As artificial intelligence (AI) technologies surge forward at breakneck speed, the world’s largest tech companies are finding themselves at a crossroads: how to balance the ballooning energy demands of AI with ambitious net zero emissions targets. The stakes are high, not only for the companies themselves but for the planet at large. The latest data and industry moves reveal a complex, sometimes paradoxical, relationship between AI innovation and sustainability efforts.
According to the International Energy Agency (IEA), data centres are on track to consume over 1,000 terawatt-hours (TWh) of electricity globally by 2026—a figure that rivals the entire annual power usage of Japan. This startling projection highlights just how dramatically the AI revolution is reshaping the world’s energy landscape. And the impact is already visible in the numbers: Microsoft’s electricity consumption has tripled since 2020, resulting in a 30% increase in its carbon emissions. Google’s greenhouse gas emissions, meanwhile, have soared by 48% since 2019, with a 13% year-over-year jump in 2024 largely attributed to the proliferation of AI and the rapid expansion of data centres, as reported in Google’s 2024 Environmental Report.
Yet, amid these daunting figures, there’s a silver lining—or at least a glimmer of hope. The very technology that’s driving up energy consumption is also being harnessed as a powerful tool for environmental stewardship. Kate Brandt, Google’s Chief Sustainability Officer, captured this duality succinctly: “AI represents a huge opportunity for sustainability. 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].”
Amazon, another tech behemoth, is also leaning into AI as a catalyst for sustainability. Kara Hurst, Amazon’s Chief Sustainability Officer, emphasized the urgency and scale of the challenge: “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.” Amazon’s AI-driven initiatives are manifold: reducing packaging use, identifying damaged items to prevent waste, monitoring produce to cut down on food spoilage, reducing returns by helping customers find the perfect fit, measuring the carbon footprint for products, and even preventing deforestation by democratizing data. The company is also betting on its own AWS chips to power AI more efficiently.
But the energy challenge remains immense. Sophisticated AI models, like those powering modern natural language processing and computer vision systems, require thousands of high-performance chips working in tandem—meaning small server rooms are a thing of the past. The new era belongs to industrial-sized data centres with advanced cooling systems and robust power infrastructure. This trend is creating enormous opportunities for companies that provide the backbone of the digital world.
In the UK, the data centre boom is fueling a new wave of investment and infrastructure development. Tritax Big Box, a FTSE 250 real estate investment trust (REIT), is aggressively expanding into the data hub market. The company acquired its first data hub site in January 2025, which it predicts will be “one of the largest data centres in the UK,” and quickly followed up with a second acquisition. These two sites, both located in well-connected areas of London, boast a combined potential capacity of 272 megawatts (MW) and offer ample room for long-term growth. Tritax isn’t stopping there; the company has a pipeline of another 1 gigawatt (GW) for future data centre development.
The UK already has 477 data centres in operation, but according to construction firm Barbor ABI, nearly 100 new sites will be required between 2025 and 2030 to keep up with demand. This expansion underscores the vital role that digital infrastructure now plays in both the AI revolution and the broader economy. Of course, building these massive facilities is not without risk—returns depend on construction costs, interest rates, and the ever-shifting tides of technology adoption.
It’s not just property developers who stand to benefit. Companies like Volex, a specialist in high-speed cables, are also seeing a surge in demand. Volex’s products are essential for ensuring the reliable, lightning-fast data connections that modern data centres require. As more sites come online and as AI workloads continue to grow, the need for advanced cabling and connectivity solutions will only intensify.
Tech giants are also investing in specialized hardware to make AI operations more energy efficient. Amazon’s AWS Inferentia and Google’s Tensor Processing Units (TPUs) are designed to handle AI workloads with lower power consumption per computation. Meanwhile, Meta is exploring nuclear power to support its AI infrastructure, with plans to add between 1 GW and 4 GW of new nuclear capacity in the US by the early 2030s. Notably, Meta already matches 100% of its data centre and office electricity use with renewable energy.
This arms race for efficiency is not just about optics. According to analysis from PwC, if AI-driven efficiency improvements are adopted widely, they could offset the increased energy demand from data centres. AI’s optimization capabilities in power grids, demand prediction, logistics, and waste reduction could, in theory, result in a neutral or even positive overall energy impact. It’s a tantalizing prospect: the very technology that threatens to overload the grid could also help save it.
Still, the path forward is anything but straightforward. Investors are watching the sector closely, with some wary of sky-high valuations for US tech giants like Nvidia, Microsoft, Meta, and Alphabet. Yet, as recent UK-focused analysis points out, opportunities abound beyond the usual suspects. Companies positioned to support the infrastructure of AI—whether through real estate, cabling, or power—may offer attractive alternatives for those seeking to ride the next wave of technological transformation.
Ultimately, the technology sector’s approach to managing AI’s environmental impact will shape not just their own sustainability goals, but also the global fight against climate change. The paradox at the heart of the AI boom—immense energy demands paired with unprecedented efficiency potential—means that every watt, every innovation, and every investment decision matters more than ever. As the world barrels toward an AI-powered future, the question remains: can the industry outpace its own growing footprint and help lead the way to a truly sustainable digital age?
With the world watching and the climate clock ticking, the answer may well define the next era of both technology and environmental stewardship.
