Free AAISM Exam Braindumps
ISACA Advanced in AI Security Management Questions 146–150 (page: 31)

Updated On: 13-Sep-2026

Which of the following AI data management techniques involves creating validation and test data?

  1. Learning
  2. Splitting
  3. Training
  4. Annotating

Answer(s): B

Explanation:

Splitting involves dividing the available data into separate subsets for training, validation, and testing, enabling proper evaluation of model performance and generalization.



A financial organization uses AI to detect potential fraudulent activities but is concerned about the impact of potential data poisoning.
Which of the following controls would BEST mitigate this risk?

  1. Implementing an updated and tested break-glass policy
  2. Being transparent with customers about the data sources
  3. Using training data from multiple sources
  4. Delivering AI-specific security awareness training

Answer(s): C

Explanation:

Using training data from multiple sources reduces the impact of poisoned or manipulated data from any single source, making the AI model more resilient to data poisoning and improving the robustness of fraud detection outcomes.



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?

  1. Conducting regular information security audits
  2. Manually reviewing AI model outputs
  3. Implementing input validation and templates
  4. Ensuring continuous monitoring and data tagging

Answer(s): C

Explanation:

Implementing input validation and templates prevents chat interface injection attacks by constraining and sanitizing user inputs, ensuring the model processes only expected and safe input formats and cannot be manipulated to access or disclose sensitive company data.



Which of the following AI data life cycle phases presents the GREATEST inherent risk?

  1. Monitoring
  2. Maintenance
  3. Preparation
  4. Training

Answer(s): D

Explanation:

The training phase presents the greatest inherent risk because it directly determines how the AI model learns patterns and behaviors; compromised, biased, or poisoned training data can permanently embed flaws into the model that persist throughout deployment and operation.



Which of the following would MOST effectively obtain ongoing support from stakeholders to align AI initiatives with business objectives?

  1. Quantifying and communicating the value of AI solutions
  2. Conducting periodic organization-wide AI staff training
  3. Addressing and optimizing AI-related risk
  4. Developing and monitoring the AI strategic roadmap

Answer(s): A

Explanation:

Quantifying and communicating the value of AI solutions most effectively sustains stakeholder support by clearly demonstrating how AI initiatives contribute to business outcomes, return on investment, and strategic goals, which drives continued alignment and commitment.



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