Artificial intelligence has tremendous potential to accelerate and support the global energy transition, according to a new study by the World Economic Forum, which highlights the technology’s potential to support and accelerate a more equitable energy transition, and establishes a set of principles for the energy industry to deploy AI in a safe, fair, and trustworthy way.
It can act as an intelligent layer across many applications to identify patterns, improve system performance, and predict outcomes of complex situations
However, leading energy and technology experts say that there are several key barriers preventing AI from being adopted rapidly or at global scale
Written in collaboration with BloombergNEF and the Deutsche Energie-Agentur (dena) – the German Energy Agency, 'Harnessing Artificial Intelligence to Accelerate the Energy Transition' reviews the state of play of AI adoption in the energy sector, identifies high-priority applications of AI in the energy transition, and offers a road map and practical recommendations for the energy and AI industries to maximize AI’s benefits.
The report finds that AI has the potential to create substantial value for the global energy transition. Based on BNEF’s net-zero scenario modelling, every 1% of additional efficiency in demand creates $1.3 trillion in value between 2020 and 2050 due to reduced investment needs. AI could achieve this by enabling greater energy efficiency and flexing demand.
“AI is already making its mark on many parts of society and the economy. In energy, we are only seeing the beginning of what AI can do to speed up the transition to the low-emissions, ultra-efficient and interconnected energy systems we need tomorrow. This report shows the potential and what it will take to unlock it – guided by principles that span how to govern, design and enable responsible use of AI in energy. Governments and companies can collectively create a real tipping point in using AI for a faster energy transition,” said Roberto Bocca, Head of Energy, World Economic Forum.
High priority applications for how AI can accelerate the transition to low-carbon energy future include identifying patterns and insights in data to increase efficiency and savings; co-ordinating power systems with growing shares of renewable energy; and managing complex, decentralised energy systems at scale.
Navigating these opportunities presents huge strategic and operational challenges for energy-intensive sectors and energy systems themselves, just as they are undergoing once-in-a-lifetime digital transformations. AI can act as an intelligent layer across many applications and has the ability to identify patterns and insights in data, ‘learn’ lessons accurately and improve system performance over time, and predict and model possible outcomes for complex, multivariate situations.
Recent efforts to deploy AI in the energy sector have proven promising but innovation and adoption remain limited. AI holds far greater potential to accelerate the global energy transition but it will only be realised if there is greater AI innovation, adoption and collaboration across the industry. To address this, the white paper establishes a set of principles to help industry govern and scale AI technology in a rapid, safe and fair manner.