AI’s Economic Gains Outweigh Carbon Emissions Cost, Says IMF: Experts Respond

The International Monetary Fund (IMF) recently shared some intriguing insights, stating that the economic benefits of artificial intelligence are expected to enhance global output by about 0.5% each year from 2025 to 2030. This growth is anticipated to outweigh the costs associated with the increasing carbon emissions from the data centers that support AI models.

According to the IMF, the global demand for electricity driven by AI could surge more than threefold, reaching around 1,500 terawatt-hours (TWh) by 2030. The International Energy Agency predicts that the worldwide push towards AI technology will require nearly as much energy by the end of this decade as Japan currently consumes, yet only about half of this energy demand is expected to be satisfied by renewable sources.

The carbon footprint resulting from this surge will largely hinge on whether tech companies can fulfill their commitments to reduce emissions from data centers through greater reliance on renewables and other strategies. Still, there are lingering concerns regarding the efficiency and commercial viability of the current renewable energy solutions available.

This ongoing narrative of the AI and sustainability paradox has sparked discussions among industry experts about the transition to renewable energy and how AI can both promote and challenge sustainability efforts.

William White, Senior Application Specialist DER at Fluke Corporation, said:

“Driven by the use of artificial intelligence (AI) and widespread electrification, a diverse use of energy sources will be required to meet rising electricity demand. This, coupled with the global goal of tripling clean electricity generation by 2030, is accelerating new investments in the renewable energy market.

Solar power is one of the world’s fastest growing sources of energy. The Energy Information Administration (EIA) projects that 93% of all new utility-scale electric generating capacity added in 2025 will be from solar, battery storage and wind sources. Technological advancements have made solar a more affordable and attractive option in recent years. However with 91% of the solar industry admitting they’re concerned about the efficiency of the current generation of solar modules, clearly significant challenges must still be addressed.

“As energy demand grows, the quality and efficiency of solar installations have become more important for maximising energy output, extending system lifespans and ensuring installer safety. AI-enabled technologies can automate maintenance operations, analysing data and proactively detecting issues before they risk causing failures. By applying advanced diagnostic tools and providing in-depth training for technicians on how to use them, we can maximise solar production and maintenance efficiency. This will help pave the way for a greener solar-powered future.”

Iju Raj, Executive Vice President of Research & Development at AVEVA, said:

“AI will undoubtedly have a significant role to play when it comes to the sustainability of industrial plants and processes, and will be crucial in driving the industry towards overall improved efficiency and sustainability.

The reason people aren’t using renewable energy everywhere currently is because it’s still too expensive and often not as reliable as traditional methods of power production. If AI can be leveraged to drive down the cost of renewable energy and improve its reliability, using renewables will become a no brainer!

The goal of every company is to make money – so it’s here that we’re likely to see a big shift on sustainability. Already, AI is helping organisations to become more efficient and to reduce their emissions from their industrial plants. The role of AI in boosting sustainability will only increase as technology evolves, and ultimately, AI will be a key factor in driving the journey to Net Zero.

As an example, AI could be given an objective to minimise a factory’s greenhouse gas emissions using any available means that are legal, ethical and safe. AI would take it from there by identifying underperforming assets, prescribing & coordinating maintenance and then improving the operational control of the assets. This would, in turn, optimise fuel utilisation and thus minimise carbon and other harmful by-products that are released into the atmosphere. All of this will initially be under human supervision, but in the future this could viably move to full autonomy.”