AI IN ENERGY
In what ways can the energy industry utilise machine learning capabilities to address the urgent challenges of today ?
WRITTEN BY : MARIAM AHMAD
y this point , it ’ s a safe assumption that most people are at least somewhat aware of terms such as net zero and energy transition ; endless conversations surrounding ’ zero carbon 2030 ’ are seemingly pervasive in our climate change vernacular and corporate conversations .
As businesses look to scale processes , enabling them to be more cost-efficient and sustainable , the deployment of AI can prove invaluable . The convergence of AI and energy means that on the convoluted path towards achieving net zero , businesses are able to better manage operations . The integration of machine learning not only enhances productivity and releases resources for the transition towards sustainable energy , but it can also directly contribute to reducing the environmental impact through the ramping of renewables and integrating cloud computing , alongside improving the traceability of supply chains and increasing transparency in governance .
Every cloud has a sustainable lining For all the denunciations that the oil-andgas industry receives , it nevertheless remains vital within the climate change discussion – and to energy security at large . Research from the International Data Corporation has found that the adoption of cloud computing in large-scale data centres has the potential to decrease carbon dioxide emissions by at least one billion metric tonnes or more .
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