Isaca AAIA Exam Dumps

ISACA Advanced in AI Audit (AAIA)

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Exam Code	AAIA
Exam Name	ISACA Advanced in AI Audit (AAIA)
Questions	275 Questions Answers With Explanation
Update Date	06, 04, 2026
Price	Was : $81 Today : $45 Was : $99 Today : $55 Was : $117 Today : $65

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Demo Questions

Question # 1

An AI-based marketing analytics tool is trained on data that is five years old. Which of the following is MOST likely to occur?

A. Model extraction 
B. Model poisoning 
C. Model inversion 
D. Model drift 

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Question # 2

A retailer's AI pricing engine recommends unusually large discounts in certain regions. An audit reveals that most historical sales data used for model training came from large urban areas, while smaller regions were represented by very few or no sales records. Which of the following is the MOST likely cause of this issue?

A. Labeling inconsistencies in regional identifiers 
B. Data scarcity in the training set that causes the model to be unable to learn regional patterns 
C. Model drift from recent changes in customer demand
D. Overfitting of the model resulting in misrepresentation of sales records 

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Question # 3

An organization has exhausted its internal data sources to train an AI model. Which of the following is the BEST source to obtain new data?

A. Data from web scraping 
B. Copyright-free data 
C. Extended retention of internal data 
D. Shadow data 

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Question # 4

An IS auditor analyzed an AI model scorecard and identified that training data was imbalanced. Which of the following is the BEST recommendation to remediate risk?

A. Use class-weighted loss with stratified train/validation splits. 
B. Tune decision thresholds using expected misclassification costs. 
C. Optimize the decision threshold for maximum F1 on validation. 
D. Increase the capacity of the model with early stopping. 

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Question # 5

An organization implements a neural network-based AI system for credit scoring that processes extensive input data from multiple sources. Which of the following represents the GREATEST risk if input validation and anomaly detection controls are inadequate? 

A. Biased inputs that can affect credit decisions 
B. Overfitting caused by excessive anomaly filtering 
C. Increased computational cost due to redundant input checks 
D. Delayed model training cycles from excessive data preprocessing 

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Question # 6

An IS auditor notes that an AI modelachieved significantly better results on training data than on test data. After the development, a quality assurance (QA) team checks that all input variables and parameters match the technical design. Which of the following BEST describes this activity?

A. Model validation 
B. Model verification 
C. Model testing 
D. Model tuning 

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Question # 7

A health organization has deployed an AI model to analyze chest X-rays. The model reports high accuracy, but thresholds are unclear and performance is not broken down by patient demographics. Why is accuracy alone insufficient to evaluate this model?

A. The model may perform poorly for certain groups, leading to hidden fairness risks. 
B. Accuracy can only be calculated on structured tabular datasets. 
C. A high accuracy score always indicates low false positives. 
D. Performance is identical across all demographic subgroups. 

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Question # 8

The PRIMARY benefit of using AI in audit fieldwork is that it:

A. Saves time for the engagement manager in reviewing the audit work. 
B. Can scan large datasets to identify trends and anomalies. 
C. Helps auditors to cover testing processes of all risk levels. 
D. Automates documentation of workpapers and artifacts. 

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Question # 9

A bank's fraud detection model achieves high accuracy on its initial dataset but performs poorly in production. The data science team needs to tune hyperparameters and select the best model architecture. Which dataset is BEST to use for this selection process?

A. Holdout dataset 
B. Training dataset 
C. Testing dataset 
D. Validation dataset 

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Question # 10

Which of the following is the GREATEST risk associated with normalizing a data set before splitting it into training, testing, and validation sets?

A. The model affects data distribution. 
B. The model requires external validation. 
C. The model gains indirect knowledge from data leakage. 
D. The developer uses tree-based models with the normalized data set. 

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Question # 11

When an auditor is using AI to test controls, what would be the HIGHEST risk to the audit's integrity?

A. AI tests reviewed by an auditor relying solely on AI output 
B. AI generating test output in a confusing format 
C. AI testing failing to include all relevant transactions in its analysis 
D. AI returning only medium-risk observations from the test 

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Question # 12

Which of the following techniques is BEST to use when there is a limited dataset of detailed images available to train a convolutional neural network (CNN) model?

A. Splitting the dataset 50/50 between training and testing sets 
B. Minority class undersampling 
C. Transfer learning from an open-source model 
D. Duplication of current dataset 

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Question # 13

An organization's fraud detection model achieves high accuracy on its initial data set but performs poorly in production. After a complex neural network was trained, the training accuracy was significantly higher than the validation accuracy. Which of the following is the MOST likely cause?

A. Insufficient training data 
B. Overfitting 
C. Underfitting 
D. Feature scaling

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Question # 14

Which of the following AI solutions is BEST used to generate standardized reports using unstructured customer feedback? 

A. Anomaly detection 
B. Natural language processing (NLP) 
C. Predictive analytics 
D. Recommendation engines 

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Question # 15

The accuracy of an AI model used for product recommendations, trained on data from a specific year, is declining two years later as customer buying patterns have shifted toward sustainable products. Which of the following is the MOST likely cause?  

A. Data drift 
B. Schema drift 
C. Data labeling 
D. Covariate shift 

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Question # 16

Which of the following presents the GREATEST risk when an organization deploys a machine learning model in a public cloud environment for real-time predictions? 

A. Cloud provider employees have limited AI skills 
B. AI model audit trails have not been comprehensively documented 
C. The service level agreement (SLA) does not include network latency and inference guarantees 
D. The cloud provider has not adopted an ethical AI governance framework 

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Question # 17

Which of the following is the MOST important reason for measuring the AI system's performance against predefined metrics in a staging environment? 

A. To ensure the AI system complies with privacy standards before production deployment 
B. To confirm the AI system has been trained on the most recent dataset 
C. To validate that the AI system meets requirements prior to release 
D. To verify that the AI system's user interface is aligned with accessibility standards 

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Question # 18

An AI audit tool incorrectly flagged that business decisions were biased, leading to inappropriate management action plans. Which of the following can BEST prevent this risk?

A. Use different fairness definitions. 
B. Apply explainable AI validation methods.
 C. Reweight groups to oversample. 
D. Document assumptions and record scope. 

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Question # 19

Which of the following is the GREATEST benefit of integrating AI in ransomware prevention? 

A. Maintaining the confidentiality of threat intelligence analysis 
B. Analyzing large volumes of data to enhance detection of anomalies 
C. Enabling more rapid identification of parties responsible for attacks 
D. Reducing resources required for traditional cybersecurity defenses 

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Question # 20

An insurance organization deployed an AI tool for assigning customer risk levels. An IS auditor discovers that the learning algorithm is vulnerable to adversarial attacks. Which of the following is the BEST course of action?

A. Review the speed of learning adaptation. 
B. Assess the response time to the attacks. 
C. Evaluate the number of system logs maintained. 
D. Validate the process for handling manipulated inputs. 

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Question # 21

Which of the following BEST helps in detecting AI model drift?

A. Engaging periodic external reviews of model outputs and identifying root causes 
B. Establishing a model performance baseline and implementing continuous monitoring 
C. Using linear regression techniques and conducting cluster analysis 
D. Evaluating model accuracy rates for stability and performing qualitative data analysis 

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Question # 22

The internal audit department of a large global organization is evaluating the use of an AIbased 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?

A. Unauthorized access to sensitive data by the cloud vendor 
B. Privacy concerns arising from data storage in the cloud 
C. Potential data loss resulting from service downtime or failures
D. Inaccurate transcriptions impacting reliability of audit records

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Question # 23

When an IS auditor reviews audit evidence gathered by AI, which of the following practices should the auditor perform to ensure the reliability of the evidence?

A. Review the AI model card. 
B. Interview the organizational management team. 
C. Evaluate the completeness of the evidence collection procedure. 
D. Validate the evidence against source documents.

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Question # 24

Which of the following techniques BEST enhances the security and robustness of AI models against adversarial attacks?

A. AI security awareness training 
B. User access reviews 
C. Input token limitation 
D. Defensive distillation 

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Question # 25

In deep learning neural networks, which of the following layers is considered MOST important for an IS auditor to evaluate because it performs feature extraction to mimic human decision-making?

A. Hyperparameter 
B. Hidden 
C. Input 
D. Output 

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