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| Section | Weight | Objectives |
|---|---|---|
| AI Governance and Program Management | 31% | - AI security program management
|
| AI Risk Management | 31% | - Third-party and supply chain risk management
|
| AI Technologies and Controls | 38% | - AI security monitoring and operations
|
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NEW QUESTION # 176
An organization deploys a large language model (LLM) to automate legal document analysis.
Which of the following is MOST critical before model deployment?
Answer: D
Explanation:
Before deployment, it is most critical to validate that the model produces accurate, reliable, and expected outputs for legal document analysis. Testing model behavior helps identify errors, inconsistencies, hallucinations, or unsafe outcomes that could create significant legal and operational risks.
NEW QUESTION # 177
An audit reveals that a third-party AI vendor of a financial organization does not provide documentation on model training and testing. Which of the following is the MOST critical risk for the organization?
Answer: B
Explanation:
Without documentation on how the model was trained and tested, the organization cannot demonstrate transparency, explainability, or proper validation. This creates significant regulatory compliance risk, especially in financial services where decisions must be explainable and auditable.
NEW QUESTION # 178
An organization is implementing a large language model (LLM) to answer questions for both employees and customers. The CIO wants the LLM to provide employees with additional internal data that should not be shared with customers. Which of the following is the MOST secure approach?
Answer: B
Explanation:
Retrieval-augmented generation (RAG) combined with access control lists (ACLs) ensures that the LLM retrieves and exposes only the data each user is authorized to access. This approach provides granular, role-based protection of internal information while supporting different data visibility requirements for employees and customers.
NEW QUESTION # 179
An aerospace manufacturer prioritizing accuracy and security wants to use generative AI. Which LLM adoption plan BEST aligns with its risk appetite?
Answer: C
Explanation:
AAISM notes that high-security industries (e.g., aerospace) should prefer private, controlled environments with restricted data exposure. Developing a private LLM for non-critical workloads minimizes operational and security risk while enabling innovation.
Public LLMs for critical functions (C) violate safety expectations. Purchased datasets (D) introduce unknown provenance. Outsourcing (B) increases third-party risk.
References: AAISM Study Guide - AI Governance; Safe LLM Adoption Strategies.
NEW QUESTION # 180
Which of the following is the GREATEST concern when a vendor enables generative AI features for an organization's critical system?
Answer: B
Explanation:
When enabling genAI capabilities in a critical system, AAISM prioritizes controlling access to the model and its interfaces (prompt surfaces, context windows, tools/functions, and connected data) because exposure expands the attack surface for prompt injection, data exfiltration, jailbreaks, and misuse. Monitoring (C) is necessary but detective; ethics and bias (D) are vital but secondary to immediate safety and security of a mission-critical environment; proposed regulations (B) are not an immediate operational risk.
References: AAISM Body of Knowledge: GenAI Security-Access Governance, Interface Hardening, and Prompt Surface Controls; AAISM Study Guide: Critical System Safeguards-Least Privilege, Guardrails, and Abuse Prevention.
NEW QUESTION # 181
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2026 Latest ValidTorrent AAISM PDF Dumps and AAISM Exam Engine Free Share: https://drive.google.com/open?id=1Rz0giCFvRpH_9ZV0bF-zP6bA1Z-tcjyb