Using AI to tackle climate change

Artificial intelligence-powered use cases for climate action could help organisations meet up to 45% of the Economic Emission Intensity (EEI) targets of the Paris Agreement. New research from the Capgemini Research Institute has found that while AI offers many climate action use cases, only 13% of organisations are successfully combining climate vision with AI capabilities.

AI use cases include improving energy efficiency, reducing dependence on fossil fuels and optimising processes to aid productivity. The research found that 67% of organisations have long-term business goals to tackle climate change.

While many technologies address a specific outcome, such as carbon capture or renewable sources of energy, AI can accelerate organisations’ climate action across sectors and value chains. Adoption is on the rise, with 53% of organisations moving beyond pilots or proofs of concepts.

The research surveyed 800 sustainability and tech executives from 400 organisations in a range of industries and found that 48% are using AI for climate action and have reduced greenhouse gas emissions (GHG) by 12.9%, improved power efficiency by 10.9% and reduced waste by 11.7% since 2017.

The potential positive impact of AI is significant. AI-driven climate action projects can help organisations cut GHG emissions by 16% in the next three to five years. AI-powered use cases can also deliver up to 45% of the Paris Accord requirement, leading up to 2030. The consumer retail sector demonstrates the most potential for improvement using AI at 45% and wholesale retail the least at 11%.

By analysing more than 70 climate action AI use cases, Capgemini identified the 10 with the biggest impact, which include energy consumption and optimisation platforms, algorithms to automatically identify defects and predict failures without interrupting operations, and tracing leakages at industrial sites.

Despite the potential of AI for climate action, adoption remains low, with more than eight in ten organisations spending less than 5% of climate change investment on AI and data tracking. Additionally, 54% of organisations have less than 5% of employees with the skills to take up data and AI-driven roles.

“Addressing climate change is everyone’s responsibility and AI has the potential to make a significant impact, yet only a fraction of organisations are actively using this technology to its full potential,” said Anne Laure Thieullent, Vice President, Artificial Intelligence and Analytics Group Offer Leader at Capgemini.

In light of the COVID-19 pandemic, 37% of sustainability executives have decelerated their climate goals, with the highest deceleration in the energy and utilities industry. 38% of organisations have put a hold on capital expenditure allocated for climate initiatives.

Only 13% of organisations have aligned their climate vision and strategy with their AI capabilities — Capgemini defines these organisations as climate AI champions.

Climate AI champions are closer to the required Paris Agreement temperature contributions compared with their peers in scope 1 and 2 emissions and have made considerable progress in applying AI to reduce direct emissions. Two-fifths of these come from Europe, followed by the Americas and APAC.

The research also revealed a lack of awareness for AI climate action potential, as 84% of executives would rather compensate for (or offset) their carbon footprint than deploy technology solutions to reduce their footprint (16%) in the long run. Organisations need to invest in AI and data science teams to understand how best to deploy AI to harness it positively for sustainability.

Before using AI use cases, organisations must carefully assess the environmental impact of AI systems and solutions, building AI solutions with sustainability core design principles, to ensure that the benefits of their AI deployments outweigh their emissions ‘costs’.

“Organisations have the opportunity to prioritise the deployment of AI solutions to address their sustainable goals. Frameworks now exist to educate, build awareness, establish scalable operating models and manage data to deliver tangible business outcomes with AI applied to climate action. And, of course, this requires AI solutions to be designed, built, deployed and monitored with sustainable design principles to ensure overall positive environmental impact,” Thieullent said.

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