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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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ISACA Advanced in AI Security Management (AAISM) Exam AAISM Prüfungsfragen mit Lösungen (Q336-Q341):

336. Frage
Which of the following BEST enables an organization to maintain visibility to its AI usage?

A. Maintaining a comprehensive inventory of AI systems and business units that leverage them
B. Measuring the impact of AI implementation using key performance indicators (KPIs)
C. Ensuring the board approves the policies and standards that define corporate AI strategy
D. Maintaining a monthly dashboard that captures all AI vendors

Antwort: A

Begründung:
The AAISM framework stresses that the most effective way to maintain oversight of organizational AI usage is by maintaining a comprehensive inventory of all AI systems and the business units using them. Such an inventory provides a centralized, transparent record of where AI is deployed, ensuring accountability, monitoring, and compliance. While board approval, dashboards, and KPIs are important governance tools, they do not provide holistic visibility across the enterprise. The inventory ensures traceability and governance alignment, making it the best method to maintain visibility of AI usage.
References:
AAISM Study Guide - AI Governance and Program Management (AI Inventories) ISACA AI Security Management - Centralized Oversight of AI Assets

337. Frage
When using AI as part of incident response, which of the following BEST ensures the automation aligns with regulatory and governance obligations?

A. Implement a tiered automation strategy where severity ratings inform the need for human oversight
B. Use deep learning models to autonomously classify all incidents
C. Train the AI incident response platform to mirror legacy response workflows and log containment
D. Apply anomaly detection models to filter incoming threats and automate containment

Antwort: A

Begründung:
AAISM prescribes risk-based, human-in-the-loop orchestration for safety-critical or regulated actions. A tiered automation strategy that gates autonomy by incident severity, data sensitivity, and regulatory requirements ensures accountability, auditability, and proportionality, satisfying governance obligations. Full autonomy (A) risks non-compliance; simply mirroring legacy workflows (B) may not meet current obligations; broad auto-containment (C) lacks necessary oversight controls.
References: AI Security Management™ (AAISM) Body of Knowledge - Governance of AI-Driven Security Automation; Human Oversight and Escalation; Risk-Based Orchestration. AAISM Study Guide - Incident Response with AI: Controls, Approvals, and Auditability.

338. Frage
To ensure AI tools do not jeopardize ethical principles, it is MOST important to validate that:

A. The organization has implemented a responsible development policy
B. Outputs of AI tools do not perpetuate adverse biases
C. AI tools are evaluated by the privacy department before implementation
D. Stakeholders have approved alignment with company values

Antwort: B

Begründung:
AAISM highlights that the core ethical risk in AI is the perpetuation of bias that results in unfair or discriminatory outcomes. Therefore, the most important validation step is ensuring that outputs of AI systems are free from adverse biases. A responsible development policy, stakeholder approvals, and privacy reviews all contribute to governance, but they do not directly ensure ethical outcomes. Validation of output fairness is the critical safeguard for ensuring AI does not violate ethical principles.

339. Frage
Which of the following technologies can be used to manage deepfake risk?

A. Adaptive authentication
B. Multi-factor authentication (MFA)
C. Systematic data tagging
D. Blockchain

Antwort: D

Begründung:
The AAISM study material highlights blockchain as a control mechanism for managing deepfake risk because it provides immutable verification of digital media provenance. By anchoring original data signatures on a blockchain, organizations can verify authenticity and detect tampered or synthetic content. Data tagging helps organize but does not guarantee authenticity. MFA and adaptive authentication strengthen identity security but do not address content manipulation risks.
Blockchain's immutability and traceability make it the recognized technology for mitigating deepfake challenges.

340. Frage
An organization is adopting multiple AI solutions for customer support and management is concerned about potential privacy and confidentiality violations due to the implementation of the new solution. Which of the following is the BEST risk mitigation strategy in this situation?

A. Use consumer-level AI guidelines with rules, terms, and recommendations for end users.
B. Rely on best practice manuals from AI vendors to guide how employees use the systems.
C. Implement key risk indicators (KRIs) to monitor AI usage and update the risk register.
D. Create responsible AI use policies that address ethics, acceptable use, and transparency.

Antwort: D

Begründung:
Establishing responsible AI use policies defines clear expectations for handling data, ethical use, and transparency, directly addressing privacy and confidentiality risks across multiple AI solutions and guiding consistent behavior organization-wide.

341. Frage
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