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ISACA AAISM Exam Syllabus Topics:

SectionWeightObjectives
AI Governance and Program Management31%- Stakeholder considerations and governance frameworks
  • 1. AI governance models and oversight
  • 2. Industry frameworks and regulatory requirements
- AI policies and procedures
  • 1. AI-related strategy development
  • 2. Policy implementation and compliance
- AI security program management
  • 1. Program development and maintenance
  • 2. Incident response and business continuity
- AI asset and data lifecycle management
  • 1. Data governance
  • 2. AI asset inventory and management
AI Technologies and Controls38%- AI security monitoring and operations
  • 1. Security monitoring and logging
  • 2. Operational AI controls
- AI security architecture and design
  • 1. AI infrastructure protection
  • 2. Secure AI system architecture
- Trust, safety and compliance controls
  • 1. Responsible AI practices
  • 2. Compliance and governance validation
- Data management and privacy controls
  • 1. Privacy and ethical AI controls
  • 2. Data integrity and protection
AI Risk Management31%- Third-party and supply chain risk management
  • 1. Vendor risk evaluation
  • 2. Supply chain security controls
- AI threat and vulnerability management
  • 1. Threat modeling for AI systems
  • 2. AI vulnerability assessment
- AI risk assessment and treatment
  • 1. Risk identification and analysis
  • 2. Risk thresholds and mitigation

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ISACA Advanced in AI Security Management (AAISM) Exam Sample Questions (Q407-Q412):

NEW QUESTION # 407
An organization is considering a Software as a Service (SaaS)-based HR system that uses AI to automate resume vetting and pre-screening of candidates. Which of the following controls is MOST important to review?

Answer: A

Explanation:
AAISM states that HR systems performing candidate evaluation must prioritize training data fairness, representativeness, and bias mitigation because biased HR decisions carry regulatory, ethical, and litigation risks.


NEW QUESTION # 408
A preliminary risk assessment of a SaaS-based large language model (LLM) business support system has identified prompt injection, data poisoning, and model exfiltration as material threats.
Which of the following is the BEST approach to ensure risks are treated consistently?

Answer: D

Explanation:
AAISM prescribes building and maintaining an AI Threat-Control Matrix to ensure consistent, repeatable risk treatment. The matrix traces each material threat (e.g., prompt injection, poisoning, exfiltration) to named controls, test/evidence procedures, and assurance owners across the lifecycle. Baselines and vendor attestations can support assurance but are insufficient alone; deferring control selection until after deployment conflicts with AAISM's proactive treatment principle.


NEW QUESTION # 409
Which of the following attack types is the MOST likely cause of model drift?

Answer: B

Explanation:
AAISM defines data poisoning as directly capable of causing model drift because corrupted training data shifts the statistical distribution, leading to degraded or unsafe performance.


NEW QUESTION # 410
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?

Answer: A

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.
References:
AAISM Study Guide - AI Governance and Program Management
ISACA AI Risk Guidance - Risk Appetite and Compliance Decisions


NEW QUESTION # 411
An organization uses a vendor's AI service to screen job applicants. The master service agreement includes a clause related to accountability models. Which of the following is the PRIMARY purpose of this clause in managing AI-specific risk?

Answer: D

Explanation:
Accountability clauses in AI service agreements are primarily intended to clearly define the responsibilities, obligations, and liabilities of each party involved in the use, operation, governance, and oversight of the AI system. This helps manage AI-specific risks related to compliance, security, ethics, and operational failures.


NEW QUESTION # 412
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