Artificial intelligence (AI) has the potential to significantly reduce carbon emissions, with the International Energy Agency (IEA) estimating that it could drive emissions reductions three times larger than its own footprint. According to the IEA report, widespread adoption of AI applications in end-use sectors could lead to 1,400 million tonnes of CO2 emissions reductions in 2035.
The IEA highlights several ways AI can contribute to emissions reductions, including optimizing manufacturing processes, improving power grids, enhancing transportation and streamlining building energy consumption. For instance, AI can improve energy efficiency in industries like cement production by over 2% and save around 10% in energy consumption by optimizing heating, ventilation, and air conditioning systems in buildings.
However, AI's growing energy demand poses a challenge. Data centres are projected to more than double their electricity demand over the next five years, with AI driving a significant portion of this increase. The IEA emphasizes the need for a broad range of low-carbon electricity sources to meet AI's rising power demands.
To realize AI's emissions-reducing potential, governments and companies must address barriers to adoption, including limited access to data, lack of digital infrastructure and skills, regulatory and security restrictions and social or cultural obstacles. By overcoming these challenges and investing in low-carbon electricity sources, businesses can unlock the full potential of AI to drive sustainability and reduce emissions.
