A. Invoke the contract's termination-for-convenience clause and begin immediate vendor transition planning ( As clauses for acquiring by foreign company having conflicting regulatory domain in the prevoius contract not mentioned for approprite action, unlateral direct contract termination is not conforming to corporate governance). B. Conduct a risk assessment to evaluate the change in data sovereignty exposure and regulatory compliance impact ( the said course of action is more aligning with security governance with buisness objectives). C. Require the vendor to migrate all customer data to data centers located within approved jurisdictions ( its apprprite steo but later step after 'B' ) D. Notify the Data Protection Authority and affected customers of the potential cross-border data transfer (the action is meant for data breach notofication and not be acceptable under GDPR by DPA / customers).

A. Engage legal counsel to review the AI vendor's training data sources and contractual indemnification clauses ( As the matter is of legal nature licese violations - regulatory issue, " Call tha Attorney" for opinion and transfer the risk through indemnity clauses- Governance decision). B. Implement software composition analysis (SCA) and require all AI-generated code to be digitally signed before commit ( it will mitigate risk of known vunalabities and increase integrity of code but will not solve the root cause- operational action). C. Restrict the AI tool's access to internal repositories and enforce output review through secure-coding peer validation ( restiction will effect feature delivery though out review --- is best coding practice). D. Retrain or fine-tune the AI model using only vetted, license-compliant code from approved sources ( it will under mine use of open source repostires for efficient good generation capability of AI model).

A. Reclassify the AI-generated outputs under the highest data sensitivity level ( As the input data source is shared model centrally manged, AI generated out put has no clear classification ). B. Clarify and formally assign data ownership and stewardship for AI-derived assets (as per Governance, ownership of AI derived assets comes first for further classification according to sensitivity level is priority action ). C. Segregate AI workloads by business unit to prevent cross-correlation ( effect business performance and not aligning governance/security with business objectives). D. Implement stronger access controls on the shared data lake ( it will prevent unauthorised access to data lakes ( source data) that is irrelevant measure for AI generated output dispute).

A. Require human review of all AI-generated workforce decisions ( Good decsion following recommendations AI governanace that AI under human oversight). B. Document the risk acceptance and ethical considerations in governance records ( As security leader, its applicable for other risk acceptences except ethical concerns where ISC2 canons put some bindings). C. Suspend the AI system until explainability requirements are met ( its not secuirty aligned with busienss as excutive governace desicion cannnot be reversed abruptly). D. Conduct a privacy impact assessment focused on employee data ( lays off not directly rlevent to privacy impact assessment).

A. Symmetric encryption using AES-256 with a managed Key Vault ( best for data at rest / disk ). B. Asymmetric encryption using RSA-4096 with Perfect Forward Secrecy ( best for data in transit and protection from replay attack). C. Homomorphic encryption ( best for data in use / prcessing ). D. Quantum-resistant cryptography ( generic term best for future alogorithms secure form quantum computing cpability to solve complex mathematical problem basis for asymmetric cryptography).