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ISACA AAIA Exam Syllabus Topics:

Section	Weight	Objectives
AI Operations	46%	- Third-Party and Supply Chain Risk - AI System Lifecycle and Deployment - Operational Controls and Readiness - Performance Monitoring and Evaluation - Incident Management and Resilience
AI Governance and Risk	33%	- AI Models, Considerations, and Requirements - AI Governance and Program Management - Privacy and Data Governance Programs - Ethics, Regulations, and Standards for AI - AI Risk Management
AI Auditing Tools and Techniques	21%	- AI Audit Outputs and Reporting - Audit Evidence Collection Techniques - Data Quality and Analytics for AI Audit - Audit Testing and Sampling Methodologies - Audit Planning and Design

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ISACA Advanced in AI Audit Sample Questions (Q75-Q80):

NEW QUESTION # 75
An organization using AI to create digital content faces challenges in protecting its intellectual property.
Which of the following is the BEST way to mitigate this risk?

A. Separate training and production data.
B. Implement watermarking.
C. Apply adversarial training.
D. Implement a firewall.

Answer: B

Explanation:
For AI-generated content (images, text, or audio), " watermarking " is a critical technical control to protect Intellectual Property (IP) and ensure provenance. Digital watermarks can be embedded into the metadata or the content itself (often invisibly) to prove the organization is the creator and to track unauthorized distribution. This supports legal claims and brand protection. Firewalls and data separation protect the system , but watermarking protects the output once it is shared online or with clients. As AI makes content creation easier, the ability to prove ownership becomes an essential ethical and legal safeguard.

NEW QUESTION # 76
Which of the following controls helps mitigate the risk of competitors poisoning data utilized by a machine learning (ML) model performing sentiment analysis of product reviews?

A. Hiring a marketing firm to text links to customers requesting product reviews for monetary compensation
B. Requiring customers to authenticate access to their accounts prior to writing product reviews
C. Peer reviewing code that acquires product reviews from social media posts
D. Augmenting the unbalanced product review data set with the use of oversampling by the model developer

Answer: B

NEW QUESTION # 77
An organization uses an AI image generation platform to create promotional materials. An IS auditor identifies that the platform includes copyrighted images in its training data. Which of the following is the auditor's BEST recommendation to address this issue?

A. Use a platform that certifies the provenance and licensing of its training data.
B. Label all AI-generated images to disclaim the possibility of third-party content.
C. Suspend the use of the platform until the training data is sanitized.
D. Implement a manual review process to ensure no copyrighted images are used in generated outputs.

Answer: A

Explanation:
Ensuring that AI tools are trained on properly licensed and documented data sets is critical to avoiding copyright infringement and legal exposure. The AAIA™ Study Guide emphasizes using platforms with certified and traceable training data to meet ethical and legal standards.
"Organizations must verify the provenance and licensing of data used to train AI systems. Platforms that certify data sources reduce the risk of using protected intellectual property without consent." Manual review (A) is resource-intensive and may not detect embedded copyright violations. Labeling (C) is not sufficient for legal protection. Suspension (D) may be excessive without first attempting remediation.
Thus, B is the most strategic and effective recommendation.
Reference: ISACA Advanced in AI Audit™ (AAIA™) Study Guide, Section: "Ethical and Legal Considerations in AI," Subsection: "Intellectual Property and Data Licensing in AI Systems"

NEW QUESTION # 78
Which of the following is the GREATEST data quality risk when using an AI tool to assist with audit procedures?

A. Applying automated anomaly detection without human oversight
B. Training models on historical audit results generated prior to AI adoption
C. Utilizing unstructured data sources without standardized preprocessing
D. Embedding AI audit tools in transactional systems without user training

Answer: C

Explanation:
Unstructured data without standardized preprocessing (option A) creates the highest data quality risk because AI models depend heavily on the cleanliness, consistency, and structure of input data.
AAIA warns that improperly processed unstructured data leads to:
* Incorrect text extraction
* Lost contextual meaning
* Feature extraction errors
* Misclassification
* Inaccurate audit evidence
Option B is a bias or relevance risk, not data quality.
Option C is a governance/training issue.
Option D is an oversight risk, not a data quality issue.
Therefore, using unstructured data without preprocessing is the most direct threat to data quality.
References:
AAIA Domain 2: Data Preprocessing and Quality
AAIA Domain 3: AI-Assisted Audit Evidence Integrity

NEW QUESTION # 79
An IS auditor is evaluating a cybersecurity system that uses agentic AI for autonomous threat detection and incident response. Which of the following is MOST important for the auditor to consider?

A. The agent's audit logs are lengthier than traditional logs.
B. The agent can take automated actions that may disrupt business operations.
C. The agent operates across systems, which might require network expansion.
D. The agent processes data autonomously, reducing the need for analyst intervention.

Answer: B

Explanation:
"Agentic AI" goes beyond simple detection; it can take actions (like shutting down a server) autonomously. The greatest risk is that the AI might misinterpret a legitimate but unusual business activity as a threat and trigger a "kill switch," causing massive, unplanned downtime.
This is a significant operational and availability risk. Auditors must ensure there are "guardrails" or a "human-in-the-loop" for high-impact actions.

NEW QUESTION # 80
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