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Isaca AAIR Sample Questions
Question # 1
A financial services organization is subject to regulatory examination on its AI risk management
practices. The examiner identifies that the organization lacks documented evidence of: (1) AI risk
appetite statements, (2) risk-based AI system classification, (3) AI incident response procedures,
and (4) board oversight of AI risk. The examiner rates the overall AI risk management program as
'Unsatisfactory.' Which remediation should be prioritized FIRST?
A. Develop AI incident response procedures — these have the most direct operational impact. B. Establish board oversight mechanisms and AI risk appetite — as these are the foundationalgovernance elements upon which all other AI risk management activities depend. C. Implement AI system risk classification — this enables risk-based prioritization of all otheractivities. D. Document existing AI controls to demonstrate maturity to the regulator.
Answer: B
Explanation:
Governance is the foundation of any risk management program. Without clear board oversight and a defined AI risk appetite, the organization lacks direction and accountability for how risks should be managed.
These elements establish the tone at the top, guiding risk classification, incident response, and control documentation.
Regulators expect board-level involvement and a documented risk appetite as evidence of mature governance. Addressing this gap first ensures that subsequent remediation efforts (classification, incident response, controls) are aligned with organizational priorities.
Why not the others?
A. Develop AI incident response procedures ? Important for operations, but incident response is tactical. Without governance, procedures may lack authority or alignment.
C. Implement AI system risk classification ? Useful for prioritization, but classification depends on the organization’s defined risk appetite and governance framework.
D. Document existing AI controls ? Helps demonstrate maturity, but documenting controls without governance and oversight does not satisfy regulators’ concerns about accountability.
Question # 2
An AI model used in production has a known vulnerability that could be exploited. A patch isavailable but requires a 4-hour maintenance window during business hours. The business unitrefuses to accept the downtime. The AI risk manager must decide. What is the MOST appropriateaction?
A. Accept the risk and continue operating the vulnerable system indefinitely. B. Formally document the risk, escalate to the appropriate governance level for risk acceptancedecision, and define compensating controls for the interim period. C. Implement the patch without business unit approval. D. Wait until the next scheduled maintenance window, even if months away.
Answer: B
Explanation:
When a known vulnerability exists and a patch is available, the risk manager cannot simply ignore it or act unilaterally.
The appropriate governance process must be followed:
Document the risk clearly, including the vulnerability, potential impact, and business unit’s refusal of downtime.
Escalate to governance/board-level risk committees for a formal risk acceptance decision.
Define compensating controls (e.g., increased monitoring, network segmentation, access restrictions) to reduce exposure until the patch can be applied.
Why not the others?
A. Accept the risk indefinitely ? Irresponsible; leaves the system exposed without oversight.
C. Implement the patch without business unit approval ? Breaks governance and could damage trust/business operations.
D. Wait until the next scheduled maintenance window (months away) ? Delays remediation unnecessarily and increases exposure.
Question # 3
An organization's AI risk management program operates independently from its enterprise riskmanagement (ERM) framework. AI risks are not reflected in the enterprise risk register orescalated to the board through ERM reporting. What is the GREATEST risk of this siloedapproach?
A. The AI risk team may develop redundant risk management processes. B. AI risks may not receive appropriate executive attention, resource allocation, or strategic risktreatment, leaving the organization exposed to material risks that the board is unaware of. C. The AI program may miss technical risk factors identified by the enterprise risk team. D. Compliance auditors may identify the disconnect and cite the organization.
Answer: B
Explanation:
The greatest risk of keeping AI risk management siloed from enterprise risk management (ERM) is that critical AI risks are invisible at the enterprise level.
Without integration:
AI risks won’t appear in the enterprise risk register.
The board and executives won’t have visibility, meaning they cannot allocate resources or make strategic decisions to mitigate them.
Material risks could escalate unchecked, potentially leading to regulatory, reputational, or financial damage.
Why not the others?
A. Redundant processes ? Inefficient, but not the greatest risk.
C. Missing technical risk factors ? Possible, but technical blind spots are less severe than lack of executive oversight.
D. Compliance auditors citing the disconnect ? A consequence, but the root issue is lack of board visibility and governance.
Question # 4
What is the PRIMARY purpose of an AI Risk Treatment Plan?
A. To document all AI systems in production. B. To define specific actions, timelines, owners, and resources required to bring AI risks towithin acceptable levels. C. To record historical AI incidents for regulatory reporting. D. To establish AI performance benchmarks.
Answer: B
Explanation:
An AI Risk Treatment Plan is a structured document that outlines how identified AI risks will be managed.
Its primary purpose is to ensure risks are reduced to acceptable levels by specifying:
Actions ? What needs to be done to mitigate or manage the risk.
Timelines ? When the actions will be completed.
Owners ? Who is responsible for executing each action.
Resources ? What tools, funding, or personnel are required.
Why not the others?
A. Document all AI systems in production ? That’s more of an AI inventory, not a risk treatment plan.
C. Record historical AI incidents ? That’s part of an incident log or reporting process, not risk treatment.
D. Establish AI performance benchmarks ? That relates to model evaluation and monitoring, not risk treatment.
Question # 5
An organization wants to assess the effectiveness of its AI risk controls. Which approach provides
the MOST comprehensive assessment?
A. Self-assessment by the AI development team. B. A combination of continuous monitoring metrics, periodic independent control testing, andexternal audit. C. Annual compliance review by the legal department. D. Vendor-provided performance reports.
Answer: B
Explanation:
To truly assess the effectiveness of AI risk controls, you need a multi-layered approach:
Continuous monitoring metrics ? Provide real-time visibility into AI system performance, anomalies, and control effectiveness.
Periodic independent control testing ? Ensures controls are validated objectively, not just by the development team.
External audit ? Adds credibility and regulatory assurance, confirming that controls meet industry and compliance standards.
This combination provides the most comprehensive assessment because it balances ongoing oversight, independent validation, and external assurance.
Why not the others?
A. Self-assessment by the AI development team ? Biased and limited; lacks independence.
C. Annual compliance review by the legal department ? Too narrow and infrequent; focuses on compliance, not operational effectiveness.
D. Vendor-provided performance reports ? Useful, but vendors may not highlight weaknesses; lacks independence and comprehensiveness.
Question # 6
An organization uses AI to generate personalized financial advice for retail investors. A postdeployment review discovers the AI system recommends higher-risk products to lower-incomecustomers. The organization's risk appetite explicitly prohibits AI systems that produce outcomescorrelated with customer income level in ways that disadvantage lower-income groups. What is theMOST serious concern?
A. The AI may be generating advice that does not align with individual investor risk profiles. B. The AI system is operating outside the organization's stated risk appetite, potentiallyproducing discriminatory outcomes that violate regulatory obligations and ethical standards. C. The AI may expose the organization to increased market risk. D. Higher-risk product recommendations may generate more revenue.
Answer: B
Explanation:
Option A: A is incorrect. Suitability of advice is a related concern but is secondary to the identified
discriminatory pattern that violates risk appetite.
Option B (CORRECT): B is correct. The system is demonstrably violating the risk appetite (incomecorrelated disadvantageous recommendations), which is a governance failure. This creates regulatory
risk (potential violation of fair treatment regulations), ethical risk, and reputational risk. The risk appetite
violation is the most serious concern — it requires immediate escalation and remediation.
Option C: C is incorrect. Market risk from investment products is a financial risk separate from the AI
governance failure described.
Option D: D is incorrect. Revenue generation does not justify discriminatory AI outcomes and is an
ethically problematic framing.
Question # 7
An AI risk manager is reviewing vendor contracts for AI services. Which contractual provision is
MOST important from an AI risk governance perspective?
A. Pricing and volume discount terms. B. Right to audit AI system performance, transparency requirements, data handling obligations,and incident notification obligations. C. Vendor's marketing and branding rights. D. Automatic contract renewal terms.
Answer: B
Explanation:
Option A: A is incorrect. Pricing terms are commercial, not governance provisions.
Option B (CORRECT): B is correct. From an AI governance perspective, the most important contractual
provisions are those that enable ongoing oversight: audit rights (enables accountability), transparency
requirements (enables explainability), data handling obligations (enables privacy compliance), and
incident notification (enables timely response). These are the governance mechanisms in the contract.
Option C: C is incorrect. Branding rights are marketing terms with no AI governance relevance.
Option D: D is incorrect. Renewal terms are commercial provisions, not AI governance mechanisms.
Question # 8
An organization's AI incident response team receives an alert that an AI model used for fraud
detection has begun flagging 300% more transactions as fraudulent than its historical baseline,
with no apparent change in actual fraud rates. Which is the MOST appropriate FIRST action?
A. Disable the fraud detection AI and revert to manual review. B. Investigate whether the anomaly represents adversarial manipulation, data pipeline failure,or concept drift before taking operational action. C. Notify all customers flagged by the AI as suspected fraudsters. D. Engage the AI vendor to analyze the model and identify the cause
Answer: B
Explanation:
Option A: A is incorrect. Disabling the system is premature without understanding the cause — it could
be a critical security response or an overreaction depending on findings.
Option B (CORRECT): B is correct. A sudden 300% spike in fraud flags without a corresponding
increase in actual fraud is an anomaly that could represent data pipeline failure, adversarial
manipulation, or drift. Investigation to determine the root cause must precede operational action —
disabling the system or notifying customers prematurely could cause greater harm.
Option C: C is incorrect. Notifying flagged customers before understanding the anomaly would be
deeply inappropriate if the flags are false positives from a model malfunction.
Option D: D is incorrect. Vendor engagement may be appropriate but is not the first action — initial
investigation by the internal team should precede external escalation.
Question # 9
An AI risk manager identifies a control gap: the organization's AI systems are monitored for
accuracy but not for fairness metrics. What type of risk does this gap MOST represent?
A. Operational risk — the system may become unreliable. B. Compliance and ethical risk — discriminatory outputs may go undetected, creatingregulatory and reputational exposure. C. Technology risk — the monitoring infrastructure is insufficient. D. Strategic risk — AI investments may not achieve business objectives.
Answer: B
Explanation:
Option A: A is incorrect. Operational risk relates to system reliability, not the fairness monitoring gap.
Option B (CORRECT): B is correct. Failing to monitor for fairness creates compliance risk (violations of
anti-discrimination laws, GDPR, EU AI Act) and ethical risk (perpetuating discriminatory outcomes). This
is specifically a governance gap that goes beyond operational or technology risk.
Option C: C is incorrect. Infrastructure sufficiency is a technology concern, but the gap described is
about what is being measured, not how.
Option D: D is incorrect. Strategic risk relates to value delivery, not the specific fairness monitoring gap.
Question # 10
An organization is building a supply chain AI system that relies on data feeds from multiple external
partners. What is the PRIMARY third-party supply chain risk for this AI system?
A. Partners may charge higher fees for data access. B. Compromised, manipulated, or low-quality external data feeds could degrade modelperformance or enable supply chain attacks. C. Partners may not provide real-time data updates. D. Integration complexity may increase development costs.
Answer: B
Explanation:
Option A: A is incorrect. Pricing is a commercial concern, not the primary AI risk.
Option B (CORRECT): B is correct. The primary supply chain risk for AI systems dependent on external
data is the integrity and quality of those inputs. Compromised data feeds (through partner breaches or
malicious manipulation) directly impact model outputs and could enable indirect adversarial attacks — a
recognized AI supply chain threat.
Option C: C is incorrect. Latency is an operational performance concern, not the primary supply chain
risk.
Option D: D is incorrect. Development costs are a project management concern, not the primary AI risk.
Question # 11
An organization discovers that its AI vendor has a subcontractor processing training data in a
jurisdiction with inadequate data protection laws. This arrangement was not disclosed during
vendor due diligence. The organization is subject to GDPR. What is the GREATEST risk and
MOST appropriate response?
A. Risk: vendor reputation. Response: Notify customers of the data processing arrangements. B. Risk: GDPR violation through unauthorized international transfer of personal data.Response: Immediately assess transfer compliance, require the vendor to remediate, andconsider contract suspension until compliant. C. Risk: Data quality degradation. Response: Require the subcontractor to demonstrate datahandling certifications. D. Risk: Competitive intelligence leakage. Response: Conduct a data classification review.
Answer: B
Explanation:
Option A: A is incorrect. Vendor reputation is a secondary concern. GDPR compliance is the primary
legal risk. Customer notification may be required but is not the immediate priority.
Option B (CORRECT): B is correct. Under GDPR, transferring personal data to jurisdictions without
adequate protection without appropriate safeguards is a violation (Articles 44–49). The organization is
the data controller and bears accountability. Immediate assessment, vendor remediation, and potential
suspension are the required governance actions.
Option C: C is incorrect. Data quality is a model performance concern, not the greatest risk in this
scenario.
Option D: D is incorrect. Competitive intelligence leakage is a confidentiality risk but is not the greatest
risk given the GDPR implications.
Question # 12
Which of the following BEST describes 'risk transfer' as an AI risk treatment option?
A. Moving the AI system to a different business unit to reassign accountability. B. Shifting financial consequences of an AI risk to a third party, such as through insurance orcontractual indemnification. C. Reducing AI risk exposure through the implementation of preventive controls. D. Eliminating an AI system to remove the associated risk entirely.
Answer: B
Explanation:
Option A: A is incorrect. Moving a system to a different business unit reassigns management, not risk —
the organizational risk remains.
Option B (CORRECT): B is correct. Risk transfer shifts the financial consequences of a risk to a third
party — typically through insurance or contractual indemnification. It does not eliminate the risk or its
operational impact, but reduces the organization's financial exposure.
Option C: C is incorrect. Implementing preventive controls describes risk mitigation, not risk transfer.
Option D: D is incorrect. Eliminating a system to remove risk describes risk avoidance, not risk transfer.
Question # 13
An organization is developing its AI risk reporting framework for the board. What information is
MOST important to include in board-level AI risk reporting?
A. Technical details of AI model architectures and training parameters. B. AI risk exposure levels, trends, significant incidents, risk appetite compliance status, andrecommended governance actions. C. Detailed audit logs of all AI model outputs. D. Vendor SLA compliance statistics.
Answer: B
Explanation:
Option A: A is incorrect. Technical architecture details are not appropriate for board-level reporting —
they are for technical governance committees.
Option B (CORRECT): B is correct. Board-level reporting should provide strategic insight: overall risk
exposure and trends, incidents requiring board awareness, whether the organization is operating within
risk appetite, and governance decisions needed from the board. Strategic perspective, not technical
detail.
Option C: C is incorrect. Audit logs are operational records, not board-level reporting content.
Option D: D is incorrect. Vendor SLA statistics are operational metrics appropriate for management
reporting, not primary board-level AI risk content.
Question # 14
An organization's AI system for automated trading generates anomalous trades during a marketvolatility event, causing significant financial loss. Post-incident analysis reveals the model was nottested against extreme market conditions. Which control would have been MOST effective inpreventing this incident?
A. Real-time monitoring with automatic trading halt triggers when model outputs exceeddefined thresholds. B. Stress testing the AI model against historical market crisis scenarios before deployment. C. Implementing a 24-hour delay on AI-generated trades for human review. D. Diversifying AI trading models across multiple vendors.
Answer: A
Explanation:
Option A (CORRECT): A is correct. While stress testing (B) would have helped identify the vulnerability,
the MOST effective prevention in an automated trading environment is a real-time kill switch with
predefined trading halt thresholds. This is a preventive control that stops anomalous trading at the
moment it occurs, limiting financial exposure regardless of model failure mode.
Option B: B is incorrect. Stress testing is a validation control that would have identified the gap before
deployment but, in this scenario, the incident has already occurred. The question asks what control
would be most effective at preventing the financial loss — a real-time halt is more effective than a predeployment test alone.
Option C: C is incorrect. A 24-hour delay defeats the purpose of automated trading and is operationally
impractical.
Option D: D is incorrect. Vendor diversification addresses concentration risk, not the model testing and
live circuit-breaker gaps that caused this incident.
Question # 15
An organization implements an AI system that monitors employee communications for policyviolations. An employee files a complaint alleging the monitoring is invasive and not disclosed inthe employment agreement. What is the PRIMARY governance risk?
A. The AI system may produce inaccurate monitoring results. B. The organization may have failed to meet transparency, consent, and privacy obligationsregarding employee surveillance. C. The employee may share confidential information externally. D. The AI monitoring system may be susceptible to adversarial manipulation.
Answer: B
Explanation:
Option A: A is incorrect. Accuracy is a performance concern, not the primary governance risk in this
complaint scenario.
Option B (CORRECT): B is correct. Deploying employee monitoring AI without disclosure and consent
creates significant privacy, employment law, and governance risks. Transparency and informed consent
are fundamental requirements for employee monitoring systems under most regulatory frameworks.
Option C: C is incorrect. Employee data leakage is a security concern unrelated to the governance
failure described.
Option D: D is incorrect. Adversarial manipulation is a security risk, not the primary governance issue
raised by the employee complaint.
Question # 16
An organization's AI vendor provides a service level agreement (SLA) promising 99.9% uptime foran AI-powered customer service system. During an incident, the system is down for 12 hours,causing significant customer complaints and lost revenue. What risk management lesson does thisincident MOST highlight?
A. SLA-based contractual guarantees are insufficient substitutes for internal AI resiliencecontrols and business continuity planning. B. The organization should negotiate a higher SLA of 99.99% with the vendor. C. The vendor should be replaced with a more reliable provider. D. AI systems should never be used for customer-facing services.
Answer: A
Explanation:
Option A (CORRECT): A is correct. SLAs establish accountability and financial penalties but do not
prevent downtime or protect the business during an outage. The organization's own resilience controls
(failover, manual fallback, BCP) are essential complements to SLA protections. Over-reliance on SLAs is
a third-party risk management failure.
Option B: B is incorrect. A higher SLA reduces contractual exposure but does not address the
operational resilience gap.
Option C: C is incorrect. Vendor replacement may or may not be appropriate — the core lesson is about
organizational resilience, not vendor selection.
Option D: D is incorrect. Avoiding AI for customer-facing services is an extreme and unsupported
conclusion from a single incident.
Question # 17
An organization's AI governance committee reviews a report showing that 40% of theorganization's AI systems have no defined risk owner, 25% have not been assessed in over twoyears, and 15% have open high-severity risks with no treatment plans. The committee must decideon priority actions. What should be the FIRST priority?
A. Conduct comprehensive new risk assessments for all systems. B. Assign risk owners to the 40% of systems lacking ownership — because withoutaccountability, no other governance action can be effectively executed. C. Develop treatment plans for the 15% of systems with open high-severity risks. D. Report the governance gaps to the board and request additional budget.
Answer: B
Explanation:
Option A: A is incorrect. Conducting assessments is important, but assessments without assigned
owners will have no one to act on the findings.
Option B (CORRECT): B is correct. Accountability is the foundational governance prerequisite. Without
defined risk owners for 40% of systems, there is no responsible party to execute risk assessments,
implement treatments, or maintain oversight. Ownership must be established first for all other
governance actions to be effective.
Option C: C is incorrect. Addressing high-severity open risks is critical, but these systems may be
among the 40% without owners — creating treatment plans without owners is ineffective.
Option D: D is incorrect. Board reporting and budget requests are appropriate actions, but the
immediate operational priority is establishing accountability.
Question # 18
Which of the following BEST describes the purpose of AI red-team testing?
A. To assess the financial return on investment of AI systems. B. To simulate adversarial attacks and misuse scenarios to identify vulnerabilities in AI systemsbefore they can be exploited. C. To review AI system code quality and development standards. D. To validate AI model accuracy on production data.
Answer: B
Explanation:
Option A: A is incorrect. ROI assessment is a financial analysis activity, not red-team testing.
Option B (CORRECT): B is correct. Red-team testing involves simulating adversarial attacks, misuse
scenarios, and edge cases to proactively identify vulnerabilities in AI systems. It is a proactive security
and risk control that discovers weaknesses before malicious actors do.
Option C: C is incorrect. Code review is a software quality control, distinct from adversarial testing.
Option D: D is incorrect. Production data accuracy validation is model validation, not red-team testing.
Question # 19
An AI risk manager conducts a Business Impact Analysis (BIA) for an AI-powered supply chain
optimization system. The BIA should prioritize which factor FIRST?
A. Cost of retraining the AI model after failure. B. Maximum tolerable downtime (MTD) and recovery time objectives (RTO) based on businessimpact of the system being unavailable. C. Technical architecture of the AI system for backup planning. D. Number of users who depend on the system daily.
Answer: B
Explanation:
Option A: A is incorrect. Retraining costs are a recovery cost, not the primary BIA priority.
Option B (CORRECT): B is correct. BIA prioritizes business impact quantification — specifically
maximum tolerable downtime and recovery time objectives. These determine how critical the system is
to the business and drive all subsequent continuity planning decisions.
Option C: C is incorrect. Technical architecture informs recovery planning but is not the primary BIA
concern.
Option D: D is incorrect. User count is one input to impact assessment but does not by itself determine
business criticality.
Question # 20
During an AI risk assessment, a risk manager uses a quantitative approach and calculates the
Annual Loss Expectancy (ALE) for an AI system failure scenario as $2.4M. The cost of
implementing a control to reduce this risk is $800K annually. However, the control would only
reduce the probability of loss by 40%. Should the control be implemented based purely on
quantitative analysis?
A. Yes — any reduction in risk justifies control implementation. B. No — the control cost ($800K) exceeds the risk reduction benefit (40% of $2.4M = $960Knet risk reduction). Wait — the benefit is $960K which exceeds $800K. Yes, implement. C. No — quantitative analysis alone is insufficient for AI risk decisions without qualitativefactors. D. Yes — but only if the remaining 60% residual risk is within the risk appetite.
Answer: D
Explanation:
Option A: A is incorrect. Cost-benefit must be assessed. Not all risk reductions justify control cost.
Option B: B is incorrect. While the math in option B reaches the right numeric conclusion, it does not
address the critical residual risk and risk appetite requirement — making D a more complete governance
answer.
Option C: C is incorrect. Quantitative analysis is valid and useful. The issue is not the method's
sufficiency but the need to also consider residual risk appetite.
Option D (CORRECT): D is correct. Quantitatively the control appears justified (cost-benefit: $960K risk
reduction vs $800K cost). However, after implementing the control, 60% of the risk remains (ALE still
~$1.44M). Risk appetite alignment must be confirmed — if the residual risk exceeds appetite, additional
controls are required. Risk quantification and risk appetite alignment must both be satisfied.
