The rapid adoption of Generative AI (GenAI) in the software development life cycle (SDLC) increases computational demand, which can raise the carbon footprint of development activities. At the same time, organizations are increasingly embedding governance mechanisms into GenAI-assisted development to support trust, transparency, and accountability. However, these governance mechanisms introduce additional computational workloads, including repeated inference, regeneration cycles, and expanded validation pipelines, increasing energy use and the carbon footprint of GenAI-assisted development. This paper proposes Carbon-Aware Governance Gates (CAGG), an architectural extension that embeds carbon budgets, energy provenance, and sustainability-aware validation orchestration into human-AI governance layers. CAGG comprises three components: (i) an Energy and Carbon Provenance Ledger, (ii) a Carbon Budget Manager, and (iii) a Green Validation Orchestrator, operationalized through governance policies and reusable design patterns.

翻译：生成式人工智能在软件开发生命周期中的快速应用增加了计算需求，这可能提升开发活动的碳足迹。与此同时，组织正越来越多地将治理机制嵌入生成式人工智能辅助开发中，以支持信任、透明度和问责制。然而，这些治理机制引入了额外的计算工作负载，包括重复推理、再生周期和扩展的验证流水线，从而增加了生成式人工智能辅助开发的能源使用和碳足迹。本文提出碳感知治理门控，这是一种将碳预算、能源溯源和可持续性感知的验证编排嵌入人机治理层的架构扩展。碳感知治理门控包含三个组件：（i）能源与碳溯源账本，（ii）碳预算管理器，以及（iii）绿色验证编排器，通过治理策略和可复用设计模式实现操作化。