How AI can drive a sustainable energy future

AI can be utilised in a diverse number of industries and processes to enhance the capabilities of managing environmental impacts and climate change. AI can be used to enhance clean distributed energy grids, sustainable supply chains, environmental monitoring and improving weather and disaster prediction.

In a recent study, PwC UK investigated the economic impact of AI’s in managing the environment within agriculture, water, energy and transport. The study concluded that using AI within environmental applications could generate over $5 trillion USD towards the global economy in 2030, over 4% increase in relation to current business activity.

Furthermore, the integration of could reduce global greenhouse gas emissions by 4% in 2030, an amount equating to 2.4 Gt CO2e, the equivalent to the 2030 annual emissions of Japan, Canada and Australia together. The other major benefit of AI implementation relates to overall productivity. AI could potentially generate over 38 million new jobs worldwide, offering new skilled positions within the transition.

Celine Herweijer, global innovation and sustainability leader for PwC UK explains that it is quite clear that AI can ensure our future systems are more productive, for both the environment and economy. Herweijer emphasises that AI technology could enable continued economic growth and at the same time, closer management of rising emissions.

PwC believes that AI could be most valuable and productive within the energy and transport industries, particularly within clean distributed energy grids and improved environmental monitoring. According to PwC, AI technology could enhance distributed generation, support the automation of manual and routine jobs and reduce overall energy emissions per unit of GDP by up to 8% by 2030.

Five key areas were identified within the report as ways to enhance the potential of AI. This includes:

Raising awareness, levels of collaborations and partnerships within industry, academia and with experts and policymakers.

Begin with a focus on ‘Responsible AI’ and expand on this approach towards environmental and social impacts

Include digital infrastructure requirements, access to AI systems and data and other relevant technologies.

Ensure there are opportunities for training and re-skilling industries to be capable of adapting to new technology

Supporting research and development from initial research through to deploying on a commercial scale.

PwC highlights how important AI’s contribution could be towards enhancing the decentralisation of power grids and electrification. PwC model believes a steady transition towards renewable energy, however, if this happened quicker than expected more research would be necessary. The report warns that a significant rise in AI adoption could potentially expose energy systems to certain risks associated with security and control. Other barriers related to integrating new technologies would also need to be addressed if there was a rise in AI.