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ISACA AAISM Exam Syllabus Topics:

TopicDetails
Topic 1
  • 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 2
  • 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.
Topic 3
  • 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.

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ISACA Advanced in AI Security Management (AAISM) Exam Sample Questions (Q225-Q230):

NEW QUESTION # 225
An information security manager is tasked with preparing management reports regarding the risk mitigation controls applied to the organization's customer service chatbot. Which of the following is MOST critical to include in these reports?

Answer: A

Explanation:
Management reports should provide actionable recommendations that help decision-makers improve the effectiveness of risk mitigation controls. This information is critical for ongoing governance, risk reduction, and informed management oversight of the chatbot environment.


NEW QUESTION # 226
Which area of intellectual property law presents the GREATEST challenge in determining copyright protection for AI-generated content?

Answer: B

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.


NEW QUESTION # 227
Which of the following is the MOST effective control to prevent malicious modification of AI chatbot outputs?

Answer: B

Explanation:
A governance AI model trained on known attack patterns can dynamically detect and block malicious attempts to manipulate chatbot outputs, including prompt injection and adversarial input techniques. This provides adaptive, real-time protection that is more effective than static filtering or user training alone.


NEW QUESTION # 228
Which of the following is the BEST method to uncover known vulnerabilities in an AI-based web application that has been recently deployed?

Answer: C


NEW QUESTION # 229
A financial services firm received a regulatory fine after a vendor switched its chatbot's AI model without due diligence, resulting in unethical investment advice to the firm's clients. Which of the following controls should be implemented by the firm to BEST prevent recurrence of this scenario?

Answer: D

Explanation:
AAISM requires formal change management for AI systems, including vendor-initiated changes: pre- approval, documented impact assessment (ethics/compliance/performance), regression testing, sign-off by accountable owners, and traceable release records. While MSAs (A) and shared responsibility models (B) set contractual/role baselines, they do not enforce per-change approvals. Data minimization (C) reduces exposure but does not control model substitutions.
References: AI Security Management (AAISM) Body of Knowledge - AI Governance: Change Control & Release Management; Third-Party AI Assurance and Approval Workflows; Accountability and Sign-off for Model Changes.


NEW QUESTION # 230
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