AI's Energy Impact: Data Centres Under Fire for Emissions

AI is driving massive growth in energy consumption at data centres.
Recent reports reveal that the carbon footprint of major companies like Google, Microsoft, Meta and Apple could be significantly higher than official figures suggest.
This has sparked debate over how the industry can continue advancing AI while meeting environmental targets.
The International Energy Agency (IEA) reported that data centres accounted for 1% to 1.5% of global electricity use in 2022, even before AI reached its current peak. The IEA warns that global electricity demand could double by 2026, potentially doubling of carbon dioxide (CO2) emissions from data centres between 2022 and 2030.
AI systems are particularly power-hungry. According to Morgan Stanley, AI-related data centre emissions could triple by 2030, reaching 2.5 billion tonnes of CO2.
This rapid growth poses a challenge to tech companies striving to balance their pursuit of AI dominance with their carbon-neutral promises.
The struggle to reduce data centre emissions
The expansion of data centres, especially in the AI sector, makes emission reduction increasingly difficult.
In the UK, data centres have been recognised as Critical National Infrastructure (CNI), emphasising their importance to the digital economy. Yet this rapid growth threatens sustainability goals. For instance, Google reported a 13% increase in emissions in early 2024, largely due to its AI-focused data centres.
“The race for AI dominance is heating up, but at what cost?” questions Elio van Puyvelde, Chief Information Officer at Nscale.
He points out that older data centres struggle to meet AI's power demands, leading to higher emissions. Despite investments in renewable energy, the scale of AI's growth risks outpacing these efforts.
Morgan Stanley’s prediction that AI could cause data centre emissions to triple by 2030 presents a stark reality. To address this, Elio suggests that new data centres should be designed with sustainability as a priority.
This includes locating them in areas with abundant renewable energy and focusing on operational efficiency. Elio also highlights the need to optimise AI workloads, as many are poorly managed, leading to wasted energy.
“Accelerating AI hardware and software optimisation is one of the best routes to managing AI energy consumption levels,” he explains.
Innovating sustainably for the future
As data centre investments surge, the industry faces the challenge of meeting AI's demands sustainably.
“Organisations across the globe are rushing to be the biggest and best AI innovator,” says Dave King, Senior Principal Product Engineer at Cadence.
However, he notes that AI's extreme power requirements have forced a "cataclysmic shift" in how data centres are powered and cooled.
Balancing the environmental impact of AI with technological progress is no easy feat. However, emerging technologies offer some solutions.
Dave suggests digital twin technology could help reduce data centres' carbon footprints. Digital twins create virtual models of physical infrastructure, allowing managers to better assess capacity needs, improve power management, and optimise cooling systems.
"By prioritising data centre efficiency through digital twins, AI's growth doesn't need to burden the environment," he says. This approach promotes responsible innovation, reducing the constant need to build new data centres.
Balancing AI growth with sustainability
The AI revolution has thrust data centres into the spotlight of both technological and environmental discussions.
As the sector grapples with soaring energy demands, it faces a pressing need to find sustainable growth strategies that align with global carbon reduction goals.
By focusing on energy-efficient infrastructure, optimising AI workloads, and adopting technologies like digital twins, the industry can work towards a future where AI’s expansion does not come at the expense of the planet.
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