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ISACA AAISM Exam Overview:

Certification Vendor:ISACA
Exam Name:Advanced in AI Security Management (AAISM) Exam
Exam Number:AAISM
Exam Price:USD 459 (member) / USD 599 (non-member)
Certificate Validity Period:3 years (continuing professional education required for renewal)
Real Exam Qty:90
Exam Duration:150 minutes
Exam Format:Multiple-choice questions
Passing Score:450/800
Related Certifications:CISM
CISSP
Available Languages:Spanish, English
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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ISACA AAISM Exam Syllabus Topics:

TopicDetails
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.

ISACA Advanced in AI Security Management (AAISM) Exam Sample Questions (Q35-Q40):

NEW QUESTION # 35
A PRIMARY objective of responsibly providing AI services is to:

Answer: C

Explanation:
AAISM emphasizes that the primary objective of responsible AI is to establish and maintain trust in AI-driven decisions and predictions. Trust is achieved through transparency, accountability, fairness, and governance. While confidentiality and integrity are critical technical objectives, they are not the overarching purpose of responsible AI service provision. Autonomy and learning ability are features of AI, but without trust, adoption and compliance falter. The correct answer is that responsible AI services must focus on building trust in AI outcomes.


NEW QUESTION # 36
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?

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 # 37
An organization is updating its vendor arrangements to facilitate the safe adoption of AI technologies. Which of the following would be the PRIMARY challenge in delivering this initiative?

Answer: A

Explanation:
In the AAISM guidance, vendor management for AI adoption highlights that large AI providers often resist contractual changes, particularly when customers seek to impose stricter security, transparency, or ethical obligations. The official study materials emphasize that while organizations must evaluate AI risk and build internal expertise, the primary challenge lies in negotiating acceptable contractual terms with dominant AI vendors who may not be willing to adjust their standardized agreements. This resistance limits the ability of organizations to enforce oversight, bias controls, and compliance requirements contractually.
References:
AAISM Exam Content Outline - AI Risk Management
AI Security Management Study Guide - Third-Party and Vendor Risk


NEW QUESTION # 38
What is the GREATEST benefit of performing AI security risk assessments?

Answer: C

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 # 39
An organization is planning to commission a third-party AI system to make decisions using sensitive data. Which of the following metrics is MOST important for the organization to consider?

Answer: C

Explanation:
When AI systems make consequential decisions over sensitive data, AAISM requires explicit performance thresholds tied to decision quality--i.e., accuracy (and related error/false-rate limits) aligned to business risk appetite and regulatory expectations. Availability and latency are important service metrics, but decision integrity and error bounds are primary risk drivers in sensitive contexts. Establishing, monitoring, and enforcing minimum accuracy thresholds (with subgroup performance checks) is essential to reduce harm, ensure fairness/compliance, and support auditability.


NEW QUESTION # 40
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