AI Can Help Organizations To Slash 16% GreenHouse Gas Emission In Next 3-5 Yrs: Report
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Artificial Intelligence (AI) can be used to help organizations truncate their greenhouse gas emission by 16 per cent in the next three to five years, finds a new study.
According to the Capgemini report, AI-powered use cases for climate action have the potential to help organizations fulfil up to 45 per cent of their Economic Emission Intensity (EEI) targets of the Paris Agreement.
After surveying 800 sustainability and tech executives from 400 organization, it was found that almost 48 per cent of them are using AI for climate action and as a result have reduced greenhouse gas emissions (GHG) by 12.9 per cent, improved power efficiency by 10.9 per cent and reduced waste by 11.7 per cent since 2017. The organization involved were in the automotive, industrial/process manufacturing, energy and utilities, consumer products, and retail industries.
The report noted that around 56 per cent of experts believe AI to be the top technology for climate action compared with 93 per cent of experts in India, 16 per cent in US, 33 per cent in UK, and 100 per cent in China.
At the end of the study, it was found that around 14.7 per cent of the organizations worldwide could improve power/industrial efficiency compared to 14.6 per cent in India and 15.5 organizations in the us. Around 14.2 per cent of the organization believe that AI will help them with cost savings—carbon credits, legal fees, insurance premiums, and risk mitigation.
However, it was found that deployment of AI for climate action is still low. Out of eight companies in ten spend less than 5 per cent of climate change investment on AI and data tracking, half the organizations surveyed had only 5 per cent of employees with skills to handle AI-driven roles.
The report has also noted that AI systems and solutions can lead to a lot of power consumption and also generate high volumes of carbon emissions. It further raised caution that organizations must carefully assess the environmental impact before deploying AI use cases.