Quiz ISACA - AAIA–Professional Valid Exam Camp

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ISACA AAIA Exam Overview:

Certification Vendor:ISACA
Exam Name:ISACA Advanced in AI Audit
Exam Number:AAIA
Real Exam Qty:90
Passing Score:65%
Exam Format:Multiple Choice, Remotely Proctored, Computer-Based
Exam Duration:120 minutes
Available Languages:English
Related Certifications:ACCA
CISA
CIA
FCCA
CPA
Sample Questions:ISACA AAIA Sample Questions
Exam Way:Online remotely proctored computer-based exam
Pre Condition:Candidates must hold an active CISA certification or another qualified audit-related designation such as CIA, CPA, ACCA, FCCA, Canadian CPA, Australian CPA/FCPA, or Japanese CPA.
Official Syllabus URL:https://www.isaca.org/credentialing/aaia

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ISACA AAIA Exam Syllabus Topics:

TopicDetails
Topic 1
  • Auditing Tools and Techniques: This section of the exam measures the skills of AI auditors and centers on auditing AI systems using appropriate tools and methods. It includes audit planning and design, sampling methodologies specific to AI, collecting audit evidence, using data analytics for quality assurance, and producing AI audit outputs and reports, including follow-up and quality control measures.
Topic 2
  • AI GOVERNANCE AND RISK: It encompasses understanding different AI models and their life cycles, guiding AI strategy, defining roles and policies, managing AI-related risks, overseeing data privacy and governance, and ensuring adherence to ethical practices, standards, and regulations.
Topic 3
  • AI Operations: It covers managing AI-specific data needs—including collection, quality, security, and classification—applying development lifecycle methodologies with privacy and security by design, change and incident management, testing AI solutions, identifying AI-related threats and vulnerabilities, and supervising AI deployments.

ISACA Advanced in AI Audit Sample Questions (Q69-Q74):

NEW QUESTION # 69
When auditing AI systems, which data management practice BEST ensures compliance with privacy regulations?

Answer: A

Explanation:
Privacy regulations like GDPR and CCPA emphasize the principle of "Data Minimization"-- collecting only the data that is strictly necessary for the intended purpose. In an AI context, organizations often feel tempted to collect as much data as possible to improve accuracy (Option A), but this increases privacy risk and legal exposure. According to ISACA, implementing data minimization is the most effective practice for ensuring regulatory compliance. It reduces the
"attack surface" in the event of a breach and ensures that the organization is not holding onto sensitive PII that it cannot justify. Indefinite retention (Option D) is a direct violation of most modern privacy laws.


NEW QUESTION # 70
An organization is using information gathered from customer accounts to train its AI chatbot. Which of the following is the GREATEST risk associated with this practice?

Answer: C


NEW QUESTION # 71
An IS auditor is testing an AI-based fraud detection system that flags suspicious transactions and finds that the system has a high false positive rate. Which of the following testing methods should be prioritized to BEST optimize the detection rate?

Answer: C


NEW QUESTION # 72
What is the PRIMARY purpose of a "red team" exercise for an AI system?

Answer: B

Explanation:
AI red teaming simulates adversarial or malicious use to uncover weaknesses (jailbreaks, biased outputs, harmful content generation) before deployment, complementing traditional security testing.


NEW QUESTION # 73
An organization is reviewing its existing data governance framework after implementing an AI- based document repository solution. Which of the following should be the PRIMARY consideration?

Answer: B

Explanation:
The PRIMARY consideration is data classification (B), because the AI-based repository handles different types of documents that may contain sensitive, confidential, regulated, or public information. Proper classification ensures correct application of access controls, retention rules, encryption requirements, and privacy protections.


NEW QUESTION # 74
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