Cadence Asks: Does Sustainable AI Need Greener Data Centres?

As AI grows more powerful and embedded in everyday operations, data centres sit at the core of this shift, enabling the computational strength needed to train and deploy large-scale models.

But this power comes at an environmental cost.

Cadence’s 'Data Center Evolution: The Innovation Imperative' report underlines how energy demand, waste heat and carbon footprints are forcing leaders to rethink infrastructure.

With 80% of decision-makers worried about their data centres’ environmental impact, the industry is reaching a critical point. Cadence’s report, which gathers insights from 400 IT, facility and business leaders across the globe, paints a clear picture: data centres must innovate or fall behind.

A tipping point for sustainable data centres

The energy hunger of data centres is no secret.

High-performance computing used in AI training and deployment consumes vast electricity, not just for processing, but for cooling the machinery that makes AI possible.

This translates into massive environmental consequences.

The growing strain on power infrastructure highlights the need for energy-efficient data centre designs and a shift towards renewables.

Yet, despite the urgency, many operators hesitate. Overprovisioning remains widespread, with 60% of decision-makers admitting to it, usually out of fear of outages.

This wasteful practice directly contradicts sustainability goals.

Still, there are steps in the right direction.

Cadence reports that 63% of respondents already use renewable energy, while 19% plan to follow suit.

Confidence is strong too—84% say they believe their organisations can successfully integrate renewables. But 9% remain resistant, citing concerns about reliability and the limitations of local grids.

One path forward lies in reusing waste heat, a practice already adopted by 40% of data centres surveyed, with another 26% planning to adopt it within a year.

Dave King, Product Engineering Architect at Cadence, explains: “The emphasis on this is unsurprising as the importance of energy efficiency is paramount:

“Every site operates within a fixed power budget. By improving infrastructure efficiency – in other words, enabling greater processing capability without increasing power consumption – more energy can be allocated to compute tasks.

"This allows the data centre to deliver improved performance and value, creating a competitive advantage. Greater efficiency also means improved sustainability, which is increasingly important given environmental concerns and regulatory pressures.”

AI’s power problem meets the UK’s clean energy vision

The UK Government is responding to the AI energy challenge by establishing the AI Energy Council, which met for the first time on 8 April.

Bringing together representatives from EDF, NESO, Ofgem, National Grid, Scottish Power and technology leaders like Google, Amazon, Microsoft and ARM, the Council aims to tackle how AI growth and clean energy strategies can align.

Peter Kyle, Secretary of State for Science, Innovation and Technology, says: “The work of the AI Energy Council will ensure we aren’t just powering our AI needs to deliver new waves of opportunity in all parts of the country, but can do so in a way which is responsible and sustainable.

“This requires a broad range of expertise from industry and regulators as we fire up the UK’s economic engine to make it fit for the age of AI – meaning we can deliver the growth which is the beating heart of our Plan for Change.”

The Council’s formation signals a coordinated effort to ensure energy infrastructure evolves alongside the digital economy.

AI’s transformative effect on industries demands sustainable energy policies and robust grid connections.

Ed Miliband, Secretary of State for Energy Security and Net Zero, adds: “We are making the UK a clean energy superpower, building the homegrown energy this country needs to protect consumers and businesses, and drive economic growth, as part of our Plan for Change.

“AI can play an important role in building a new era of clean electricity for our country and as we unlock AI’s potential, this Council will help secure a sustainable scale up to benefit businesses and communities across the UK.”

Innovation, risk and regional adaptation

Sustainability isn’t the only catalyst pushing data centres to innovate.

With AI workloads scaling fast and regulations tightening, modernisation is an essential tactic.

But barriers remain. Complexity, cost and lack of expertise often stall adoption.

Still, Cadence’s findings suggest progress is being made, with 86% of leaders agreeing that a failure to innovate poses serious or moderate consequences. Their top fears? Falling behind competitors (37%), financial loss (30%), and inability to meet AI demands (27%).

Encouragingly, 60% of respondents feel more confident in using innovative technologies than they did 12 months ago. In South America, that number rises to 68%.

Aitor Zabalegui, Senior Principal Application Engineer at Cadence, shares insights into this regional confidence: “Past adoption trends can also shed light on why those working with facilities in South America have become markedly more confident in their innovation capabilities over the past year. Consider the fact that some parts of the world skipped straight to wireless technology, rather than going through the infrastructure that paved the way for it, such as power lines.

“In the same way, certain regions have been able to jump straight into certain data center innovations, rather than going through all the innovative steps. This is because they have seen others navigate these over the past few years to reach a desirable end goal and been able to take on these learnings and quickly jump to the more advanced stages of adoption.”

The report recommends that organisations focus on technologies that match their operational requirements. Success hinges on a mix of collaboration, sustainability, data-driven decisions and infrastructure investment.

Data centres that fail to meet the AI era’s performance expectations or ignore environmental realities risk obsolescence.

Those who act boldly can reap both environmental and commercial rewards.

As AI advances, the relationship between technology and the planet must be rebalanced.

Energy-efficient innovation is not optional—it’s foundational.

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