ESG.AI has launched a publicly accessible AI Impact Calculator that allows users to measure and compare the environmental footprint of widely used artificial intelligence models. The tool estimates electricity consumption, water use, and greenhouse gas emissions linked to AI activity, marking one of the first efforts to translate AI usage into concrete environmental metrics that can be compared across models and regions.

The announcement comes as policymakers, investors, and technology leaders convene in Davos amid intensifying debate around climate risk, digital infrastructure, and the growing resource demands of data centres. While recent scrutiny has highlighted the strain generative AI places on power grids and water systems, ESG.AI argues that decision-makers have lacked practical tools to quantify and compare those impacts in a consistent way.

Turning AI From an Abstract Concept Into Measurable Impact

The AI Impact Calculator is designed to bridge that gap. Users can input how they interact with AI, whether measured in pages generated, tokens processed, or other industry benchmarks, and specify where that activity occurs. Based on location and usage intensity, the tool estimates electricity demand, water consumption, emissions over time horizons ranging from a month to a year, and the associated operating costs.

According to ESG.AI, the aim is to move conversations about AI sustainability away from generalised concern toward data-informed choices. Kelly Kirsch, European Director at the company, described AI as physical infrastructure with real-world consequences rather than an abstract digital service, noting that the calculator helps make those consequences visible and comparable.

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Supporting Disclosure and Accountability

The company says the calculator is already being used by organisations subject to public-market disclosure requirements, particularly those needing to assess and report the environmental and financial impacts of AI-driven operations. As regulatory scrutiny around technology-related emissions grows, tools that link digital activity to measurable environmental outcomes are increasingly relevant for compliance, risk management, and investor communication.

ESG.AI also works in partnership with the London Stock Exchange Group to improve transparency around the environmental footprint of AI across listed companies. This collaboration reflects a broader push within capital markets to better understand how emerging technologies affect emissions profiles and operational sustainability.

AI Sustainability as a Policy and Investment Issue

Beyond benchmarking, ESG.AI positions the calculator as a catalyst for broader accountability. The company hopes it will be used not only by sustainability teams and procurement leaders, but also by regulators, developers, and journalists examining the systemic impacts of large-scale AI deployment.

Nicholas Miller, Founder and Chief Executive Officer of ESG.AI, framed the tool as part of a shift in how AI is evaluated, arguing that its environmental footprint is as much a policy and investment concern as it is a technical one. Measuring AI impacts, he said, is a necessary step toward aligning rapid adoption with climate and sustainability goals.

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Expanding the Scope of ESG Intelligence

ESG.AI operates as an AI-powered ESG intelligence platform, helping organisations visualise, analyse, and optimise environmental, social, and governance data in real time. Its technology combines large ESG datasets with machine learning to support reporting, scenario analysis, and performance improvement across sustainability metrics. By extending this capability to AI itself, the company is positioning environmental transparency as a core requirement of the digital economy.

As AI adoption accelerates across sectors, tools like the AI Impact Calculator suggest a shift toward greater scrutiny of the hidden environmental costs embedded in digital services. Whether such transparency will influence procurement decisions, regulatory standards, or model design remains an open question, but the launch signals growing momentum behind the idea that AI usage should be measured not only by performance and cost, but also by its environmental footprint.

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