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NEW QUESTION # 278
Which of the following is the PRIMARY objective of AI governance?
Answer: A
Explanation:
The AAIA™ Study Guide defines the primary objective of AI governance as establishing structure and accountability for AI initiatives. This includes clearly assigning responsibilities across development, deployment, risk management, and auditing roles to ensure that AI is used responsibly and transparently.
"AI governance establishes the policies, roles, and oversight structures that guide the ethical and secure deployment of AI. Clear accountability helps prevent unauthorized use and ensures strategic alignment." Options A and C are essential components of governance but are not its core definition. Option D is a business outcome, not a governance goal. Thus, B is the most comprehensive and accurate objective.
Reference: ISACA Advanced in AI Audit™ (AAIA™) Study Guide, Section: "AI Governance and Risk Management," Subsection: "Governance Objectives and Structures"
NEW QUESTION # 279
Which of the following is MOST important to consider when auditing an organization's AI procedures?
Answer: C
NEW QUESTION # 280
An IS auditor is auditing a financial system in which a generative AI tool is used to identify trends in batches of 4,000 rows, while the generative AI tool has a limit of 3,000 tokens. Which of the following is the GREATEST concern?
Answer: B
Explanation:
Generative AI tools such as large language models often have token limitations that restrict how much input they can process in a single prompt. According to the AAIA™ Study Guide, when input exceeds token limits, the model processes only the initial portion-leading to biased outputs based on early entries.
"Token limits in generative AI systems may lead to partial input processing, skewing model outputs toward the beginning of the data and introducing interpretive bias. Auditors must assess whether output reflects the full dataset." Options A and C describe side effects, but D identifies the most significant risk-output distortion due to truncated input.
Reference: ISACA Advanced in AI Audit™ (AAIA™) Study Guide, Section: "AI Operations and Performance," Subsection: "Limitations of Generative AI Models"
NEW QUESTION # 281
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 dat a. Which of the following is the auditor's BEST recommendation to address this issue?
Answer: C
NEW QUESTION # 282
An organization is using a large language model (LLM) to assist in evaluating loan applications, but the training data used is known to be incomplete. Which of the following is the GREATEST associated risk?
Answer: C
Explanation:
Incomplete training data often leads to underrepresentation of certain applicant types, products, or scenarios. In credit and lending, this typically translates into systematic bias : some groups are evaluated on richer historical patterns, while others are evaluated on sparse or unrepresentative information. The greatest associated risk is therefore unfair loan decisions (A), which can manifest as unjustified rejections, inappropriate pricing, or inconsistent risk assessments.
While delays (B), reduced satisfaction (C), or increased manual work (D) may occur, they are secondary operational issues. AAIA highlights that for financial services, the central risks include fairness, discrimination, regulatory compliance, and reputational impact . Incomplete data directly undermines fairness and can violate lending regulations and internal risk appetite.
References:
ISACA, AAIA Exam Content Outline - Domain 1: AI Governance and Risk (risk categories, including fairness and discriminatory outcomes).
ISACA AI ethics content on data completeness and representativeness in decisioning systems.
NEW QUESTION # 283
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