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（GenAI）在软件开发生命周期（SDLC）中的快速普及增加了计算需求，这可能导致开发活动碳足迹的上升。与此同时，各类组织正逐步将治理机制嵌入GenAI辅助开发过程，以支持信任、透明度和可问责性。然而，这些治理机制引入了额外的计算负载，包括重复推理、再生成周期以及扩大的验证管道，从而增加了GenAI辅助开发的能耗与碳足迹。本文提出碳感知治理门控（CAGG），这是一种架构扩展，它将碳预算、能源溯源及可持续性感知验证编排嵌入人机治理层。CAGG包含三个组件：（i）能源与碳足迹溯源账本、（ii）碳预算管理器，以及（iii）绿色验证编排器，并通过治理策略与可复用设计模式实现其功能。