management
- Business continuity and incident response for AI systems
- AI governance frameworks and alignment with business objectives

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ISACA Advanced in AI Security Management (AAISM) Exam Sample Questions (Q333-Q338):

NEW QUESTION # 333
What is the GREATEST benefit of performing AI security risk assessments?

Answer: D

Explanation:
AAISM emphasizes that the primary value of AI security risk assessments is prioritizing risks based on likelihood, impact, and business relevance.
Updating the register (A) is administrative. Privacy controls (B) are one category of mitigation. Funding (D) is possible but not the primary purpose.
References: AAISM Study Guide - AI Risk Assessment Objectives; Prioritization and Governance.


NEW QUESTION # 334
Which of the following metrics BEST evaluates the ability of a model to correctly identify all true positive instances?

Answer: B

Explanation:
AAISM technical coverage identifies recall as the metric that specifically measures a model's ability to capture all true positive cases out of the total actual positives. A high recall means the system minimizes false negatives, ensuring that relevant instances are not overlooked. Precision instead measures correctness among predicted positives, specificity focuses on true negatives, and the F1 score balances precision and recall but does not by itself indicate the completeness of capturing positives. The official study guide defines recall as the most direct metric for evaluating how well a model identifies all relevant positive cases, making it the correct answer.
References:
AAISM Study Guide - AI Technologies and Controls (Evaluation Metrics and Model Performance) ISACA AI Security Management - Model Accuracy and Completeness Assessments


NEW QUESTION # 335
Which of the following would BEST help an organization address the legal risk of processing personal information using AI?

Answer: A

Explanation:
Identifying and documenting legal obligations based on regional standards is the best way to address legal risk because privacy and AI regulations vary across jurisdictions. Understanding applicable legal requirements ensures that AI processing of personal information remains compliant with relevant laws and regulatory expectations.


NEW QUESTION # 336
When evaluating a third-party AI service provider, which of the following master services agreement provisions is MOST critical for managing security risk?

Answer: B

Explanation:
The most material contractual control for reducing security and privacy risk in outsourced AI services is a data-use restriction that prohibits the provider from using customer data for model training (and from derivative model improvements) unless explicitly authorized. This prevents unintended secondary processing, model inversion exposure of proprietary data, unauthorized profiling, and downstream data proliferation across multi-tenant systems. AAISM positions third-party risk controls to prioritize data minimization, purpose limitation, confidentiality, and downstream controls; among common MSA provisions, data-use limitations directly constrain the provider's technical and organizational handling of sensitive inputs, making it the highest-impact risk-reducing clause. Query throttling (B) and logging (C) are useful operational controls but are secondary to legal/processing authority. Unlimited retraining (D) increases attack surface and cost without addressing the core risk of misuse of customer data.
References: AI Security Management™ (AAISM) Body of Knowledge - Third-Party & Supply-Chain Governance; Contractual Controls for AI Services; Data Minimization and Purpose Limitation. AAISM Study Guide - Procurement & MSA/DPA Clauses for AI; Provider Model Training and Data-Use Restrictions; Privacy & Confidentiality Safeguards in Outsourced AI.


NEW QUESTION # 337
A global financial organization wants to deploy an AI solution for credit scoring. Which of the following should the organization do FIRST?

Answer: D

Explanation:
Ensuring the solution complies with applicable laws and regulations is the foundational step before any deployment activities. Regulatory compliance defines permissible data use, model behavior, and governance requirements, which must be established before conducting assessments, testing strategies, or documentation.


NEW QUESTION # 338
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