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ISACA AAISM Exam Syllabus Topics:

Section	Weight	Objectives
Topic 1: AI Governance and Program Management	31%	- AI Strategy and Policy 1. Policies and procedures 2. Responsible and acceptable use 3. AI strategy development - Frameworks and Compliance 1. Regulatory requirements 2. Privacy and ethics considerations 3. Industry frameworks and standards (e.g., NIST AI RMF, ISO/IEC 42001) - AI Governance Foundations 1. Organizational structure and governance 2. Roles and responsibilities 3. Stakeholder considerations
Topic 2: AI Risk Management	31%	- AI Risk Assessment 1. Risk thresholds and treatment 2. Risk identification and analysis - AI Threats and Vulnerabilities 1. Adversarial AI and ML attacks 2. Data poisoning and model manipulation 3. Supply chain and vendor risks
Topic 3: AI Technologies and Controls	38%	- Data and Model Controls 1. Data protection and governance 2. Monitoring and runtime controls 3. Privacy-preserving techniques - AI Security Architecture 1. Model lifecycle security 2. Secure AI system design - AI Assurance and Safety 1. Ethical AI controls 2. Model validation and testing 3. Bias mitigation

Section

Weight

Objectives

Topic 1: AI Governance and Program Management

31%

- AI Strategy and Policy

1. Policies and procedures
2. Responsible and acceptable use
3. AI strategy development

- Frameworks and Compliance

1. Regulatory requirements
2. Privacy and ethics considerations
3. Industry frameworks and standards (e.g., NIST AI RMF, ISO/IEC 42001)

- AI Governance Foundations

1. Organizational structure and governance
2. Roles and responsibilities
3. Stakeholder considerations

Topic 2: AI Risk Management

31%

- AI Risk Assessment

1. Risk thresholds and treatment
2. Risk identification and analysis

- AI Threats and Vulnerabilities

1. Adversarial AI and ML attacks
2. Data poisoning and model manipulation
3. Supply chain and vendor risks

Topic 3: AI Technologies and Controls

38%

- Data and Model Controls

1. Data protection and governance
2. Monitoring and runtime controls
3. Privacy-preserving techniques

- AI Security Architecture

1. Model lifecycle security
2. Secure AI system design

- AI Assurance and Safety

1. Ethical AI controls
2. Model validation and testing
3. Bias mitigation

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ISACA Advanced in AI Security Management (AAISM) Exam Sample Questions (Q34-Q39):

NEW QUESTION # 34
An information security manager is tasked with preparing management reports regarding the risk mitigation controls applied to the organization's customer service chatbot. Which of the following is MOST critical to include in these reports?

A. Service level agreements (SLAs) for AI vendor performance
B. Project plans and milestones for chatbot deployment
C. Actionable recommendations for control performance improvements
D. In-depth descriptions of chatbot training data sources and AI algorithms

Answer: C

Explanation:
Management reports should provide actionable recommendations that help decision-makers improve the effectiveness of risk mitigation controls. This information is critical for ongoing governance, risk reduction, and informed management oversight of the chatbot environment.

NEW QUESTION # 35
Security and assurance requirements for AI systems should FIRST be embedded in the:

A. Model deployment phase
B. Model testing phase
C. Model design phase
D. Model training phase

Answer: C

Explanation:
AAISM directs organizations to embed security, safety, and compliance controls at design time ("secure-by-design" and "shift-left"), ensuring requirements for robustness, privacy, and governance are defined as non-functional constraints on architecture, data sourcing, model choices, and evaluation criteria before any model is trained. Deferring these requirements to training, testing, or deployment increases residual risk and rework, and weakens traceability of control coverage.

NEW QUESTION # 36
Which of the following information is MOST important to include in a centralized AI inventory?

A. Training data sets
B. Foundation model and package registry
C. Ownership and accountability of AI systems
D. AI model use cases

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 # 37
Which attack type is MOST likely to cause model drift?

A. Model stealing
B. Data poisoning
C. Membership inference
D. Perfect knowledge

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.
Model stealing (A) extracts model behavior but does not cause drift. Perfect knowledge (B) is an attacker capability, not an attack causing drift. Membership inference (D) attacks privacy, not performance.
References: AAISM Study Guide - Model Drift Causes; Data Poisoning Impact.

NEW QUESTION # 38
Which of the following is the GREATEST concern when a vendor enables generative AI features for an organization's critical system?

A. Access to the model
B. Security monitoring and alerting
C. Bias and ethical practices
D. Proposed regulatory enhancements

Answer: A

Explanation:
When enabling genAI capabilities in a critical system, AAISM prioritizes controlling access to the model and its interfaces (prompt surfaces, context windows, tools/functions, and connected data) because exposure expands the attack surface for prompt injection, data exfiltration, jailbreaks, and misuse.

NEW QUESTION # 39
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