2026 Updated Verified AAIR Q&As – Pass Guarantee or Full Refund [Q79-Q93]

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2026 Updated Verified AAIR Q&As – Pass Guarantee or Full Refund

[Oct-2026] AAIR Certification with Actual Questions from Real4dumps

ISACA AAIR Exam Syllabus Topics:

Section	Objectives
Topic 1: AI Lifecycle Controls	– Controls across AI development lifecycle 1. Model validation and testing 2. Data quality and preparation controls
Topic 2: Ethics, Privacy, and Responsible AI	– Ethical AI principles and compliance 1. Transparency and explainability 2. Bias and fairness mitigation
Topic 3: AI Governance and Strategy	– AI governance frameworks and organizational oversight 1. Roles and responsibilities in AI governance 2. Policy development for AI systems
Topic 4: AI Risk Management	– Risk identification and assessment for AI systems 1. Model risk identification 2. Operational risk in AI deployment
Topic 5: Regulatory and Compliance Requirements	– Global AI regulatory landscape 1. Industry standards for AI risk management 2. Data protection and privacy regulations

Q79. The MOST important consideration when reviewing existing business processes to determine their suitability for AI integration is whether:

the AI tools have been adopted widely within the industry.

the AI tools can be implemented immediately at scale.

staffing requirements and costs can be reduced by using AI tools.

the process includes clearly defined rules for AI tools to follow.

Q80. Which of the following is MOST important to verify when assessing open-source AI components in an organization’s supply chain?

Traceability for open-source AI artifacts

Geographic locations of open-source component suppliers

Implementation costs and resource requirements

Ownership of AI component security documentation

Q81. Which of the following is the PRIMARY concern associated with AI-based attacks on systems that store personal data?

Vulnerabilities exploitable by AI-based attacks may be more difficult to identify.

The cost of acquiring and vetting synthetic data to replace personal data may be prohibitive.

AI models may be able to identify combinations of attributes that can be used to re-identify individuals.

Data integrity testing may reveal personal data change logs.

Q82. Which of the following is the GREATEST risk when an AI system requires a specific safeguard that cannot be put in place because of technical constraints?

Elevated residual exposure due to lack of effective controls

Deterioration of model accuracy due to restrictions on training datasets

Degraded user experience resulting from reduced system performance

Increased operational inefficiency and reliance on manual processes

Q83. Which of the following should be the MOST important area of focus during the development of data security risk scenarios specific to AI?

Attack vectors enabled by techniques for malicious alteration of AI system outputs

Documentation of business unit readiness for secure adoption of AI for general operations

Development and communication of need-based access policies for the use of AI applications

Quantum encryption methods for the protection of proprietary organizational data assets

Q84. A risk practitioner is performing a risk assessment of an AI system that will be used to predict failures in aircraft components. Which of the following is the MOST important design consideration in this context?

Integration with existing maintenance systems

Capacity to handle rapid increases in sensor input

Robust safety validation mechanisms

Inclusion of maintenance history in training data

Q85. Which of the following should be the PRIMARY consideration when determining the priority for restoration of AI systems following a model exfiltration attack?

Reliance on the AI system for critical business requirements

AI-specific expertise among business continuity team members

Cost of AI system vulnerability testing and patch deployment

Availability of externally vetted datasets for AI model retraining

Q86. A risk practitioner learns that a credit-scoring AI system is exhibiting bias that cannot be eliminated through further training. Which of the following is the risk practitioner ‘ s BEST recommendation?

Apply compensating controls that generate offsetting biases in the opposite direction.

Take the system out of production to avoid harm and potential legal liability.

Source vendors for a new credit-scoring AI solution.

Request a risk acceptance from senior management.

Q87. Which of the following is the PRIMARY benefit of implementing a formal data disposition process for AI training and operational datasets?

Accelerating deployment by eliminating redundant validation and governance activities

Maximizing retention of historical records to support future retraining

Consolidating storage under a single platform with broad access and centralized management

Reducing exposure to breaches and regulatory penalties

Q88. Which of the following BEST mitigates the risk of misaligned return on investment (ROI) in AI initiatives?

Establishing a comprehensive inventory of AI systems and services

Creating separate metrics for AI-aligned workforce development

Mapping AI project outcomes to enterprise performance metrics

Prioritizing quantifiable outcomes in ROI calculations

Q89. AI tools can BEST help to mitigate supply chain risk by:

automating routine inventory management tasks.

enhancing predictive capabilities to identify potential disruptions.

identifying historical physical and logical security control gaps.

performing sentiment analysis on supplier reputation and reviews.

Q90. Which of the following is the GREATEST societal risk posed by the dissemination of deepfakes created with AI image generation technology?

Intellectual property infringement

Job loss and economic destabilization

Widespread misinformation

Disclosure of personal data

Q91. A risk practitioner assesses a new AI system and determines that the risk is within the organization ‘ s risk tolerance. Which of the following is the BEST recommendation to ensure system controls remain effective over time?

Ongoing AI security and risk awareness training

Alignment with recognized AI control frameworks

Continuous monitoring for data and performance drift

Periodic regulatory compliance reviews

Q92. An organization is selecting an AI model for a solution that requires the creation of new content. It is MOST important to consider selecting:

a generative model capable of synthesizing samples from an underlying distribution.

an unsupervised clustering model that groups observations by similarity metrics.

a rule-based expert system driven by explicit decision rules and domain knowledge.

a reinforcement learning model that optimizes sequential actions through reward signals.

Q93. Which of the following BEST helps to ensure the success of an AI risk management plan?

Standardization of risk assessment criteria across relevant use cases

Robust structures for governance and ethical oversight

Protection mechanisms for proprietary organizational information and trade secrets

Continuous validation of security controls for AI training datasets

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2026 Updated Verified AAIR Q&As – Pass Guarantee or Full Refund [Q79-Q93]

ISACA AAIR Exam Syllabus Topics:

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