Security practitioners are proactively developing incident response playbooks for AI data breaches, recognizing that third-party AI vendors now represent a significant and underexamined attack surface. When an organization integrates external AI data pipelines, training datasets, or model-serving infrastructure, sensitive data, including customer records, proprietary prompts, and model weights, moves beyond traditional perimeter controls and into vendor environments with inconsistent security postures. This trend signals that AI supply chain risk is maturing from theoretical concern to operational planning priority, and boards should expect security teams to demand the same third-party assurance requirements for AI vendors that they apply to cloud and SaaS providers.