Organizations are increasingly aware of the environmental footprint of Gen AI, but most aren’t able to address it alone

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Capgemini SE
Capgemini SE

Press contact:
Victoire Grux
Tel.: +33 6 04 52 16 55
E-mail: victoire.grux@capgemini.com

Organizations are increasingly aware of the environmental footprint of Gen AI, but most aren’t able to address it alone

  • Almost half of executives believe that their use of Gen AI has driven a rise in Greenhouse Gas (GHG) emissions, and 42% have had to relook at their climate goals

  • However, more than half say driving efficiency is more important than measuring impact.

Paris, January 14, 2024 The Capgemini Research Institute’s report into the sustainability of generative AI, ‘Developing sustainable Gen AI’, published today, shows that Gen AI has a significant and growing negative environmental impact. However, many organizations are failing to appropriately track this growing footprint, which is jeopardizing their ESG objectives. As businesses weigh up Gen AI’s ability to drive business growth against the technology’s environmental cost, the report outlines measures to design a responsible and sustainable generative AI strategy.

Throughout its lifecycle, generative AI has a significant environmental impact
Generative AI adoption has accelerated rapidly, with previous Capgemini research showing that while only 6% of organizations had integrated generative AI across their business functions and locations as at end-2023, that figure had risen to 24% as at October 2024. As a whole, AI not only drives business growth but also has the potential to enhance energy efficiency and support sustainability initiatives. However, generative AI requires processing vast amounts of data and significant computational power, which consumes large quantities of electricity, water, and other resources.

As a result, nearly half (48%) of executives believe that their use of generative AI has driven a rise in GHG emissions. This increase in carbon footprint is projected to continue to grow. Organizations that currently measure their Gen AI footprint expect the share of generative AI-driven emissions as a proportion of total organizational carbon emissions to rise, on average, from 2.6% to 4.8% over the next two years. To mitigate this, organizations are increasingly turning to renewable energy sources and optimizing their AI infrastructure.

A minority of organizations are prioritizing and addressing the sustainability of Gen AI
With rapid innovations around generative AI, organizations’ sustainability reporting has not kept up with the pace of change. Only 12% of executives that use Gen AI say their organization measures the environmental footprint of their use, and, in fact, only 38% claim to be aware of that environmental impact. Similarly, as companies try to keep up with competitors, performance, scalability and cost are key considerations for generative AI model evaluation, while sustainability is only of marginal importance. Only one fifth of executives rank the environmental footprint of Gen AI as a top 5 factor when selecting or building Gen AI models, and more than half recognize that including sustainability as a key criterion in vendor selection for all generative AI-related requirements would reduce environmental footprint.