Capgemini: Executives Must Address Gen AI’s Sustainability

Almost half of executives believe that their use of generative AI (Gen AI) has driven a rise in greenhouse gas emissions according to the Capgemini Research Institute.
The 2025 report, titled Developing Sustainable Gen AI, looked at the environmental impact of the technology and how organisations are prioritising this.
“If we want Gen AI to be a force for sustainable business value, there needs to be a market discussion around data collaboration, drawing up industry-wide standards around how we account for the environmental footprint of AI, so business leaders are equipped to make more informed, responsible business decisions and mitigate these impacts,” says Cyril Garcia, Capgemini’s Head of Global Sustainability Services and Corporate Responsibility and Group Executive Board Member.
“AI has the potential to accelerate business objectives and sustainability initiatives. We are proposing here practical steps to follow for business leaders to fully harness technologies such as Gen AI and deliver a positive impact for organisations, society and the planet.”
The environmental impact of Gen AI
Gen AI relies on processing enormous volumes of data.
This requires huge computational power, making the data centres it runs in particularly energy-intensive.
Predictions suggest that AI’s growth will increase data centres’ power demand by 15% to 20% annually, with a projection of hitting between 100GWh to 130 GWh hours by 2030 — enough to supply two-thirds of US homes.
Graphics processing units (GPUs) are integral to the functioning of this technology, but require rare earth metals that further contribute greenhouse gas emissions through mining alongside putting stress on natural resources.
In fact, estimates suggest Gen AI could create between 1.2 to five million tonnes of e-waste by 2030, around 1,000 times more than was produced in 2023.
Training a GPT-3 model, which includes 175 billion parameters, consumes an amount of electricity equivalent to the annual consumption of 130 US homes.
Just one size up, GPT-4, is estimated to be equivalent to the yearly power consumption of 5,000 US homes.
When models are being used, the inferencing phase requires an equal or greater amount of energy.
It is not just energy – water is also used. Running an inference of 20-50 queries on a large language model uses around 500ml of water each time.
How do executives feel about Gen AI?
McKinsey research from 2024 shows that 65% of organisations and individuals are using Gen AI.
This sparkly new technology promises streamlined efficiencies, innovative decision making and ultimately higher revenue.
However, this cannot come without AI’s enormous environmental costs.
Capgemini’s research found that 48% of executives believe that their use of Gen AI has driven a rise in greenhouse gas emissions.
Organisations measuring the environmental impact of their Gen AI use expect their share of emissions driven by it to rise from 2.6% to 4.8% by 2027.
It also says that 42% of executives have had to reassess their climate goals due to Gen AI’s growing footprint.
Are organisations taking action on Gen AI’s environmental impact?
The short answer is no.
“Organisations are currently taking only a partial view of costs, effectively ignoring the energy costs of model deployment and inferencing,” Capgemini’s report says.
Just 12% of executives surveyed by Capgemini said their organisations measure Gen AI carbon footprint.
Only 20% rank the “environmental footprint of AI” among the top five factors when selection or building Gen AI models – performance, scalability and cost dominate this list.
Further, just 27% of executives say they compare energy consumption levels of Gen AI models.
Steven Webb, UK Chief Technology and Innovation Officer at Capgemini, says: “Organisations need to make the footprint of Gen AI visible within their business analysis.
“It’s vital businesses fully track the impact of Gen AI as this is what enables strategies to measure and mitigate appropriately, as well as unlocking opportunities to implement sustainable practices throughout the Gen AI lifecycle.”
The sustainability potential of AI
Despite Gen AI’s sustainability problems, it has potential to do good.
Steven says: “Gen AI is already being used to support sustainability in enterprise. With its ability to transform the workforce by automating tasks and complex processes, Gen AI in the form of AI agents can play a pivotal role in optimising use of resources and improving efficiency at all levels, which is key to accelerating sustainability.
“Gen AI’s intense energy demands require a cautious balancing act from business leaders, however in the face of both economic and environmental challenges, AI agents can also equip leaders to make more informed, responsible business decisions.
“We’ve also seen that Gen AI is providing opportunities to push forward sustainable business objectives and progress environmental initiatives. For example, German company Compliance Solutions has launched an ESG AI-Agent that fully automates research, evaluation, and reporting on ESG topics.”
Explore the latest edition of Sustainability Magazine and be part of the conversation at our global conference series, Sustainability LIVE.
Discover all our upcoming events and secure your tickets today.
Sustainability Magazine is a BizClik brand
- Boeing & HPCL Join Forces to Decarbonise India's AviationRenewable Energy
- Henkel’s Big Step Forward in Sustainable Sports FootwearSupply Chain Sustainability
- Top 10: Sustainable Packaging InnovationsSupply Chain Sustainability
- Mars’ US$27m Pledge for Dairy Emissions ReductionSupply Chain Sustainability