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ISACA AAISM Exam Syllabus Topics:

Section	Weight	Objectives
Topic 1: AI Governance and Program Management	31%	- 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. Stakeholder considerations 2. Organizational structure and governance 3. Roles and responsibilities - AI Strategy and Policy 1. AI strategy development 2. Responsible and acceptable use 3. Policies and procedures
Topic 2: AI Risk Management	31%	- AI Risk Assessment 1. Risk identification and analysis 2. Risk thresholds and treatment - AI Threats and Vulnerabilities 1. Data poisoning and model manipulation 2. Supply chain and vendor risks 3. Adversarial AI and ML attacks
Topic 3: AI Technologies and Controls	38%	- AI Security Architecture 1. Secure AI system design 2. Model lifecycle security - AI Assurance and Safety 1. Bias mitigation 2. Ethical AI controls 3. Model validation and testing - Data and Model Controls 1. Privacy-preserving techniques 2. Data protection and governance 3. Monitoring and runtime controls

Section

Weight

Objectives

Topic 1: AI Governance and Program Management

31%

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

- AI Strategy and Policy

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

Topic 2: AI Risk Management

31%

- AI Risk Assessment

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

- AI Threats and Vulnerabilities

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

Topic 3: AI Technologies and Controls

38%

- AI Security Architecture

1. Secure AI system design
2. Model lifecycle security

- AI Assurance and Safety

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

- Data and Model Controls

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

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ISACA Advanced in AI Security Management (AAISM) Exam Sample Questions (Q210-Q215):

NEW QUESTION # 210
An organization plans to leverage AI in the software development process to speed up coding.
Which of the following should the information security manager do FIRST?

A. Conduct an impact assessment
B. Perform a cost-benefit analysis
C. Update the security policy to include AI controls
D. Train developers to verify AI output

Answer: A

Explanation:
AAISM guidance specifies that before introducing AI into any business or technical workflow, an AI Impact Assessment must be conducted early to determine potential risks, privacy implications, misuse scenarios, governance gaps, and required security controls. This aligns with the principle that AI adoption must begin with governance and risk identification, not training or policy modification.

NEW QUESTION # 211
An organization uses an AI model to optimize traffic signals and predict congestion. Due to misconfiguration and lack of validation, the system over-prioritizes low-traffic areas, causing gridlock in major cities. Which of the following should be done FIRST to address this issue?

A. Retrain the model in real time using new traffic data.
B. Roll back the AI system to a previous version.
C. Disable the AI system and issue a public statement.
D. Continue running the AI model and deploy a secondary system.

Answer: B

Explanation:
Rolling back to a previously stable version immediately restores known correct behavior and mitigates ongoing impact. This provides a controlled state before further validation or retraining is performed.

NEW QUESTION # 212
After an organization deploys an AI-based system, a regulator warns of increased risk related to AI re-identification attacks on anonymized data sets. Which of the following should the information security manager do FIRST?

A. Implement a monitoring program including privacy audits and adversarial testing
B. Assume anonymization is permanent and continue regular business operations.
C. Immediately delete anonymized datasets and suspend AI services
D. Establish strong access controls for services using anonymized data

Answer: A

Explanation:
AAISM states that anonymization is not permanent and may be reversible through re- identification attacks. The first action should be to evaluate and measure the actual privacy risk through:
- adversarial re-identification testing
- privacy audits
- monitoring for misuse
This provides the factual basis needed before making destructive or operational decisions.

NEW QUESTION # 213
Which of the following BEST enables an organization to strengthen information security controls around the use of generative AI applications?

A. Validating AI model training data
B. Implementing a kill switch
C. Ensuring controls exceed industry benchmarks
D. Monitoring AI outputs against policy

Answer: D

Explanation:
For generative AI, the primary enterprise security exposure is data and content exfiltration or policy violations at output, including leakage of sensitive data, toxic content, or regulatory non-compliance. AAISM prescribes policy-aligned output monitoring (e.g., DLP checks, PII/PHI detection, toxicity/safety filters, watermark
/attribution checks) integrated into inference gateways to enforce organizational policies and evidence compliance. Exceeding benchmarks (A) is not a control; training-data validation (C) may be infeasible with third-party LLMs; and kill switches (D) are essential contingency controls but do not continuously strengthen everyday security posture.
References: AI Security Management™ (AAISM) Body of Knowledge - GenAI Governance and Guardrails; Output Filtering and DLP Controls; Policy Enforcement at Inference. AAISM Study Guide - Monitoring & Auditing of GenAI; Gateway Patterns for Safe Use; Control Effectiveness Measures.

NEW QUESTION # 214
Which of the following security framework elements BEST helps to safeguard the integrity of outputs generated by AI algorithms?

A. Management is prepared to disclose AI system architecture to stakeholders
B. Risk exposure due to bias in AI outputs is kept within an acceptable range
C. Responsibility is defined for legal actions related to AI regulatory requirements
D. Ethical standards are incorporated into security awareness programs

Answer: B

Explanation:
According to AAISM technical controls, the element of security frameworks that directly safeguards output integrity is ensuring that bias-related risks are maintained within acceptable ranges. This ensures that AI results remain consistent, fair, and reliable, preserving trust in outputs. Ethical awareness, architectural disclosure, and legal responsibilities are governance practices but do not directly secure output integrity. Output integrity is primarily protected through bias management and ongoing evaluation of fairness and accuracy.

NEW QUESTION # 215
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