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ISACA AAISM Exam Syllabus Topics:

TopicDetails
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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AAISM Test Objectives Pdf, Testking AAISM Learning Materials

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ISACA Advanced in AI Security Management (AAISM) Exam Sample Questions (Q223-Q228):

NEW QUESTION # 223
An organization plans to use an external vendor's AI service for customer retention analytics.
Management is worried about third-party dependency and the risk of unauthorized access to customer data. Which of the following is the BEST approach to reduce this risk?

Answer: A

Explanation:
Including data protection requirements in the vendor contract establishes enforceable obligations for safeguarding customer data, while ongoing monitoring ensures the vendor continues to meet those obligations. This directly addresses both third-party dependency and unauthorized access risks in a sustainable and accountable manner.


NEW QUESTION # 224
An organization has implemented a natural language processing model to respond to customer questions when personnel are not available. A pre-implementation security assessment revealed attackers could access sensitive company data through a chat interface injection attack. Which of the following is the BEST way to prevent this attack?

Answer: A

Explanation:
To prevent prompt/interface injection, AAISM prioritizes preventive technical controls at the boundary: input validation/sanitization, structured templates/system prompts, allow/deny lists, and context isolation. These measures constrain user-supplied content and block adversarial instructions from being interpreted as system directives.


NEW QUESTION # 225
An AI application development team has been given access to user information and now must format it to be readable by the AI model. During which phase of the data life cycle would this MOST likely occur?

Answer: A

Explanation:
According to AAISM's data life-cycle model, data preparation is the phase where raw data is transformed into a model-ready format. The materials describe this phase as including "cleaning, encoding, formatting, feature engineering, and other transformations required for model consumption." This directly matches the scenario where a team formats user information to be readable by an AI model.


NEW QUESTION # 226
AI developers often find deep learning systems difficult to explain PRIMARILY because:

Answer: B

Explanation:
AAISM notes that deep learning systems lack transparency due to complex neural architectures, where internal representations are statistical, nonlinear, and not directly interpretable.


NEW QUESTION # 227
A data scientist creating categories and training an algorithm on large data sets is performing which learning technique?

Answer: D

Explanation:
AAISM identifies supervised learning as involving:
- labeled categories
- ground-truth datasets
- model training with known outcomes
This aligns exactly with categorizing data and training on labeled datasets.


NEW QUESTION # 228
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2026 Latest Pass4sures AAISM PDF Dumps and AAISM Exam Engine Free Share: https://drive.google.com/open?id=1mTg9ZQhzLr18ZtXodJFMlUjSqB17z5f7