The research models scenarios for AI’s use across four sectors – agriculture, transport, energy and water. The application of AI levers could reduce worldwide greenhouse gas (GHG) emissions by 4 per cent in 2030, an amount equivalent to 2.4Gt CO2e – equivalent to the 2030 annual emissions of Australia, Canada and Japan combined.
AI combined with the adoption of a complementary technology infrastructure such as AI-enabled distributed energy grids, distributed generation, distributed storage, industrial IoT, electric vehicle charging, dynamic pricing and smart meters in the energy sector, would have the biggest impact on GHG emissions, it concludes.
PwC estimated the energy sector could reduce GHG emissions by up to 2.2 per cent, while in transport, AI could result in a 1.7 per cent cut in GHG emissions.
“By applying AI to improve efficiencies in the energy sector across all fuels and regions, technology can help develop a cleaner and less fossil-fuel dependent energy sector that can lead to a world with a more prosperous economy and less climate change,” say the report’s authors.
The report looked at number of areas within energy to which AI could be applied to reduce carbon dioxide emissions:
• Smart monitoring and management of energy consumption;
• Energy supply and demand prediction;
• Co-ordination of decentralised energy networks;
• Predictive maintenance;
• Increased operational efficiency of renewable assets;
• Increased operational efficiency of fossil fuel assets.
“By allowing energy prices to respond to market signals in real time, smart monitoring has the potential to optimise electricity consumption by not just key sectors but also households and governments. Lower energy costs can result in output expansion by businesses and higher demand by consumers and boost economic activity,” says the report.
Similarly, decentralised energy networks can significantly improve the process of electricity transmission and distribution, resulting in higher productivity for the sector, and boost overall electricity production by enabling faster uptake of renewables, the report says.
The authors observe that automatic pricing of electricity reduces electricity wastage across the economy, lowering emissions, while the greater use of renewables, enabled by localised grids and AI technologies that improve the effectiveness of renewable assets, reduces fossil fuels’ share in energy production and shifts the energy mix towards less carbon-intensive energy sources.
Celine Herweijer, global sustainability leader at PwC UK, commented: “Technology firms and industry alike will need to champion responsible technology practices, considering social, environmental impact and long-term value creation. What is clear is that the companies and countries that fare best will be those that embrace the simultaneous changes and reinforcing opportunities of the AI era and the transition to sustainable economies.”
This article first appeared in Flex, issue 3. Read the full issue of Flex here