Free ISACA AAIA Practice Questions & Answers 2026 Part1 | ISACA Advanced in AI Audit

A healthcare organization uses patient data to train an AI model for early disease detection. Which of the following practices provides the BEST assurance that personal data is secure and its integrity is maintained?

Which of the following is the MOST effective way an IS auditor could use generative AI to plan an audit of a new database storing transactional data?

Which control is MOST important to verify in order to ensure proper data management with AI systems? According to the ISACA AAIA Study Guide, a 'Data Governance Framework' is the foundational control. It provides the policies, roles (stewards, owners), and standards necessary to manage the entire data lifecycle. Without a framework, activities like inventorying (Option C) or labeling (Option D) are ad-hoc and lack accountability. A formal framework ensures that data management is consistent, compliant with privacy laws, and aligned with the organization's risk tolerance. It is the 'enabling' control that makes all other data quality and security metrics meaningful and enforceable.

When utilizing a machine learning (ML) model to predict whether a wind turbine electricity generator will fail, which model evaluation metric should be the PRIMARY focus?

The BEST way to prevent sensitive information disclosure by large language model (LLM) chatbots is through:

When utilizing a machine learning (ML) model to predict whether a wind turbine electricity generator will fail, which model evaluation metric should be the PRIMARY focus? In predictive maintenance use cases---such as detecting turbine failure---the most critical concern is identifying as many actual failures as possible to prevent catastrophic events. The AAIA Study Guide emphasizes that in such high-risk scenarios, Recall is the most appropriate metric because it measures the proportion of true positives correctly identified. ''Recall is critical in scenarios where missing a positive instance (e.g., a failure) is costly or dangerous. It ensures that most real issues are caught by the model, even at the expense of some false positives.'' Precision measures correctness of positive predictions, specificity measures true negatives, and accuracy may be misleading if the data is imbalanced. Thus, D (Recall) is most appropriate.

An IS auditor is evaluating a cybersecurity system that uses " agentic AI " for autonomous response. Which of the following is MOST important to consider?

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?

Which of the following is the MOST important purpose of conducting a risk assessment for AI modelswithin an organization?

Which of the following is the MOST important course of action for an organization prior to allowing end users to utilize an AI tool?

A digital bank utilizes an AI system to generate credit scores. Which of the following would BEST mitigate the risk of sudden and unexplained changes in a borrower's credit score?

Which of the following key performance indicators (KPIs) are MOST important when evaluating whether an AI model meets business objectives?

An organization deploys an AI recruitment platform to screen job applicants. The IS auditor identifies that the platform’s decisions may be influenced by model bias. Which of the following risk mitigation strategies is BEST for the auditor to recommend?

Which of the following data management practices poses the GREATEST risk to the reliability of an AI model ' s correlations?

Which of the following key performance indicators (KPIs) are MOST important when evaluating whether an AI model meets business objectives?

Which of the following is MOST important for an IS auditor to review during an AI system audit in order to determine compliance with intellectual property and data rights?

While evaluating a complex machine learning (ML) model used for regulatory compliance in afinancial institution, which of the following should the IS auditor do to BEST ensure transparency?

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?

Which program management practices are critical for ensuring an AI strategy is effectively implemented across the enterprise? (Choose two)

An IS auditor uses an AI model to summarize worksheets, but several worksheets contained a " Hidden Cell " instructing the model to ignore control failures. Which solution BEST mitigates the risk?

Which of the following key performance indicators (KPIs) are MOST important when evaluatingwhether an AI model meets business objectives?

A digital bank utilizes an AI system to generate credit scores. Which of the following would BEST mitigate the risk of sudden and unexplained changes in a borrower's credit score?

Which activities are considered best practices in designing an AI audit testing methodology? (choose two)

Which of the following should be done FIRST when an attacker exfiltrates sensitive information froman AI model?

An organization is adopting AI for its procurement and inventory teams, raising concern fromstakeholders that they will lose their jobs due to AI. Which of the following is the BEST way for the ISauditor to assess whether the potential negative impacts were minimized?

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? 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 AAIA 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.'' Benchmarking (B) supports best practice alignment, and incident response (C) is part of mitigation, but D addresses the most critical consequence of AI risks in banking.

The PRIMARY objective of machine learning (ML) in data processing is to:

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?

The internal audit department of a large global organization is evaluating the use of an AI-based voice-to-speech tool to document interviews during audits. The tool uploads all recordings to a cloud service provider for transcription. Which of the following is the GREATEST risk? Audit interviews often contain highly sensitive, proprietary, or even non-public information. Uploading these recordings to a cloud provider introduces the 'Risk of unauthorized access' by the vendor's employees or through a security breach at the vendor's site. According to ISACA, the loss of 'Confidentiality' over audit workpapers is a critical failure of professional standards. While inaccurate transcriptions (Option D) are a nuisance, they can be corrected by the auditor; however, once sensitive data is compromised by a third party, the damage is irreversible. Auditors must ensure the vendor has rigorous 'encryption' and 'at-rest' security attestations.

When using off-the-shelf AI models, which of the following is the MOST appropriate way for organizations to approach vendor management?

Which of the following would provide the BEST evidence to an IS auditor that an AI model's outputs are effectively controlled for bias?

What makes walkthroughs and interviews valuable in AI audit evidence collection?