Within the ISACA Advanced in AI Risk framework, governance decisions should align AI use with policy, accountability, stakeholder expectations, risk appetite, and applicable legal or ethical obligations. AI-enabled re-identification is a direct privacy risk because models can combine attributes that appear harmless in isolation and infer an individual identity. This can defeat ordinary masking or pseudonymization and create regulatory exposure even when direct identifiers are absent. This makes option C, AI models may be able to identify combinations of attributes that can be used to re-identify individuals, the strongest answer. The other choices describe narrower technical, operational, performance, or administrative considerations and do not address the primary risk-management objective in the scenario as directly. A risk practitioner should select the response that most effectively reduces the stated exposure while preserving appropriate oversight, traceability, and alignment with organizational risk tolerance and business requirements.