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ISACA AAISM Exam Overview:

Certification Vendor:	ISACA
Exam Name:	ISACA Advanced in AI Security Management (AAISM) Exam
Exam Number:	AAISM
Related Certifications:	ISACA Advanced in AI Security Management (AAISM)
Certificate Validity Period:	3 years
Available Languages:	English, Spanish
Real Exam Qty:	90
Exam Duration:	150 minutes
Exam Format:	Scenario-based Questions, Multiple Choice
Exam Price:	USD $399
Passing Score:	450/800
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:

Topic	Details
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 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 3	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.

ISACA Advanced in AI Security Management (AAISM) Exam Sample Questions (Q95-Q100):

NEW QUESTION # 95
A school district contracts a third-party provider for AI-based curriculum recommendations. Which of the following is the BEST way to ensure the vendor uses AI responsibly?

A. Requiring the vendor to provide the model card
B. Confirming the AI solution supports single sign-on (SSO)
C. Ensuring the vendor offers 24/7 technical support
D. Verifying the vendor has updated terms of service

Answer: A

Explanation:
AAISM emphasizes transparency artifacts from vendors to enable due diligence and assurance. A model card documents intended use, data sources, limitations, performance across subgroups, known risks, and evaluation procedures-information necessary to assess safety, fairness, and compliance for sensitive contexts like education. SSO and support are useful operational features; generic ToS updates are insufficient without model-specific disclosures.
References: AI Security Management (AAISM) Body of Knowledge - Third-Party & Supply Chain Governance; Transparency Artifacts (Model Cards, Datasheets). AAISM Study Guide - Vendor Due Diligence Requirements; Documentation for Risk, Fairness, and Intended Use.

NEW QUESTION # 96
After implementing a third-party generative AI tool, an organization learns about new regulations related to how organizations use AI. Which of the following would be the BEST justification for the organization to decide not to comply?

A. The AI tool is regularly audited
B. The AI tool is widely used within the industry
C. The cost of noncompliance was not determined
D. The risk is within the organization's risk appetite

Answer: D

Explanation:
The AAISM framework clarifies that compliance decisions must always be tied to an organization's risk appetite and tolerance. When new regulations emerge, management may choose not to comply if the associated risk remains within the documented and approved risk appetite, provided that accountability is established and governance structures support this decision. Other options such as widespread industry use, third-party audits, or lack of cost assessment do not justify noncompliance under the governance principles. The risk appetite framework is the only recognized justification under AI governance principles.

NEW QUESTION # 97
Which of the following controls BEST mitigates the inherent limitations of generative AI models?

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

Answer: D

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 # 98
When using AI as part of incident response, which of the following BEST ensures the automation aligns with regulatory and governance obligations?

A. Apply anomaly detection models to filter incoming threats and automate containment
B. Implement a tiered automation strategy where severity ratings inform the need for human oversight
C. Use deep learning models to autonomously classify all incidents
D. Train the AI incident response platform to mirror legacy response workflows and log containment

Answer: B

Explanation:
AAISM prescribes risk-based, human-in-the-loop orchestration for safety-critical or regulated actions. A tiered automation strategy that gates autonomy by incident severity, data sensitivity, and regulatory requirements ensures accountability, auditability, and proportionality, satisfying governance obligations. Full autonomy (A) risks non-compliance; simply mirroring legacy workflows (B) may not meet current obligations; broad auto-containment (C) lacks necessary oversight controls.
References: AI Security Management™ (AAISM) Body of Knowledge - Governance of AI-Driven Security Automation; Human Oversight and Escalation; Risk-Based Orchestration. AAISM Study Guide - Incident Response with AI: Controls, Approvals, and Auditability.

NEW QUESTION # 99
An organization has requested a developer to apply AI algorithms to existing modules in order to improve customer service quality. At this stage, which of the following should be considered FIRST?

A. IT management may need to revise the service agreement if AI behavior cannot be predefined
B. Project sponsors may need to agree on a phased approach in order to ensure safe release
C. The developer may need to be held accountable for business inquiries raised by customers
D. The organization may need to explain the performance of the applied AI algorithm

Answer: A

Explanation:
According to AAISM governance principles, when AI functionality is added to existing services, the first consideration is contractual and service-level accountability. If AI outputs cannot be predefined, the existing service agreements may no longer reflect performance responsibilities or liability. Revising or updating the agreement ensures governance alignment, accountability, and risk management for AI-driven behavior.
Phased approaches and performance explanations are valuable but occur later in project management.
Developer accountability for customer inquiries is not a primary governance step. The most immediate consideration is revising service agreements when AI introduces new uncertainties.
References:
AAISM Exam Content Outline - AI Governance and Program Management (Policies and Service Agreements) AI Security Management Study Guide - Accountability in AI Deployments

NEW QUESTION # 100
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