cert
cert-1
cert-2

Pass Isaca AAIA Exam in First Attempt Guaranteed!

Get 100% Latest Exam Questions, Accurate & Verified Answers to Pass the Actual Exam!
30 Days Free Updates, Instant Download!

cert-5
cert-6
AAIA Exam - Verified By Experts
AAIA Premium Bundle
$14.99

AAIA Premium Bundle

$74.99
$89.98
  • Premium File 556 Questions & Answers. Last update: Nov 08, 2026
  • Training Course 110 Video Lectures
 
$89.98
$74.99
accept 22 downloads in last 7 days
block-screenshots
Purchase Isaca AAIA Exam Training Products Individually
Isaca AAIA Premium File
Premium File 556 Q&A
$76.99$69.99
Isaca AAIA Video Training Course
Training Course 110 Lectures
$21.99 $19.99
Isaca AAIA Practice Test 33

Question 320

An independent AI auditor reviews this case: An insurer retains raw call audio for prediction despite a validated nonidentifying feature representation. Which TWO complementary elements should the auditor seek: an effective corrective control and the most probative independent evidence? Select TWO answers.

  1. Design usable human review with understandable context, authority to intervene, escalation and traceable decisions.
  2. Compare use-case requirements, deterministic baselines, quantitative error rates, grounded outputs and exception handling.
  3. Assume pseudonymized identifiers are anonymous and keep unneeded raw attributes forever.
  4. Compare feature necessity, identifiability, model utility, transformation design and data retention.
  5. Test whether less identifying features or on-premises transformations satisfy the business purpose.

Explanation

Correct Answers

D:

The reason it is necessary is: Privacy by design changes processing architecture rather than relying solely on downstream access policy. For this situation: An insurer retains raw call audio for prediction despite a validated nonidentifying feature representation.

E:

The reason it is necessary is: Privacy by design changes processing architecture rather than relying solely on downstream access policy. This response fits the risk associated with Privacy by design for model features: Test whether less identifying features or on-premises transformations satisfy the business purpose.

Incorrect Answers

A:

This option concerns Human oversight design for high-impact AI, which is a related but different AI governance concern. The audit must corroborate: Compare feature necessity, identifiability, model utility, transformation design and data retention.

B:

This option concerns Predictive versus generative model task fit, which is a related but different AI governance concern. For this situation: An insurer retains raw call audio for prediction despite a validated nonidentifying feature representation.

C:

It misses the key control principle: Privacy by design changes processing architecture rather than relying solely on downstream access policy.

Question 321

A governance and assurance review uncovers the following: A staffing model stores employee free-text medical comments inside reusable embeddings. What is the MOST appropriate risk-based audit recommendation that addresses the root control weakness? Select ONE best answer.

  1. Map international processing locations and lawful transfer safeguards through vendors, subprocessors and backups.
  2. Conduct a documented impact assessment of purpose, necessity, proportionality, alternatives and safeguards before deployment.
  3. Assume pseudonymized identifiers are anonymous and keep unneeded raw attributes forever.
  4. Test whether less identifying features or on-premises transformations satisfy the business purpose.

Explanation

Correct Answer

D:

The reason it is necessary is: Privacy by design changes processing architecture rather than relying solely on downstream access policy. Independent audit evidence includes: Compare feature necessity, identifiability, model utility, transformation design and data retention.

Incorrect Answers

A:

This option concerns Cross-border AI data transfer mapping, which is a related but different AI governance concern. The decisive principle here is: Privacy by design changes processing architecture rather than relying solely on downstream access policy.

B:

This option concerns Privacy impact assessment for biometric AI, which is a related but different AI governance concern. The decisive principle here is: Privacy by design changes processing architecture rather than relying solely on downstream access policy.

C:

This attractive shortcut does not resolve the Privacy by design for model features weakness: Assume pseudonymized identifiers are anonymous and keep unneeded raw attributes forever. In this case: A staffing model stores employee free-text medical comments inside reusable embeddings.

Question 322

A risk-based audit engagement examines this operating condition: A staffing model stores employee free-text medical comments inside reusable embeddings. Which principle BEST explains why the observed practice is a material governance or control concern? Select ONE best answer.

  1. Assume pseudonymized identifiers are anonymous and keep unneeded raw attributes forever.
  2. Generative fluency and predictive statistical accuracy address different tasks; auditors must test fitness for a defined business decision.
  3. Availability of data inside a company does not imply every new AI training purpose is authorized.
  4. Privacy by design changes processing architecture rather than relying solely on downstream access policy.

Explanation

Correct Answer

D:

The acceptable verified outcome is: Validated reduced-data features meet model purpose without exposing unnecessary identities or content. The corrective action is: Test whether less identifying features or on-premises transformations satisfy the business purpose.

Incorrect Answers

A:

This attractive shortcut does not resolve the Privacy by design for model features weakness: Assume pseudonymized identifiers are anonymous and keep unneeded raw attributes forever. For this situation: A staffing model stores employee free-text medical comments inside reusable embeddings.

B:

This option concerns Predictive versus generative model task fit, which is a related but different AI governance concern. The audit must corroborate: Compare feature necessity, identifiability, model utility, transformation design and data retention.

C:

This option concerns Purpose limitation in AI training data reuse, which is a related but different AI governance concern. The audit must corroborate: Compare feature necessity, identifiability, model utility, transformation design and data retention.

Question 323

An audit committee asks for a defensible assessment of this situation: A staffing model stores employee free-text medical comments inside reusable embeddings. What evidence should the auditor examine FIRST to substantiate or challenge the control owner’s claim? Select ONE best answer.

  1. Assume pseudonymized identifiers are anonymous and keep unneeded raw attributes forever.
  2. Review data categories, stakeholder impacts, alternatives, lawful basis, accuracy and mitigation decisions.
  3. Inspect provider terms, retention schedules, index lifecycle, backups, deletion tickets and test identifiers.
  4. Compare feature necessity, identifiability, model utility, transformation design and data retention.

Explanation

Correct Answer

D:

The reason it is necessary is: Privacy by design changes processing architecture rather than relying solely on downstream access policy. The corrective action is: Test whether less identifying features or on-premises transformations satisfy the business purpose.

Incorrect Answers

A:

For this situation: A staffing model stores employee free-text medical comments inside reusable embeddings.

B:

This option concerns Privacy impact assessment for biometric AI, which is a related but different AI governance concern. For this situation: A staffing model stores employee free-text medical comments inside reusable embeddings.

C:

This option concerns AI inference retention and right-to-erasure handling, which is a related but different AI governance concern. The audit must corroborate: Compare feature necessity, identifiability, model utility, transformation design and data retention.

Question 324

During an AI controls assessment, the team learns that a staffing model stores employee free-text medical comments inside reusable embeddings. After management addresses the issue, which result MOST convincingly demonstrates effective remediation? Select ONE best answer.

  1. Validated reduced-data features meet model purpose without exposing unnecessary identities or content.
  2. Normal tasks succeed with reduced personal information and prohibited fields do not enter model requests.
  3. Assume pseudonymized identifiers are anonymous and keep unneeded raw attributes forever.
  4. Selected components meet task-specific accuracy, controllability and auditability tests on representative work.

Explanation

Correct Answer

A:

The reason it is necessary is: Privacy by design changes processing architecture rather than relying solely on downstream access policy. In this case: A staffing model stores employee free-text medical comments inside reusable embeddings.

Incorrect Answers

B:

This option concerns Data minimization and PII in prompts, which is a related but different AI governance concern. The decisive principle here is: Privacy by design changes processing architecture rather than relying solely on downstream access policy.

C:

The auditor should instead examine: Compare feature necessity, identifiability, model utility, transformation design and data retention.

D:

This option concerns Predictive versus generative model task fit, which is a related but different AI governance concern. For this situation: A staffing model stores employee free-text medical comments inside reusable embeddings.

Question 325

An independent AI auditor reviews this case: An audit report cites the NIST AI RMF but cannot connect any model risk to accountable decisions and measures. What is the MOST appropriate risk-based audit recommendation that addresses the root control weakness? Select ONE best answer.

  1. Require time-bound exception approvals, explicit risk ownership, compensating measures and periodic review.
  2. Map accountable GOVERN processes, context under MAP, evidence-based MEASURE and decisions under MANAGE without mischaracterizing voluntary guidance.
  3. Maintain jurisdiction-specific legal mapping with version dates, accountable counsel and periodic applicability reviews.
  4. Treat naming all four NIST functions as proof that every AI risk has been addressed.

Explanation

Correct Answer

B:

The reason it is necessary is: NIST AI RMF 1.0 provides risk-management functions, not a universal legal compliance certificate. This is the proportionate control response to NIST AI RMF governance and measurement alignment: Map accountable GOVERN processes, context under MAP, evidence-based MEASURE and decisions under MANAGE without mischaracterizing voluntary guidance.

Incorrect Answers

A:

This option concerns AI policy exception governance, which is a related but different AI governance concern. It does not establish control effectiveness for NIST AI RMF governance and measurement alignment.

C:

This option concerns Regulatory change tracking without overclaiming compliance, which is a related but different AI governance concern. It does not establish control effectiveness for NIST AI RMF governance and measurement alignment.

D:

This attractive shortcut does not resolve the NIST AI RMF governance and measurement alignment weakness: Treat naming all four NIST functions as proof that every AI risk has been addressed.

Question 326

A governance and assurance review uncovers the following: An audit report cites the NIST AI RMF but cannot connect any model risk to accountable decisions and measures. Which principle BEST explains why the observed practice is a material governance or control concern? Select ONE best answer.

  1. NIST AI RMF 1.0 provides risk-management functions, not a universal legal compliance certificate.
  2. Treat naming all four NIST functions as proof that every AI risk has been addressed.
  3. Responsible AI assessment includes human and social outcomes beyond aggregate technical model accuracy.
  4. ISO/IEC 42001 describes requirements for an AI management system, not instant proof from a policy document.

Explanation

Correct Answer

A:

Independent audit evidence includes: Inspect AI inventory, contextual risk register, model evaluations, management treatment and oversight minutes. This is the applicable AI audit principle for NIST AI RMF governance and measurement alignment: NIST AI RMF 1.0 provides risk-management functions, not a universal legal compliance certificate.

Incorrect Answers

B:

This attractive shortcut does not resolve the NIST AI RMF governance and measurement alignment weakness: Treat naming all four NIST functions as proof that every AI risk has been addressed. For this situation: An audit report cites the NIST AI RMF but cannot connect any model risk to accountable decisions and measures.

C:

This option concerns Fairness and accessibility ethical governance, which is a related but different AI governance concern. It does not establish control effectiveness for NIST AI RMF governance and measurement alignment.

D:

This option concerns ISO IEC 42001 AI management system controls, which is a related but different AI governance concern. It does not establish control effectiveness for NIST AI RMF governance and measurement alignment.

Question 327

A risk-based audit engagement examines this operating condition: An audit report cites the NIST AI RMF but cannot connect any model risk to accountable decisions and measures. What evidence should the auditor examine FIRST to substantiate or challenge the control owner’s claim? Select ONE best answer.

  1. Treat naming all four NIST functions as proof that every AI risk has been addressed.
  2. Inspect AI inventory, contextual risk register, model evaluations, management treatment and oversight minutes.
  3. Inspect UI disclosures, synthesized content labels, user testing, jurisdiction analysis and change approvals.
  4. Review cluster validation, anomaly score distributions, seasonal control populations, downstream actions and analyst adjudications.

Explanation

Correct Answer

B:

The reason it is necessary is: NIST AI RMF 1.0 provides risk-management functions, not a universal legal compliance certificate. This evidence directly tests the asserted control for NIST AI RMF governance and measurement alignment: Inspect AI inventory, contextual risk register, model evaluations, management treatment and oversight minutes.

Incorrect Answers

A:

This attractive shortcut does not resolve the NIST AI RMF governance and measurement alignment weakness: Treat naming all four NIST functions as proof that every AI risk has been addressed. The auditor should instead examine: Inspect AI inventory, contextual risk register, model evaluations, management treatment and oversight minutes.

C:

This option concerns AI transparency and meaningful disclosure, which is a related but different AI governance concern. It does not establish control effectiveness for NIST AI RMF governance and measurement alignment.

D:

This option concerns Unsupervised anomaly detection and alert governance, which is a related but different AI governance concern. It does not establish control effectiveness for NIST AI RMF governance and measurement alignment.

Question 328

An audit committee asks for a defensible assessment of this situation: An audit report cites the NIST AI RMF but cannot connect any model risk to accountable decisions and measures. After management addresses the issue, which result MOST convincingly demonstrates effective remediation? Select ONE best answer.

  1. The documented risk cycle links context, measurement, ownership and treatment for sampled systems.
  2. Organization documents role-specific obligations and controls for its actual use and checks changes over time.
  3. Affected users receive meaningful notice where required and can distinguish AI outputs from human decisions.
  4. Treat naming all four NIST functions as proof that every AI risk has been addressed.

Explanation

Correct Answer

A:

The reason it is necessary is: NIST AI RMF 1.0 provides risk-management functions, not a universal legal compliance certificate. This is an observable validation result for NIST AI RMF governance and measurement alignment, not just management assurance: The documented risk cycle links context, measurement, ownership and treatment for sampled systems.

Incorrect Answers

B:

This option concerns EU AI Act role and risk classification, which is a related but different AI governance concern. It does not establish control effectiveness for NIST AI RMF governance and measurement alignment.

C:

This option concerns AI transparency and meaningful disclosure, which is a related but different AI governance concern. For this situation: An audit report cites the NIST AI RMF but cannot connect any model risk to accountable decisions and measures.

D:

This attractive shortcut does not resolve the NIST AI RMF governance and measurement alignment weakness: Treat naming all four NIST functions as proof that every AI risk has been addressed. Map accountable GOVERN processes, context under MAP, evidence-based MEASURE and decisions under MANAGE without mischaracterizing voluntary guidance.

Question 329

During an AI controls assessment, the team learns that an AI committee uses GOVERN and MAP labels but has no MEASURE evidence or risk treatment under MANAGE. What is the MOST appropriate risk-based audit recommendation that addresses the root control weakness? Select ONE best answer.

  1. Evaluate foreseeable disparate impacts, accessibility needs, stakeholder participation and proportional mitigation.
  2. Map accountable GOVERN processes, context under MAP, evidence-based MEASURE and decisions under MANAGE without mischaracterizing voluntary guidance.
  3. Require time-bound exception approvals, explicit risk ownership, compensating measures and periodic review.
  4. Treat naming all four NIST functions as proof that every AI risk has been addressed.

Explanation

Correct Answer

B:

The reason it is necessary is: NIST AI RMF 1.0 provides risk-management functions, not a universal legal compliance certificate. Independent audit evidence includes: Inspect AI inventory, contextual risk register, model evaluations, management treatment and oversight minutes.

Incorrect Answers

A:

This option concerns Fairness and accessibility ethical governance, which is a related but different AI governance concern. The decisive principle here is: NIST AI RMF 1.0 provides risk-management functions, not a universal legal compliance certificate.

C:

This option concerns AI policy exception governance, which is a related but different AI governance concern. The decisive principle here is: NIST AI RMF 1.0 provides risk-management functions, not a universal legal compliance certificate.

D:

This attractive shortcut does not resolve the NIST AI RMF governance and measurement alignment weakness: Treat naming all four NIST functions as proof that every AI risk has been addressed. In this case: An AI committee uses GOVERN and MAP labels but has no MEASURE evidence or risk treatment under MANAGE.

Question 330

An independent AI auditor reviews this case: An AI committee uses GOVERN and MAP labels but has no MEASURE evidence or risk treatment under MANAGE. Which TWO complementary elements should the auditor seek: an effective corrective control and the most probative independent evidence? Select TWO answers.

  1. Inspect approved exception register, justifications, expiry, control alternatives and follow-up evidence.
  2. Map accountable GOVERN processes, context under MAP, evidence-based MEASURE and decisions under MANAGE without mischaracterizing voluntary guidance.
  3. Identify relevant AI Act roles, use-case classifications, jurisdictions and applicable obligations with competent legal input.
  4. Treat naming all four NIST functions as proof that every AI risk has been addressed.
  5. Inspect AI inventory, contextual risk register, model evaluations, management treatment and oversight minutes.

Explanation

Correct Answers

B:

The reason it is necessary is: NIST AI RMF 1.0 provides risk-management functions, not a universal legal compliance certificate. For this situation: An AI committee uses GOVERN and MAP labels but has no MEASURE evidence or risk treatment under MANAGE.

E:

The reason it is necessary is: NIST AI RMF 1.0 provides risk-management functions, not a universal legal compliance certificate. The corrective action is: Map accountable GOVERN processes, context under MAP, evidence-based MEASURE and decisions under MANAGE without mischaracterizing voluntary guidance.

Incorrect Answers

A:

This option concerns AI policy exception governance, which is a related but different AI governance concern. For this situation: An AI committee uses GOVERN and MAP labels but has no MEASURE evidence or risk treatment under MANAGE.

C:

This option concerns EU AI Act role and risk classification, which is a related but different AI governance concern. The decisive principle here is: NIST AI RMF 1.0 provides risk-management functions, not a universal legal compliance certificate.

D:

This attractive shortcut does not resolve the NIST AI RMF governance and measurement alignment weakness: Treat naming all four NIST functions as proof that every AI risk has been addressed. For this situation: An AI committee uses GOVERN and MAP labels but has no MEASURE evidence or risk treatment under MANAGE.

ISACA Advanced in AI Audit (AAIA) Practice Tests