Actual AAISM ISACA Advanced in AI Security Management (AAISM) Exam Questions 2026

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ISACA AAISM Exam Overview:

Certification Vendor:ISACA
Exam Name:Advanced in AI Security Management (AAISM) Exam
Exam Number:AAISM
Certificate Validity Period:3 years (continuing professional education required for renewal)
Passing Score:450/800
Exam Price:USD 459 (member) / USD 599 (non-member)
Related Certifications:CISM
CISSP
Available Languages:Spanish, English
Exam Duration:150 minutes
Exam Format:Multiple-choice questions
Real Exam Qty:90
Recommended Training:ISACA Official Training & Review Materials
Exam Registration:ISACA AAISM Credentialing Page
Sample Questions:ISACA AAISM Sample Questions
Exam Way:Computer-based exam (online proctored or authorized test center)
Pre Condition:Recommended: Active CISM or CISSP certification and experience in IT/security management or advisory roles
Official Syllabus URL:https://www.isaca.org/credentialing/aaism

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AAISM Most Reliable Questions - AAISM Study Dumps

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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.

ISACA Advanced in AI Security Management (AAISM) Exam Sample Questions (Q111-Q116):

NEW QUESTION # 111
Which area of intellectual property law presents the GREATEST challenge in determining copyright protection for AI-generated content?

Answer: A

Explanation:
AAISM governance content highlights that the greatest intellectual property challenge in the context of AI-generated works is determining rightful ownership. Traditional copyright law requires human authorship, but AI-generated creations blur authorship and ownership boundaries, raising legal uncertainty about who can claim rights. Trademark enforcement, trade secret protection, and licensing frameworks are established areas of IP law but do not present the same fundamental challenge as ownership attribution. For AI-generated content, the central legal dilemma is ownership of the creation.


NEW QUESTION # 112
A bank's fraud detection AI model is trained on customer transaction data. A customer submits a data erasure request under privacy law, but the data also exists in training sets. Which of the following is the BEST approach if there is concern that complete data removal may reduce accuracy?

Answer: D

Explanation:
Updating standard operating procedures to ensure the customer's data is fully deleted is the best approach because organizations must comply with applicable privacy and data erasure requirements. Operational procedures should address how data is removed from training datasets and associated AI processes while balancing model maintenance and retraining considerations.


NEW QUESTION # 113
Which of the following involves documenting and monitoring the complete journey of data as it flows through an AI system?

Answer: A

Explanation:
Data lineage records and monitors the end-to-end journey of data-sources, movements, transformations, storage locations, uses, and dependencies-providing traceability, auditability, and accountability across the AI lifecycle. "Origin" is a single point (provenance), "transformation" is one step within the flow, and
"processing" is a general activity rather than a governance record of the entire path.
References: AI Security Management™ (AAISM) Body of Knowledge: Data Governance-Provenance and Lineage; AAISM Study Guide: Lineage Documentation, Traceability, and Audit Evidence.


NEW QUESTION # 114
Which of the following is the MAIN objective of the operational phase of AI life cycle management?

Answer: C

Explanation:
In the operational phase, AAISM emphasizes continuous monitoring of models for performance, stability, robustness, drift, data quality, security events, and policy compliance. This includes telemetry, thresholds, alerts, incident response for AI failures, and evidence collection for audits. Alignment to business needs is established earlier in planning/governance; algorithmic optimization and feedback collection are supporting activities, but the primary operational objective is live monitoring and assurance to keep risk within tolerance.
References:* AI Security Management™ (AAISM) Body of Knowledge: AI Life Cycle-Operate/Monitor; Ongoing Performance & Drift Monitoring; AI Incident Management* AAISM Study Guide: Operational Controls, Metrics & SLAs/SLOs; Evidence & Audit Readiness in Production


NEW QUESTION # 115
An organization wants to ensure a new AI security program is in alignment with the existing information security program. Which of the following is the BEST course of action?

Answer: C

Explanation:
Defining AI-specific objectives, governance roles, and reporting responsibilities establishes a structured framework that aligns the AI security program with existing information security governance, ensuring consistency, clarity, and integration from the outset.


NEW QUESTION # 116
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