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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 (Q94-Q99):

NEW QUESTION # 94
Which of the following is MOST important to consider when validating a third-party AI tool?

A. Industry analysis and certifications
B. Terms and conditions
C. Right to audit
D. Roundtable testing

Answer: C

Explanation:
The AAISM framework specifies that when adopting third-party AI tools, the right to audit is the most critical contractual and governance safeguard. This ensures that the organization can independently verify compliance with security, privacy, and ethical requirements throughout the lifecycle of the tool. Terms and conditions provide general usage guidance but often limit liability rather than ensuring transparency. Industry certifications may indicate good practice but do not substitute for direct verification. Roundtable testing is useful for evaluation but lacks enforceability. Only the contractual right to audit provides formal assurance that the tool operates in accordance with organizational policies and external regulations.
References:
AAISM Exam Content Outline - AI Governance and Program Management (Third-Party Governance) AI Security Management Study Guide - Vendor Oversight and Audit Rights

NEW QUESTION # 95
A hospital is conducting an AI impact assessment for a proposed diagnostic imaging tool. To ensure conformity with regulatory and ethical standards, which risk requires the MOST domain- specific assessment beyond what is typically found in a standard IT risk assessment?

A. The model may produce systematically biased diagnoses for specific demographics, potentially leading to widespread clinical harm.
B. Software vulnerabilities in the application's web server may allow an attacker to gain unauthorized access to the system.
C. System downtime may increase due to hardware failure in the hosting environment, preventing medical professionals from accessing the tool.
D. Noncompliance with data residency laws may occur if patient data is processed in a cloud region outside the required jurisdiction.

Answer: A

Explanation:
Bias in diagnostic outputs directly affects clinical decision-making and patient outcomes, requiring specialized medical, ethical, and regulatory expertise beyond standard IT risk assessments. This type of risk involves domain-specific evaluation of fairness, safety, and potential harm to patients.

NEW QUESTION # 96
A CISO learns that a video showing an unverified safety issue with the organization's key product has gone viral. The individual in the video often appears to be blurry, and the video contains random lower-quality sections throughout. Which type of threat is this MOST likely an example of?

A. Deepfake
B. Model drift
C. Data poisoning
D. Hallucinations

Answer: A

Explanation:
AAISM defines deepfakes as manipulated media where individuals appear in synthetic or altered video/audio. Indicators include:
- blurred or inconsistent facial rendering
- mismatched frames
- low-quality or distorted transitions
These characteristics match the scenario provided.

NEW QUESTION # 97
To ensure ethical and responsible AI use, which AI usage policy metric is MOST important to monitor?

A. Number of policy violations
B. Number of AI projects reviewed for compliance
C. Frequency of policy consultations by employees
D. Frequency of policy reviews and updates

Answer: C

Explanation:
AAISM states the most meaningful policy performance metric is how often employees consult AI policies, which reflects:
- awareness
- practical adoption
- reliance on policy guidance
- safe decision-making behavior

NEW QUESTION # 98
Which of the following controls BEST mitigates the inherent limitations of generative AI models?

A. Ensuring human oversight
B. Reverse engineering the models
C. Classifying and labeling AI systems
D. Adopting AI-specific regulations

Answer: A

Explanation:
The AAISM governance framework emphasizes that the inherent limitations of generative AI-- including hallucinations, bias, and unpredictability--are best mitigated by human oversight.
Human-in-the-loop review ensures that outputs are validated before being used in sensitive or high-risk contexts. Regulatory adoption, system classification, and reverse engineering all play supporting roles but do not directly safeguard against the model's inherent unpredictability.
Governance best practices highlight human oversight as the critical safeguard.

NEW QUESTION # 99
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