An organization in a regulated sector has adopted AI across multiple functions, with each team adhering to approved internal procedures for model development and deployment. During an external review, reviewers observe that required activities-such as approvals, validations, updates, and reviews-have taken place at different times. However, they struggle to establish how these activities relate to one another throughout the full lifespan of each AI system. Determining how earlier decisions affected later outcomes requires manual work, cross-team coordination, and interpretation of disconnected records.
Which governance challenge best explains the organization's difficulty demonstrating dependable, end-to-end oversight of its AI systems during formal reviews?

• A. Fragmented execution of lifecycle governance activities
• B. Limited enforcement of ethical design principles
• C. Inconsistent assignment of governance ownership
• D. Insufficient monitoring of deployed model behavior

An organization maintains centralized repositories that hold AI source code, trained models, and datasets. Its security goals include preventing unauthorized changes, ensuring accountability for modifications, and allowing prompt detection of suspicious activity during development and deployment.
Which repository-security control most directly provides both restricted access and traceable oversight of AI assets?

• A. Automated security checks in CI/CD pipelines
• B. Encryption of models and datasets at rest
• C. Mandatory static source code reviews
• D. Role-based access control with audit logs

An organization is investigating recurring operational issues in an AI-based decision system. Each incident seems resolved following standard remediation actions, but similar failures recur under new data conditions.
Post-incident reviews reveal no persistent infrastructure faults or configuration errors.
Which traditional incident-response assumption most constrains its effectiveness in this scenario?

• A. Incident resolution depends on predefined response playbooks
• B. Root causes remain stable once remediation is applied
• C. Incident scope can be clearly bounded at the system level
• D. Incidents can be resolved through discrete corrective actions

Dr. Aris, Head of AI Research, is conducting an internal governance review to formally classify a legacy chess-playing system developed in the 1990s as part of an enterprise AI inventory. The system determines moves solely by evaluating the current board state through predefined logic and exhaustive-search strategies.
It does not preserve information from earlier matches, adapt its strategy over time, or change its decision process using historical gameplay data. Dr. Aris must assign a category that accurately represents the system's lack of learning, absence of memory, and entirely state-based decision behavior.
Which classification represents this system from a technical and conceptual perspective?

• A. Self-Aware AI
• B. Reactive Machines
• C. Limited Memory AI
• D. Theory of Mind AI