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ISACA Advanced in AI Risk Sample Questions:

1. A risk practitioner is reviewing an organization's implementation of a business-critical AI decision system.
Which of the following would be of GREATEST concern?

A) Reliance on conventional third-party security providers for system monitoring
B) Risk threshold acceptance criteria that do not require 100% decision accuracy
C) Lack of cross-functional AI incident identification and escalation training
D) Insufficient scenario-based testing of system failure modes and recovery procedures

2. Which of the following is the BEST governance approach for balancing risk management and operational flexibility across diverse AI applications?

A) Control approaches for AI solutions that prioritize compliance on a single regulation
B) Frameworks that can be adapted to business-relevant AI use cases
C) Risk ownership processes that focus on ensuring centralized decision-making
D) External consultants who conduct independent AI governance reviews

3. Which of the following is the GREATEST risk when an organization lacks clearly defined accountability mechanisms for AI outputs and decisions?

A) Ineffective model training
B) Reduced availability
C) Intellectual property exposure
D) Legal liability

4. Which of the following is the GREATEST benefit of incorporating AI technology for data asset management?

A) Providing more rapid identification of overfitting during model training
B) Justifying the use of synthetic data to augment smaller datasets
C) Reducing the initial impacts of data poisoning and exfiltration attacks
D) Automating data cleaning and metadata tagging for large datasets

5. An organization has deployed an AI-powered customer service chatbot. Which of the following BEST helps to ensure the chatbot maintains high accuracy in interpreting and answering customer inquiries?

A) Calculating precision and recall scores and increasing model temperature
B) Adopting vendor-recommended thresholds and conducting benchmarking
C) Measuring intent-classification error rates and refining training datasets
D) Introducing explainable AI techniques and conducting periodic code reviews

Solutions: