Will AI Speed or Slow Big Tech’s Progress to Net Zero?

Big Tech companies have positioned themselves at the forefront of the global effort to achieve net zero. But despite having ambitious targets and high-profile sustainability initiatives, the sector faces mounting scrutiny over both its progress and the credibility of its pledges — especially as the rapid expansion of AI drives up energy demands and emissions.

However, AI — although somewhat part of the problem — is also part of the solution.

The latest generation of AI models require immense computational power, running on thousands of high-performance GPUs in hyperscale data centres. These facilities demand constant power and advanced cooling, pushing energy use to new heights.

But by optimising energy systems, enhancing data analysis and driving innovation, AI has the ability to significantly reduce emissions and improve sustainability across sectors.

According to the International Energy Agency (IEA), data centres are projected to consume more than 1,000TWh of electricity globally by 2026 — roughly equivalent to the annual consumption of Japan. 

Microsoft’s electricity use has tripled since 2020, contributing to a 30% rise in its carbon emissions. 

Fellow Big Tech giant Google’s greenhouse gas emissions have soared 48% since 2019, with its 2024 Environmental Report revealing a 13% year-on-year increase, largely due to AI and data centre expansion.

AI’s role in Big Tech’s ambitious net zero commitments

Bloomberg reported in 2024 that Big Tech’s climate goals are at risk thanks to AI’s massive energy demands. But companies like Alphabet, Microsoft, Apple, Meta and Amazon — commonly known as the Big Five —have all pledged to achieve net zero emissions, some as early as 2030: well ahead of the 2050 deadline set by most international frameworks.

For example, Google aims to achieve net zero emissions across its operations and value chain by 2030, using AI to help achieve this goal. However, Google’s growing AI activities have also contributed to an increase in emissions, making it a challenging task to reach net zero.

“AI represents a huge opportunity for sustainability,” Google’s CSO Kate Brandt says. “For example, our AI-powered efficiency recommendation system for data centres led to a 40% reduction in the energy we use for cooling. There’s a huge opportunity for us to reduce energy consumption across our own data centre fleet and also to make [the technology] more widely available [for others to use].”

Since saying that in 2020, Google has curated its operations to make its facilities around 1.8 times as energy efficient as “the typical enterprise data centre”.

Google’s 2024 Environmental Report, however, did uncover a 13% rise in greenhouse gas emissions in the 12 months prior largely due to energy consumption from AI and data centres.

Speaking alongside SVP, Learning & Sustainability, Benedict Gomes, Kate says in response: “A sustainable future requires systems-level change, strong government policies and new technologies. We’re committed to collaboration and playing our part, every step of the way.

“Scaling AI and using it to accelerate climate action is as crucial as addressing its environmental impact.”

AI for impact

Over at Amazon, there are multiple ways it is leveraging AI to underpin a more sustainable future — both for itself and the world around it.

It highlights seven main use cases, covering applications from reducing packaging waste to democratising data. This, the company says, epitomises Amazon’s “unique approach to AI” and is “helping advance and innovate on sustainability goals”.

Kara Hurst, Amazon’s CSO, says: “Climate change is one of the world’s greatest challenges — and at Amazon, we know we have to move fast, constantly innovate, invest and stay nimble in order to continue to become a more sustainable company. AI and ML can help us meet our climate goals at the speed, scale and urgency our planet requires.”

This is nothing new to Amazon, however. For decades, Amazon has leveraged AI and ML to drive innovation — whether it’s minimising packaging and food waste or optimising the efficiency of its fulfillment operations. Through Amazon Web Services (AWS), which it has pledged to be net-zero carbon by 2040 and water positive by 2030, Amazon is not only providing customers with advanced AI infrastructure and solutions, but also making AI more accessible.

Its infrastructure, it claims, is up to 4.1 times more energy efficient than on-premises and can reduce workloads’ carbon footprint by up to 99%.

This, Kara attests, empowers businesses and individuals to accelerate their purchases, operations and sustainability efforts.

“As the most transformational technology of our time, Amazon expects AI to be an increasingly important part of our work to build a more sustainable business,” Kara adds.

The double-edged sword

“The challenge of reaching our sustainability goals given the increased demand for energy and resources driven by AI is not unique to Meta,” Meta’s 2024 Sustainability Report says, acknowledging the dual challenge posed by AI.

Like its Big Tech counterparts, Meta is no stranger to this challenge. While AI is driving its business growth and innovation, the technology is also significantly increasing its energy and resource demands, posing as an enabler of and challenge to its net zero goals.

Although far from a unique approach, Meta is pairing renewable energy with its AI initiatives to mitigate its impact, all while allowing AI to continue to optimise operations in the pursuit of sustainability goals.

By matching 100% of its data centre and office electricity use with renewable energy — something it has done since 2020 — Meta is ensuring that the energy-intensive AI infrastructure is increasingly powered by low-carbon sources.

Nuclear is now being explored to meet the rising power demands from AI expansion, with Meta aiming to add between 1GW and 4GW of new nuclear capacity in the US by the early 2030s.

“We’re optimistic about the role technology will play in helping us address the climate crisis,” Meta CEO Mark Zuckerberg says. “But the task ahead is massive. As both a company and a platform for social connection, we take our responsibility seriously.

“We’ll continue our sustainability work across our business and products. The possibilities that our technology will unlock for people only matter if we have a safe and thriving planet.”

Technical innovation and efficiency gains

As well as working on their own environmental impact, Big Tech is addressing energy challenges by investing in advanced technical solutions. Custom AI chips — like Amazon’s AWS Inferentia and Google’s Tensor Processing Units (TPUs) — are designed to run AI workloads more efficiently, reducing the power required per computation.

Advanced cooling also comes into play, with liquid cooling and heat re-use helping some of the world’s major tech players manage the intense heat generated by AI servers. 

This reiterates how the sector’s trajectory matters far beyond its own footprint. While Big Tech’s direct emissions are significant, its influence on global supply chains and its role in developing AI tools that optimise energy use, logistics and manufacturing mean its climate strategies set precedents for other industries.

AI’s potential to drive sustainability is enormous. PwC modelling suggests that if AI-driven efficiency gains are widely adopted, they could offset the added energy demand from data centres, potentially making AI’s overall effect on energy use neutral or even positive by optimising power grids, predicting demand, streamlining logistics and reducing waste across sectors.

This doesn’t mean that Big Tech’s climate ambitions aren’t at a crossroads, though. The same AI innovations that threaten to derail net zero targets also offer the tools to accelerate progress — if deployed wisely and transparently. 

As both a challenge and a solution, AI’s impact on sustainability will shape not just the future of the tech sector, but the global fight against climate change.

Read this feature in the August edition of Technology Magazine by clicking here.