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Test Certification AAISM Cost, AAISM Valid Exam Test

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ISACA AAISM Exam Syllabus Topics:

Topic
Details

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 (Q180-Q185):

NEW QUESTION # 180
Which of the following should be done FIRST when developing an acceptable use policy for generative AI?

A. Determine the scope and intended use of AI
B. Consult with risk management and legal
C. Review AI regulatory requirements
D. Review existing company policies

Answer: A

Explanation:
According to the AAISM framework, the first step in drafting an acceptable use policy is defining the scope and intended use of the AI system. This ensures that governance, regulatory considerations, risk assessments, and alignment with organizational policies are all tailored to the specific applications and functions the AI will serve. Once scope and intended use are clearly defined, legal, regulatory, and risk considerations can be systematically applied. Without this step, policies risk being generic and misaligned with business objectives.
References:
AAISM Study Guide - AI Governance and Program Management (Policy Development Lifecycle) ISACA AI Governance Guidance - Defining Scope and Use Priorities

NEW QUESTION # 181
Which of the following is the BEST way to ensure role clarity and staff effectiveness when implementing AI- assisted security monitoring tools?

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

Answer: B

Explanation:
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

NEW QUESTION # 182
Which of the following is the BEST way to ensure an organization remains compliant with industry regulations when decommissioning an AI system used to record patient data?

A. Update governance policies based on lessons learned and ensure a feedback loop exists
B. Perform a post-destruction risk assessment to verify that there is no residual exposure of data
C. Ensure the certificate of destruction is received and archived in line with data retention policies
D. Ensure backups are tested and access controls are recorded and audited to ensure compliance

Answer: C

Explanation:
For regulated data such as patient information, AAISM requires provable data lifecycle closure at decommissioning. The authoritative evidence is a certificate of destruction (covering primary, replicas, backups, and caches) retained per the organization's records retention policy. While testing backups and auditing access (A), updating policies (B), and doing post-destruction risk assessment (C) are valuable practices, documented destruction attestation is the primary compliance proof point that the data was disposed of in accordance with regulatory and contractual obligations.
References: AI Security Management™ (AAISM) Body of Knowledge - Data Lifecycle Governance; Decommissioning & Secure Disposal; Records Retention and Evidence of Destruction.

NEW QUESTION # 183
Which AI model is BEST suited to ensure explainability in an HR department's pre-screening tool for candidate resumes?

A. Gradient boosting machine
B. Support vector machine
C. Neural network
D. Decision tree

Answer: D

Explanation:
According to AAISM, decision trees provide the highest explainability because their structure clearly shows how inputs map to decisions. This is essential in HR applications subject to fairness, bias, and compliance requirements.
SVMs (A) and gradient boosting (D) are less interpretable. Neural networks (B) are explicitly listed as low- explainability models.
References: AAISM Study Guide - Explainability and Transparency Requirements; Interpretable ML Models.

NEW QUESTION # 184
When implementing a generative AI system, which of the following approaches will BEST prevent misalignment between the corporate risk appetite and tolerance?

A. Ensuring effective AI key performance indicators (KPIs)
B. Creating and maintaining an AI risk register
C. Establishing and monitoring acceptable levels of AI system risk
D. Performing an AI impact assessment

Answer: C

Explanation:
AAISM governance guidance specifies that alignment between AI system adoption and organizational risk appetite is achieved by defining and monitoring acceptable levels of system risk. This ensures that generative AI operations remain within boundaries approved by leadership and compliance frameworks. While KPIs track performance, they do not ensure alignment with risk tolerance. AI impact assessments help identify risks but do not maintain continuous oversight. A risk register records risks but does not dynamically enforce acceptable thresholds. The most effective governance approach is to establish and monitor acceptable AI system risk levels.
References:
AAISM Study Guide - AI Governance and Program Management (Risk Appetite and Tolerance Alignment) ISACA AI Security Management - Generative AI Risk Governance

NEW QUESTION # 185
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