AI set to cut GHG emissions by 16% in the next 3-5 years

Artificial Intelligence-enabled use cases for climate action have the potential to help organisations fulfil up to 45% of their Economic Emission Intensity targets of the Paris Agreement. This is according to new research entitled Climate AI: How artificial intelligence can power your climate action strategy, from the Capgemini Research Institute, conducted in partnership with climate change start-up right. While AI offers many climate action use cases, scaled deployment is proving elusive and just 13% of organisations are successfully combining climate vision with AI capabilities.' Two-thirds (67%) of organisations have set 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; and adoption is on the rise as more than half of organisations (53%) are moving beyond pilots or proofs of concepts.' AI use cases include improving energy efficiency, reducing dependence on fossil fuels, and optimising processes to aid productivity. From the 800 sustainability and tech executives surveyed in 400 organisations in the automotive, industrial/process manufacturing, energy and utilities, consumer products, and retail industries, nearly half (48%) are using AI for climate action and as a result 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 impact of AI is significant. Organisations can expect to cut GHG emissions by 16% in the next three to five years through AI-driven climate action projects.' Across the five sectors, the research finds that AI-enabled use cases can 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. These, detailed in the report, include energy consumption and optimisation platforms, algorithms to automatically identify defects and predict failures without interrupting operations, and tracing leakages at industrial sites.

Successful deployment requires barriers to be overcome

Despite the considerable potential of AI for climate action, adoption remains low. This could be due to several barriers to progress:

• More than eight in ten organisations spend less than 5% of climate change investment on AI and data tracking
• Half (54%) have fewer than 5% of employees with the skills to take up data and AI-driven roles
• More than 55% of organisations said the actual benefits from their AI initiatives were lower than expected
• More than a third (37%) of sustainability executives have decelerated their climate goals in light of COVID-19, with the highest deceleration in the energy and utilities industry. 38% of all organisations have put a hold on capital expenditure allocated for climate initiatives.

European climate AI champions are leading the pack

Only 13% of organisations have aligned their climate vision and strategy with their AI capabilities 'these are who Capgemini defines as climate AI champions. Two-fifths of these come from Europe, followed by the Americas and APAC. Climate AI champions are closer to the required Paris Agreement temperature contributions compared with their peers in both scope 1 and 2 emissions and have made considerable gains in applying AI to reduce direct emissions.' A clear knowledge gap is also emerging, as 84% executives would rather compensate for (or offset) their carbon footprint than deploy technology solutions to reduce their footprint (16%) in the long run. This suggests a lack of awareness for AI climate action potential. According to the report, organisations need to invest in AI and data science teams to understand how best to deploy AI to harness it positively for sustainability.

Leverage AI's full climate action potential, but also consider its impact

Despite the advances made in cognitive computing, AI systems can consume a lot of power and can generate high volumes of climate-changing carbon emissions. Before beginning to deploy AI use cases, organisations need to carefully assess the environmental impact, build greater awareness and take actions to ensure that the benefits of their AI deployments outweigh their emissions 'cost.' "Addressing climate change is everyone's responsibility and AI has the potential to make a significant impact, yet only a fraction of organisations are aligned on how this technology can be used to its full potential,'' says Anne Laure Thieullent, Vice-President, Artificial Intelligence and Analytics Group Offer Leader at Capgemini. "Action needs to come from the top and it starts with embedding a climate vision at the centre of an organisation. Without a clear vision, there is a missing link between how intention and technology can address the issue. Organisations need to establish leadership, educate, and build awareness around AI solutions. If organisations can harvest data correctly and establish scalable operating models, then the technology that exists today has a real chance of making the significant impact we all need. Additionally, it is important for organisations to assess the environmental impact of AI ' measuring and reporting on the CO2'footprint can be one of the ways to increase general awareness of emissions." This story was originally published on Smart Energy International