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| Section | Objectives |
|---|---|
| Topic 1: AI Auditing Tools and Techniques | |
| Topic 2: AI Governance and Risk | |
| Topic 3: AI Operations |
>> AAIA Associate Level Exam <<
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NEW QUESTION # 84
Which of the following techniques would be MOST effective as part of incident management procedures for a prompt injection attack?
Answer: A
Explanation:
Prompt injection attacksinvolve maliciously crafted inputs intended to override system instructions, exfiltrate data, or cause harmful behavior. The most effective control aligned with incident management is to deploy robust input validation and sanitization(C), which includes rules and filters designed to detect and neutralize potentially malicious content before it reaches the model. AAIA's coverage of AI threats and vulnerabilities highlights the importance ofinput validation and secure prompt handlingfor generative AI systems.
Fine-tuning the model (A) is a long-term adaptation, not an immediate incident control. Scanning for code- like structure (B) or excessive special characters (D) may catch some attacks but are too narrow; many prompt injections use natural language. Comprehensiveinput validationand sanitization is the most effective and generalizable incident management response.
References:
ISACA,AAIA Exam Content Outline- Domain 5: Ethical and Legal Considerations in AI; AI-specific threats and incident management.
ISACA AI security guidance covering prompt injection and input validation controls.
NEW QUESTION # 85
In the context of an AI implementation, which of the following actions is MOST critical for an organization's change management program?
Answer: B
Explanation:
The AAIATM Study Guide emphasizes that AI implementations introduce dynamic and non- deterministic elements into systems, increasing the risk associated with changes. A comprehensive, AI-specific risk assessment is therefore the most critical component of a change management program to ensure that updates, retraining, or parameter adjustments do not introduce vulnerabilities or unintended consequences.
"Risk assessments tailored to AI are crucial because changes to models, training data, or infrastructure can affect performance, ethical compliance, or expose the system to new threats. A standard IT change review is often insufficient."
NEW QUESTION # 86
Which of the following BEST demonstrates effective coordination to ensure comprehensive oversight of an AI system deployed across multiple jurisdictions?
Answer: C
Explanation:
When AI systems span multiple jurisdictions, they are subject to different regulatory regimes, cultural expectations, and risk tolerances. AAIA emphasizes that oversight must be coordinated to avoid gaps or overlaps. Establishing joint oversight plans and communication channels between agencies (B) ensures that relevant authorities share information, align on expectations, and collectively monitor AI risks, enabling coherent and comprehensive oversight.
NEW QUESTION # 87
Which of the following is MOST important for an IS auditor to consider when identifying AI risk in a know your customer (KYC) application within a banking organization?
Answer: B
Explanation:
In high-stakes financial applications like KYC, the primary concern is the potential business and regulatory impact of an AI error--such as false customer rejection or failure to detect fraudulent accounts. The AAIATM Study Guide emphasizes aligning AI risk assessments with business impact and regulatory exposure.
"In financial institutions, the most material risk of AI errors lies in operational disruption and regulatory fines. KYC models must be assessed for how errors can lead to compliance failures or reputational harm."
NEW QUESTION # 88
An organization is developing an AI system that integrates data from multiple external sources without clearly defined data ownership policies. Which of the following is the GREATEST concern in this situation?
Answer: A
Explanation:
When integrating data from multiple external sources, uncleardata ownershipdirectly affects accountability for privacy, consent, retention, and lawful processing. This createsgaps in AI privacy compliance and accountability(option D), which is the greatest concern because violations can lead to regulatory sanctions, litigation, and serious reputational damage. AAIA's governance and risk domain emphasizesprivacy and data governance programs, including clear roles, responsibilities, and ownership.
Option A is important but relates more to accuracy and performance validation, not the foundational legal and accountability issues. Option B (access permissions) is a control issue but usually easier to remediate once ownership and responsibilities are clarified. Option C (dependence on automated data collection/cleansing) can introduce quality risks but does not directly resolve or define who is accountable. Thus, the primary risk is the lack of clear privacy and accountability structures across external data sources.
References:
ISACA,AAIA Exam Content Outline- Domain 1: Privacy and Data Governance Programs (data governance, privacy considerations).
ISACA guidance on AI governance, roles, responsibilities, and accountability for data use.
NEW QUESTION # 89
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