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ISACA AAISM Exam Overview:

Certification Vendor:ISACA
Exam Name:ISACA Advanced in AI Security Management (AAISM) Exam
Exam Number:AAISM
Available Languages:Spanish, English
Exam Price:USD $399
Real Exam Qty:90
Passing Score:450/800
Related Certifications:ISACA Advanced in AI Security Management (AAISM)
Certificate Validity Period:3 years
Exam Format:Multiple Choice, Scenario-based Questions
Exam Duration:150 minutes
Sample Questions:ISACA AAISM Sample Questions
Exam Way:Online remote proctored exam or test center exam
Pre Condition:Candidates must hold an active CISM or CISSP certification.
Official Syllabus URL:https://www.isaca.org/credentialing/aaism/aaism-exam-content-outline

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ISACA AAISM Exam Syllabus Topics:

TopicDetails
Topic 1
  • 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 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 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.

ISACA Advanced in AI Security Management (AAISM) Exam Sample Questions (Q155-Q160):

NEW QUESTION # 155
For a life insurance company deploying AI for fraud detection, which factor is MOST critical?

Answer: B

Explanation:
AAISM emphasizes robustness as the key requirement for fraud-detection systems because they must resist adversarial manipulation, data poisoning, spoofing, and input tampering.
Accuracy (B) matters but does not protect against adversarial attacks. Explainability (C) is important but secondary. Adaptability (D) is useful but not the top security requirement.
References: AAISM Study Guide - AI Robustness; Fraud Detection and Adversarial Resistance.


NEW QUESTION # 156
Which of the following MOST effectively secures ongoing stakeholder support for AI initiatives?

Answer: A

Explanation:
AAISM governance guidance emphasizes that stakeholder buy-in is sustained when the measurable value of AI initiatives is clearly communicated. Value demonstrations include:
- improved efficiency
- reduced cost
- reduced risk
- business growth


NEW QUESTION # 157
Which of the following controls BEST mitigates the risk of data poisoning?

Answer: D

Explanation:
The AAISM technical controls framework emphasizes data validation as the primary safeguard against data poisoning attacks. Poisoning occurs when attackers insert malicious or corrupted data into training sets.
Validation techniques verify the quality, authenticity, and consistency of input data before training, preventing compromised samples from corrupting the model. Restoration helps after compromise, watermarking protects ownership, and intrusion detection monitors networks rather than data quality. The most effective preventive measure is data validation.
References:
AAISM Study Guide - AI Technologies and Controls (Data Poisoning Mitigation) ISACA AI Security Management - Data Validation and Quality Controls


NEW QUESTION # 158
The PRIMARY purpose of adopting and implementing AI architecture as part of an organizational AI program is to:

Answer: C

Explanation:
An AI architecture, within program governance, exists to align AI system components and lifecycle processes with business goals and policy constraints. Architecture provides the organizing structure linking strategy, capabilities, processes, data, models, controls, and assurance so that AI outcomes are traceable to business value, risk appetite, and compliance expectations. Efficiency, speed, and threat analysis are important architectural qualities, but they are not the primary purpose; the primary purpose is strategic and governance alignment so that technical choices and controls consistently realize organizational objectives.
References:* AI Security Management™ (AAISM) Body of Knowledge: AI Program Architecture - alignment of capabilities, processes, and controls to business objectives* AI Security Management™ Study Guide: Architecture-driven governance, traceability from business goals to technical and control design


NEW QUESTION # 159
Which of the following information is MOST important to include in a centralized AI inventory?

Answer: C

Explanation:
AAISM governance practices identify ownership and accountability as the most critical element in any centralized AI inventory. An AI inventory provides oversight by cataloging all AI assets within an organization, and assigning responsibility ensures that each system has clear governance, monitoring, and compliance coverage. While use cases, training data, and registries are valuable metadata, they do not guarantee accountability. Without defined ownership, no party is responsible for addressing risk, bias, or incidents. Therefore, the most important information to include is ownership and accountability details for each AI system.
References:
AAISM Exam Content Outline - AI Governance and Program Management (AI Inventories and Oversight) AI Security Management Study Guide - Ownership and Accountability Structures


NEW QUESTION # 160
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