ISACA AAISM Exam Preparation Guide and PDF Download [Q187-Q206]

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ISACA AAISM Exam Preparation Guide and PDF Download

Verified & Correct AAISM Practice Test Reliable Source Aug 30, 2026 Updated

ISACA AAISM Exam Overview:

Certification Vendor:	ISACA
Exam Name:	ISACA Advanced in AI Security Management (AAISM) Exam
Exam Number:	AAISM
Certificate Validity Period:	3 years
Exam Price:	USD $399
Exam Format:	Multiple Choice, Scenario-based Questions
Real Exam Qty:	90
Passing Score:	450/800
Exam Duration:	150 minutes
Related Certifications:	ISACA Advanced in AI Security Management (AAISM)
Available Languages:	English, Spanish
Sample Questions:	ISACA AAISM Sample Questions
Exam Way:	Online remote proctored exam or test center exam
Pre Condition:	Candidates must hold an active CISM or CISSP certification.
Official Syllabus URL:	https://www.isaca.org/credentialing/aaism/aaism-exam-content-outline

NO.187 Which of the following is the GREATEST threat to an organization where shadow generative AI is prevalent?

Accidental leakage of proprietary data

Software licensing violations

Employee misuse of the AI system

Limited technical knowledge of AI operations

NO.188 A retailer’s AI-driven dynamic pricing system failed after its feature store was corrupted, resulting in all prices being set to zero. The data source has been isolated, and management demands immediate recovery. Which of the following is the MOST appropriate course of action to restore operations while minimizing impact?

Failover to a secondary environment and retrain the model with recent data.

Revert to the previous AI model and validate backup of the feature store.

Keep the system offline and conduct a full forensic investigation.

Require customer service to manually price and approve orders until the AI system is fully restored.

NO.189 An organization needs large data sets to perform application testing. Which of the following would BEST fulfill this need?

Reviewing AI model cards

Incorporating data from search content

Using open-source data repositories

Performing AI data augmentation

NO.190 Which of the following is the BEST reason to involve a diverse team when evaluating the data used within an AI system?

It reduces the likelihood of a risk being overlooked.

It ensures that scenarios are reviewed thoroughly.

It reduces the perception of bias by the media and users.

It ensures the output is representative of target end users.

NO.191 Which of the following is the BEST way to ensure role clarity and staff effectiveness when implementing AI- assisted security monitoring tools?

Defer implementation until the security team can be expanded with data scientists.

Update the security program to include cross-functional AI-specific responsibilities.

Transition responsibilities for AI tools to external consultants for improved scalability.

Increase training budgets for business staff to obtain vendor-neutral AI certifications.

NO.192 Which of the following assessments MOST effectively addresses concerns related to ethical and trustworthy AI use?

Fundamental rights impact assessment

Information security risk assessment

Business impact analysis (BIA)

Privacy impact assessment (PIA)

NO.193 Which of the following would be of GREATEST concern to an information security manager when a small, startup organization is proposing the use of a pre-trained open-source AI solution?

The organization has limited visibility to how data is being used.

There may be a lack of support if the project is abandoned.

The model is not compatible with enterprise architecture (EA).

The open-source model includes a hidden backdoor.

NO.194 Which of the following poses the GREATEST challenge to the comprehensive testing of AI systems?

Demands for extensive user intervention during testing

Need for rigorous test planning and preparation

Difficulty obtaining adequate and validated test data

Lack of automated testing scripts and tools

NO.195 Which of the following BEST reduces the risk of exposing sensitive data through the output of large language models (LLMs) in applications?

Encrypting data in transit and at rest

Conducting adversarial testing

Implementing data sanitization techniques

Enforcing least privilege access

NO.196 Which of the following would BEST ensure a proper business continuity plan (BCP) is in place for an AI solution?

Enhancing monitoring and detection of model failures and anomalies

Implementing access controls to protect the AI system from unauthorized use

Testing the AI infrastructure failover mechanisms

Increasing the detail of AI solution backup and restoration processes

NO.197 Which of the following types of data is used to tune hyperparameters?

Validation

Configuration

Training

Test

NO.198 Which of the following is the MOST effective action an organization can take to address data security risk when using generative AI features in an application?

Establish policies and awareness training for acceptable use of AI

Require opt-out provisions for data usage in service agreements

Rely on the AI provider’s independent third-party audit reports for assurance

Establish guidelines and best practices with third parties for intellectual property ownership

NO.199 The MOST important consideration when establishing key risk indicators (KRIs) to monitor AI model drift in an operational machine learning (ML) system is adopting KRIs that:

measure utilization rates and trends for AI computational resources.

identify variations in model accuracy and outputs.

monitor latency and AI infrastructure uptime.

track user satisfaction levels with AI-generated outputs.

NO.200 When implementing a generative AI system, which of the following approaches will BEST prevent misalignment between the corporate risk appetite and tolerance?

Ensuring effective AI key performance indicators (KPIs)

Performing an AI impact assessment

Creating and maintaining an AI risk register

Establishing and monitoring acceptable levels of AI system risk

NO.201 A financial organization uses AI to detect potential fraudulent activities but is concerned about the impact of potential data poisoning. Which of the following controls would BEST mitigate this risk?

Being transparent with customers about the data sources

Implementing an updated and tested break-glass policy

Delivering AI-specific security awareness training

Using training data from multiple sources

NO.202 Which of the following is the GREATEST risk for an organization that has adopted AI-powered chatbots for its customer service platform?

Model distillation

Prompt injection

Model inversion

Data poisoning

NO.203 An organization is reviewing an AI application to determine whether it is still needed. Engineers have been asked to analyze the number of incorrect predictions against the total number of predictions made. Which of the following is this an example of?

Control self-assessment (CSA)

Model validation

Key performance indicator (KPI)

Explainable decision-making

NO.204 A viral video shows a blurry person making claims about a product safety issue. The video has random low- quality sections. This MOST likely represents what threat?

Hallucinations

Model drift

Data poisoning

Deepfake

NO.205 Which of the following is the MOST serious consequence of an AI system correctly guessing the personal information of individuals and drawing conclusions based on that information?

The exposure of personal information may result in litigation

The publicly available output of the model may include false or defamatory statements about individuals

The output may reveal information about individuals or groups without their knowledge

The exposure of personal information may lead to a decline in public trust

NO.206 When using third-party pre-trained AI models for customer due diligence in a highly regulated financial industry, which of the following is the PRIMARY security concern?

Lower energy efficiency leading to higher operational costs

Excessive model size requiring additional computing resources

Presence of unvalidated dependencies and typosquatting

Inability to deploy model fully on-premises and vendor lock-in

ISACA AAISM Exam Syllabus Topics:

Topic	Details
Topic 1	AI Governance and Program Management: This section of the exam measures the abilities of AI Security Governance Professionals and focuses on advising stakeholders in implementing AI security through governance frameworks, policy creation, data lifecycle management, program development, and incident response protocols.
Topic 2	AI Risk Management: This section of the exam measures the skills of AI Risk Managers and covers assessing enterprise threats, vulnerabilities, and supply chain risk associated with AI adoption, including risk treatment plans and vendor oversight.
Topic 3	AI Technologies and Controls: This section of the exam measures the expertise of AI Security Architects and assesses knowledge in designing secure AI architecture and controls. It addresses privacy, ethical, and trust concerns, data management controls, monitoring mechanisms, and security control implementation tailored to AI systems.

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ISACA AAISM Exam Overview:

ISACA AAISM Exam Syllabus Topics:

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