Members & Supporters
of the Coalition for Sustainable AI

AMD

AMPECO leverages AI to enhance energy efficiency in electric vehicle (EV) charging by implementing smart charging algorithms and dynamic load management. These AI-driven features optimize charging patterns, reduce grid strain, and facilitate the integration of renewable energy sources, contributing to a more sustainable and efficient EV charging infrastructure.

Arm

We’ve set internal AI guidelines, including a benchmark on their environmental impact, to raise employee awareness and promote low-impact tools. We also started building a dashboard to monitor CO2 emissions from clients’ AI projects, aiming to generalize its use beyond client requests to all future projects.

AVEVA implements green software design principles. We’ve worked with the Green Software Foundation to benchmark the energy intensity of our products, and are working with industry stakeholders to develop tools for measuring and managing the net environmental impact of AI. Arti Garg, AVEVA’s Chief Technologist, currently chairs the IEEE Working Group P7100 dedicated to this task.

Baidu actively promotes the construction of sustainable AI, and we actively adopt AI and new technologies in data centers and office buildings to reduce carbon emissions and achieve green operations. We actively collaborate with partners utilize AI to empower green development through our intelligent transportation, and many energy-saving and carbon reduction solutions.

For all Data centers under construction, Data4 is conducting a lifecycle analysis in order to chose equipment’s with lowest impact.

EcoDataCenter

We are building and operating datacenter. Our action will be focus on reducing the life cycle of the IBX to reduce as much as possible the impact of AI.

We have built an open-source study of the carbon footprint of Generative AI. This study provides a detailed methodology to estimate emissions from GenAI models, case studies, an off-the-shelf calculator and best practices to significantly mitigate the environmental impact. We are still doing research to publish further insights.

We are currently testing an AI platform developed specifically for Groupe Duval and deployed in a secure and controlled environment.
Users of this AI are sensitized to the environmental impact of their searches, with information on the energy required for the query converted into grams of CO2.

We improve the transparency and reporting of AI energy consumption and carbon emissions on a platform with over a million models and datasets. This is done via the AI Energy Score project (described above), as well as mechanisms such as model cards and datasheets.

Nokia

As a cloud provider, OVHcloud offers infrastructure to train and deploy AI models, while also offering access to a wide range of world-class AI models.
Our commitment to sustainable AI is rooted in building sustainable infrastructure.

Photoroom builds efficient AI that scales responsibly. Processing billions of images each year, we train on low-carbon energy and optimize inference at every step to reduce emissions. By openly sharing our emission calculations and technical improvements, we help others build more sustainable AI too.

Salesforce embeds sustainability into every phase of AI development by minimizing our products’ environmental footprint through efficient, specialized models. We believe it is important to think holistically across Smart Demand (using AI wisely), Efficiency (doing more with less), and Clean Supply (powering what’s left with low-impact resources).

SAP embeds sustainability across the AI lifecycle by optimizing model efficiency, powering its data centers with renewable energy, and applying ethical design principles. SAP also delivers AI solutions that help customers reduce emissions, improve resource efficiency, and advance their ESG and sustainable development goals across global value chains.

Schneider Electric tackles sustainable AI by minimizing its energy footprint through efficient hardware and software, ensuring ethical development, and leveraging AI to optimize energy use and drive broader sustainability across industries.

In AI data centres, every watt counts. That’s why we developed GrapheneGPU — to reduce electricity consumption and power demand, while boosting computing performance. We maximize performance per watt consumed in GPUs — enabling more compute, more AI capacity, and better energy-efficiency. Performance and sustainability can go hand in hand.

Our sustainable AI team aims at setting an example on how to combine innovation and sustainability on AI. We develop training for employees, tools and methodologies to assist with the eco-conception of our projects and we measure and control the impact of our AI tools. We also work with the ecosystem to address and diffuse topics more globally and to formalize the regulation of sustainability.

Telehouse has launched the construction of a module in its TH3 Data Center in Magny-les-Hameaux that will use Direct Liquid Cooling technology. This building will be dedicated to AI stakeholders and will support ultra-high-density infrastructure per rack. We are strengthening our commitment to CSR by integrating sustainable and responsible practices into our operations.

Embedding digital decarbonization for responsible and sustainable AI.

Since 2023, SEI’s taskforce has been building internal capacity at the intersection of AI, digitalization, automation and sustainability science. We have fostered a community of practice around ethical, responsible AI, with a focus its environmental and societal impacts. As a global sustainability science leader, SEI is now a go-to hub for sustainable AI research and policy.

UBA

We do research and development to obtain metrics that can be used to assess the compliance of AI applications to the sustainability, accuracy, fairness and explainability principles and to measure the risks of not being compliant.

University of Maribor, Faculty of Tourism

The AI department at the University of Malta promotes sustainable AI by developing energy-efficient models, exploring ethical and responsible AI use, and applying AI to environmental challenges such as marine conservation, waste management, and precision agriculture. It fosters interdisciplinary collaborations to align AI innovation with ecological and societal goals.

Cerema

NECTEC advances sustainable AI through initiatives such as the AI for Thai platform, green manufacturing solutions, and the LANTA Supercomputer, all designed to optimize resource use, reduce environmental impact, and support climate action. These efforts directly contribute to the UN Sustainable Development Goals by promoting responsible innovation.

Arboretica

Electricity Maps

– We automatically compress AI models to make them faster, smaller, cheaper, greener for the public and for businesses.
– We automatically benchmark AI models wrt to different metrics including energy, CO2 emissions.

Sepia Infrastructure plays a key role in enabling green AI by building next-generation industrial campuses that bring together carbon-free energy, data centres, and complementary industries in a single, integrated setting. Committed to fostering operational synergies, advancing sustainability, and creating long-term social impact, Sepia is helping shape a more sustainable future for AI.

Taza World

TotaLinuX

Vector8