AAISM Visual Cert Exam - AAISM Valid Exam Materials
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Do you want to earn the ISACA AAISM certification to land a well-paying job or a promotion? Prepare with AAISM real exam questions to crack the test on the first try. We offer our ISACA Advanced in AI Security Management (AAISM) Exam (AAISM) Dumps in the form of a real AAISM Questions PDF file, a web-based ISACA AAISM Practice Questions, and AAISM desktop practice test software. Now you can clear the ISACA Advanced in AI Security Management (AAISM) Exam test in a short time without wasting time and money with actual AAISM questions of PrepAwayETE.
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ISACA AAISM Exam | AAISM Visual Cert Exam - Bringing Candidates Good AAISM Valid Exam Materials
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ISACA Advanced in AI Security Management (AAISM) Exam Sample Questions (Q88-Q93):
NEW QUESTION # 88
Which area of intellectual property law presents the GREATEST challenge in determining copyright protection for AI-generated content?
- A. Enforcing trademark rights associated with AI systems
- B. Protecting trade secrets in AI technologies
- C. Establishing licensing frameworks for AI-generated works
- D. Determining the rightful ownership of AI-generated creations
Answer: D
Explanation:
AAISM governance content highlights that the greatest intellectual property challenge in the context of AI- generated works is determining rightful ownership. Traditional copyright law requires human authorship, but AI-generated creations blur authorship and ownership boundaries, raising legal uncertainty about who can claim rights. Trademark enforcement, trade secret protection, and licensing frameworks are established areas of IP law but do not present the same fundamental challenge as ownership attribution. For AI-generated content, the central legal dilemma is ownership of the creation.
References:
AAISM Study Guide - AI Governance and Program Management (Intellectual Property and AI) ISACA AI Security Management - Copyright and Ownership Challenges
NEW QUESTION # 89
A vendor switched its chatbot's AI model without due diligence, causing unethical investment advice. What control BEST prevents this scenario?
- A. Shared responsibility model
- B. Change management
- C. Data minimization
- D. Master services agreement
Answer: B
Explanation:
AAISM stresses AI-specific change management as essential for vendor-driven or system-driven updates.
Proper change control includes:
* impact assessments
* ethical review
* risk evaluation
* approval checkpoints
* rollback plans
An MSA (A) supports contracts but does not manage operational change. Shared responsibility (C) describes roles, not change control. Data minimization (D) reduces exposure but doesn't control model updates.
References: AAISM Study Guide - AI Change Management; Vendor Model Update Controls.
NEW QUESTION # 90
What BEST ensures a proper business continuity plan (BCP) for an AI solution?
- A. Testing AI infrastructure failover mechanisms
- B. Increasing backup restoration detail
- C. Implementing access controls
- D. Enhancing monitoring for model failure
Answer: A
Explanation:
AAISM defines an AI BCP as requiring validated failover and recovery testing of AI components, including:
* model hosting environments
* model-serving APIs
* feature stores
* inference pipelines
Only Option B tests actual continuity of AI functionality.
Monitoring (A) detects issues but does not ensure continuity. Access controls (C) relate to security, not continuity. Backup detail (D) is insufficient without recovery testing.
References: AAISM Study Guide - AI Resilience and Disaster Recovery Validation.
NEW QUESTION # 91
Which of the following strategies BEST ensures generative AI tools do not expose company data?
- A. Testing AI tools before implementation
- B. Conducting an independent AI data audit
- C. Implementing a solution to prohibit the input of sensitive data
- D. Ensuring AI tools are compliant with local regulations
Answer: C
Explanation:
AAISM prioritizes preventive controls at the point of use for generative AI, specifically input-governance and DLP controls that block or redact confidential, regulated, or high-risk data before it can be sent to external models. Audits, pre-deployment tests, and regulatory conformance are necessary but do not themselves prevent an employee from pasting sensitive content into prompts. Enforcing input restrictions, pattern-based redaction, policy-aware controls, and allow-lists for approved contexts provides the highest assurance of preventing exposure.
References:* AI Security Management™ (AAISM) Body of Knowledge: Data loss prevention for AI; prompt
/input controls; approved channels and guardrails for generative AI.* AI Security Management™ Study Guide: Preventive over detective controls for confidentiality; enterprise guardrails at prompt capture and egress points.
NEW QUESTION # 92
Which of the following is the GREATEST risk inherent to implementing generative AI?
- A. Inadequate return on investment (ROI)
- B. Potential intellectual property violations
- C. Lack of employee training
- D. Unidentified asset vulnerabilities
Answer: B
Explanation:
The AAISM framework identifies intellectual property (IP) violations as the most significant inherent risk in deploying generative AI. These systems often rely on large-scale internet data for training, which may inadvertently contain copyrighted or proprietary material. This creates legal and reputational exposure when outputs reproduce or reference protected content. While employee training gaps, asset vulnerabilities, and ROI concerns are relevant risks, they are not inherent to generative models themselves. The greatest inherent risk tied directly to generative AI adoption is the possibility of violating intellectual property rights.
References:
AAISM Study Guide - AI Risk Management (Generative AI Risks and Legal Exposure) ISACA AI Security Management - Copyright and IP Concerns in Generative AI
NEW QUESTION # 93
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