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ISACA AAISM Prüfungsplan:

Thema	Einzelheiten
Thema 1	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.
Thema 2	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.
Thema 3	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.

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Die ISACA AAISM Zertifizierungsprüfung ist der erste Schritt zum Berufserfolg fur IT-Fachleute. Durch die ISACA AAISM Zertifizierungsprüfung haben Sie schon den ersten Fuß auf die Spitze Ihrer Karriere gesetzt. ZertSoft wird Ihnen helfen, die ISACA AAISM Zertifizierungsprüfung zu bestehen.

ISACA Advanced in AI Security Management (AAISM) Exam AAISM Prüfungsfragen mit Lösungen (Q33-Q38):

33. Frage
Which of the following BEST describes the role of transparency in AI?

A. Publishing AI mechanisms, data sources, and decision-making processes while making them openly available
B. Talking through a decision tree to better understand how the algorithm made each of its choices
C. Explaining the AI system in an understandable and logical way so reasons for decisions can be given
D. Persuading someone that the AI tool in use is beneficial and operates as expected

Antwort: C

Begründung:
Transparency in AI is a governance principle requiring that systems be explainable to stakeholders in ways that are understandable and meaningful, enabling clear articulation of how decisions were reached and why.
Within an AI program, transparency supports accountability, auditability, and trust by ensuring that reasons for decisions can be communicated and scrutinized. Option C reflects this definition by focusing on intelligible, logical explanations of system behavior and decision rationale.
Option A is a narrow technique (model-specific interpretability for decision trees) and does not capture transparency as a broad governance requirement. Option B conflates transparency with full public disclosure; transparency does not require making all artifacts openly available. Option D is persuasion/advocacy, not transparency.
References: AI Security Management (AAISM) Body of Knowledge: "AI Governance-Transparency and Explainability," "Accountability and Assurance"; AAISM Study Guide: "Explainability Objectives and Stakeholder Communication," "Documentation for Decision Rationale."

34. Frage
Which of the following is the BEST way to ensure role clarity and staff effectiveness when implementing AI- assisted security monitoring tools?

A. Update the security program to include cross-functional AI-specific responsibilities.
B. Defer implementation until the security team can be expanded with data scientists.
C. Transition responsibilities for AI tools to external consultants for improved scalability.
D. Increase training budgets for business staff to obtain vendor-neutral AI certifications.

Antwort: A

Begründung:
AAISM directs that AI adoption in security operations be governed through explicit operating models and RACI-mapped responsibilities spanning security operations, data science/ML, platform engineering, privacy, and compliance. Role clarity comes from updating the security program to codify AI-specific responsibilities (model monitoring, incident handling for AI failures, data governance, change control for models, bias
/fairness reviews, supplier assurance) rather than deferring implementation, outsourcing core accountability, or relying on generic certifications. This ensures measurable accountability, reduces hand-off risk, and aligns day-to-day SOC practices with AI control objectives.
References:* AI Security Management™ (AAISM) Body of Knowledge: AI Governance Operating Model; Roles & Responsibilities; RACI for AI-enabled Security Operations* AAISM Study Guide: Program Governance, Control Objective Mapping to SOC Workflows; Cross-Functional Ownership for AI Controls

35. Frage
The PRIMARY AI governance risk of inconsistently applying data augmentation and cleansing across datasets is that the model may:

A. violate license terms of external preprocessing libraries.
B. face scalability and accuracy challenges in production.
C. require additional computational resources.
D. have biases that undermine data and model integrity.

Antwort: D

Begründung:
Inconsistent data augmentation and cleansing can introduce or amplify bias within datasets, resulting in unreliable or unfair model behavior. This undermines both data integrity and model integrity, creating significant governance, ethical, and operational risks.

36. Frage
Which strategy is MOST effective for penetration testers assessing an AI model against membership inference attacks?

A. Generating synthetic training data
B. Analyzing AI model confidence scores
C. Disabling model logging
D. Measuring accuracy on the test set

Antwort: B

Begründung:
AAISM specifies that membership inference attacks often exploit unusually high confidence scores when the model encounters data points used during training. Penetration testers identify vulnerability by analyzing model confidence behavior across known and unknown samples.

37. Frage
Which BEST describes the role of model cards in AI solutions?

A. They help developers create synthetic data
B. They document training data and AI model use cases
C. They visualize AI model performance
D. They automatically fine-tune AI models

Antwort: B

Begründung:
AAISM explains that model cards provide structured documentation about AI models, including:
- intended use cases
- training data characteristics
- ethical considerations
- known limitations
- risk factors
- performance benchmarks

38. Frage
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P.S. Kostenlose 2026 ISACA AAISM Prüfungsfragen sind auf Google Drive freigegeben von ZertSoft verfügbar: https://drive.google.com/open?id=1rFy-NBsneefbPowMMY-MPtPLejmHUzIa