Abstract

As Artificial Intelligence (AI) becomes the invisible engine behind modern economies, its environmental footprint remains disturbingly opaque. While conversations around AI ethics have largely centered on data privacy, algorithmic bias, and transparency, an equally urgent question looms large but largely unaddressed: what is the carbon cost of intelligence at scale? Behind every large language model, image generator, and recommendation algorithm lies an energy-intensive architecture of data centers and high-performance computing systems, producing vast amounts of carbon emissions—often without public disclosure, legal scrutiny, or environmental accountability. This research paper investigates the critical gap in corporate environmental accountability frameworks with respect to AI-specific carbon emissions. While environmental disclosure norms exist across sectors under sustainability reporting obligations, these largely overlook the unique, digital carbon footprint of AI technologies. In the absence of AI-targeted emission tracking protocols, companies can report aggregate emissions while concealing the carbon costs of specific AI models. This creates a troubling accountability vacuum, allowing major technology corporations to sidestep scrutiny and greenwash their AI-driven innovations. Through a comparative legal analysis, this study evaluates existing environmental disclosure regimes—such as the European Union’s Corporate Sustainability Reporting Directive (CSRD), the United States’ SEC Climate Risk Disclosure Rules, and India’s Business Responsibility and Sustainability Reporting (BRSR) framework—to assess how (and if) they can be extended or adapted to mandate transparent AI emissions disclosure. The paper argues for the creation of binding legal instruments that demand granular, model-level carbon reporting, supported by independent third-party verification mechanisms. Furthermore, the research identifies the need for cross-border harmonization of standards, particularly in the face of transnational AI deployment, and proposes a global Digital Environmental Accountability Protocol (DEAP) to regulate AI emissions uniformly across jurisdictions. This paper contributes to the evolving discourse on environmental governance, techno-legal regulation, and climate justice, emphasizing that corporate transparency in AI emissions is not just a regulatory necessity but a moral imperative in the age of accelerating climate change. Only by weaving AI into the fabric of environmental law can we ensure that the future of intelligence is sustainable, ethical, and accountable.

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