As deepfake technologies become increasingly embedded in media, marketing, and digital security infrastructures, their integration into continuous delivery (CI/CD) environments introduces new layers of complexity for governance. While generative AI offers productivity and personalization advantages, it also elevates risks related to misinformation, impersonation, and the unauthorized use of personal data. In high-speed DevOps workflows, where automated content deployment occurs with minimal human oversight, the threat of deploying unverified or malicious synthetic media is significant. This paper investigates the legal, ethical, and technical challenges of using deepfake AI within CI/CD pipelines and proposes a multi-layered governance framework to mitigate these risks. Drawing on a synthesis of existing regulatory models, technical innovations in deepfake detection, and ethical design principles, the paper outlines a framework with three interdependent layers: legal and regulatory compliance, embedded technical guardrails for traceability, and operational enforcement at the workflow level. The framework is designed to be scalable, jurisdiction-aware, and compatible with real-time deployment systems. Through critical discussion, the paper explores tensions between automation and accountability, the limitations of current laws, and the need for interdisciplinary collaboration. It concludes by recommending concrete steps for organizations, regulators, and technologists to ensure the safe deployment of synthetic media without undermining trust, privacy, or legal integrity.