AI: Savior or Saboteur? Can It 'Offset' Its Soaring Emissions?

AI: Savior or Saboteur? Can It 'Offset' Its Soaring Emissions?

April 14, 2025

Whether you embrace it or not, artificial intelligence (AI) is increasingly integrated into our daily routines. Whether it’s browsing online stores or using search engines, AI is rapidly turning into an indispensable, efficiency-boosting resource for both individuals and businesses.

When it comes to climate change AI is also demonstrating its value in this area. At the United Kingdom's Cambridge University, scientists are employing AI across various fields such as climate modeling and land-use planning, viewing it as a revolutionary instrument for safeguarding the environment.

Scientists from Oxford University have developed an artificial intelligence tool aimed at enhancing transparency regarding corporate environmental practices. Notably, even tech giant Google has highlighted its advantages, working on several AI-driven solutions to boost climate resilience.

Even with the significant potential for AI to make a beneficial difference climate crisis There are worries about its substantial potential to increase greenhouse gas emissions.

According to a recent report by the International Energy Agency (IEA), artificial intelligence is causing a significant rise in electricity consumption. Data centres , which serve as the foundation for AI systems, are expected to see their energy consumption double over the next half-decade.

The IEA forecasts that by 2030, the power consumed by data centers will increase to approximately 945 terawatt-hours, surpassing the total electrical usage of Japan.

Nevertheless, the report also highlights that AI could potentially reduce emissions Elsewhere, it states that if implemented correctly, the carbon reductions credited by this method could compensate for the extra emissions produced.

AI is among the most significant developments in the realm of energy today," states IEA Executive Director Fatih Birol. "However, up until this point, policymakers and market entities have not had access to comprehensive resources to grasp all the various implications.

How much energy does artificial intelligence require?

Artificial intelligence demands substantial energy for both training and operation. The significant computational power needed to sustain extensive language models originates from numerous servers located within data centers. data centres , with some consuming as much electricity as an entire small nation.

Data centers can be found across the globe; however, the United States takes the lead with 5,381 installations, accounting for approximately 40 percent of the worldwide market. Significant players in this sector also encompass nations like the UK, Germany, India, Australia, France, and the Netherlands.

The energy usage of these establishments is considerable. Some AI-focused data centres Consume as much electricity as two million homes. In 2023, these entities represented approximately 1.5 percent of overall global electricity usage, yet their demand is expected to significantly increase in the following years.

Training AI requires a great deal of processor power, and therefore a lot of electricity. Research published in the Journal of Machine Learning found that training the popular OpenAI ChatGPT The model utilized 1,287 megawatt-hours of electricity, equivalent to the amount of CO2 produced by 80 short-haul flights within Europe.

What sets generative AI apart is the high level of computational intensity it demands," explains Noman Bashir, who holds the position of Computing and Climate Impact Fellow at MIT. "At its core, it’s simply computation, yet a generative AI training setup could use up to seven or even eight times as much energy compared to an average computing task.

Operating the software consumes less energy for each individual task; however, this can rapidly accumulate in terms of overall power usage when millions of inquiries are processed daily.

The Electric Power Research Institute discovered that, for each inquiry, ChatGPT uses roughly 2.9 watt-hours of energy, which is about ten times more than what is needed for a typical Google search.

By early 2025, ChatGPT was handling over a billion daily inquiries, with this figure continuing to increase.

In early 2025, approximately 8 percent of American adults had begun using ChatGPT. primary search engine That figure remains significantly lower than those using Google, yet considering it has surged from only 1 percent in June 2024, it highlights the swift transition toward AI-driven applications.

Additionally, we must take into account the evolving nature of AI. Present inquiries typically restrict themselves to text-only engagements. As new developments arise, this could expand to include more interactive forms. AI video , image and audio applications have no precedents, but they are expected to be even more demanding when it comes to resource consumption.

When considering the environmental effects of generative AI, it’s more than just the power used when plugging in your computer," explains Elsa A. Olivetti, who is a professor in Materials Science at MIT. "The repercussions extend far beyond that, affecting systems as a whole and lasting due to our various actions.

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Is it truly possible for AI to counterbalance its own carbon footprint?

As per the IEA, worries that Artificial intelligence might speed up global warming. It suggests that even with the increase, emissions from data centers will remain a small portion of global energy-related emissions, estimated at about 1.5 percent.

The argument posits that broad acceptance of artificial intelligence might enhance numerous operations' efficiency, thereby cutting down emissions elsewhere. This potential reduction can stem from improved industrial procedures, enhanced scientific exploration, or advancements in technological creativity.

The IEA suggests that widespread use of current technologies could AI-led solutions This could result in emission reductions of as much as 5 percent by 2035. The claim is that this reduction would compensate for the rise in emissions caused by the growing demand for data centers.

A separate report from Energy Intelligence predicted a doubling of energy demand, but also framed AI as a key enabler of the clean energy transition.

It mentioned improved grid management, decreased costs in low-carbon technologies, and better incorporation of renewable energy sources as key factors. benefits AI could bring It was also contended that improvements in processor efficiency, advancements in cooling technologies, and optimizations in algorithms will eventually mitigate AI's significant energy consumption.

Even though the IEA report views the future of AI and its effect on climate change positively, it also states that achieving this outcome is not guaranteed.

The report emphasizes that "there is presently no significant drive to guarantee broad acceptance of these AI applications." Consequently, it adds, "their combined effect might remain minimal as late as 2035 unless the essential supporting environments are established."

Harnessing AI's capabilities will demand focused efforts across various areas. Notably, it highlights the significant benefits AI could bring to the energy sector by improving grid management and distribution, an aspect where AI is currently vastly underutilized.

It also acknowledges that investing in low-carbon electricity production is essential, especially regarding power supply. energy-hungry data centres .

Certain players are advancing in this area. Amazon leads as the biggest corporate purchaser of renewable energy globally. The company states that more than 90 percent of its activities, encompassing its Amazon Web Services data centers, are now fueled by renewable sources.

With more than 300 data centers globally, Digital Reality has pledged to utilize renewable energy sources. Currently, 100 percent of the energy requirements for their European properties are covered by purchased renewable energy.

However, transitioning to environmentally friendly practices isn’t simple in the data center industry. The inconsistent supply of renewable energies poses a difficulty, along with regional constraints that can affect access to sustainable power options.

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The part played by the United States in shaping AI's influence on future climatic changes.

Given that many of the world's largest data centers are located in the United States, this country will experience the most significant increase in energy consumption.

By the close of the decade, the expected energy usage from data centers is forecasted to surpass that of every other major power-consuming activity when combined, including aluminum production, concrete manufacturing, chemical processing, among others, as stated in the IEA report.

Currently, U.S. data centers depend primarily on fossil fuels, notably natural gas. The IEA does not anticipate this shifting anytime soon, especially considering the present administration's emphasis on utilizing these polluting energy sources.

Just this week, President Donald Trump issued an executive directive asking cabinet officials to pinpoint areas where coal-driven facilities could host AI data centers.

In Louisiana, plans have been initiated for the development of a substantial natural-gas-powered facility designed exclusively to serve a huge new data center currently under construction. Meta .

The IEA's report outlines a situation that can only come about through collaborative actions and strong political backing. According to current objectives, AI might equally well be employed for discovering new oil and gas fields as for identifying methane emissions or enhancing grid efficiency.

When discussing how AI might 'counterbalance' its carbon footprint, we must consider the broader implications. Since CO2 remains in the atmosphere for centuries, even if AI ultimately discovers methods to reduce greater amounts of emissions than it generates, it cannot negate the harm caused during the interim period.

The report states that "the broad implementation of current AI technologies might result in emission cuts significantly greater than those produced by data centers; however, these reductions would still be considerably insufficient to tackle climate change effectively."

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