Cadence Urges Tech Leaders to Push Data Centre Innovation

AI technology continues to reshape industries at a remarkable pace, but behind every AI breakthrough lies the immense infrastructure of data centres.

These facilities power the training and deployment of AI models, yet also draw vast amounts of electricity and pose considerable environmental challenges.

This issue is becoming harder to ignore.

Cadence, a global software company, has released its report, Data Center Evolution: The Innovation Imperative, offering a data-led perspective on how organisations must transform their digital infrastructure.

Based on feedback from 400 IT, facilities and business leaders around the world, the study explores the current barriers to sustainable innovation in data centres and how the industry can respond.

Data centre impact and the energy crisis

Cadence highlights a crucial tension: 80% of data centre decision-makers are concerned about the environmental impact of their operations, yet many still rely on outdated methods.

One such practice is overprovisioning — providing more computing resources than necessary — which remains in place for 60% of organisations. This happens largely out of fear of service outages but leads to wasted energy and resources.

AI, by its nature, requires high-performance computing for model training and inference.

This makes data centres indispensable to AI progress, but also intensifies energy use for both processing and cooling.

As 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.”

Cooling, in particular, is a major contributor to energy demand.

However, alternative approaches are starting to make their way into operations.

Waste heat reuse is a notable example, already adopted by 40% of respondents and on the radar for another 26% planning to implement the method within the next year.

Dave King, Product Engineering Architect at Cadence, underscores the importance of infrastructure efficiency.

“Every site operates within a fixed power budget,” he explains.

“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.”

UK’s AI Energy Council and clean power strategy

These concerns have been echoed at the highest levels of UK government.

On 8 April, leaders from the country’s technology and energy sectors gathered for the inaugural meeting of the UK’s AI Energy Council.

The meeting focused on aligning AI development with energy sustainability and explored how infrastructure investments can enhance economic growth.

Representatives from power providers such as EDF, NESO, National Grid and Scottish Power joined forces with tech giants including Google, Amazon, Microsoft and ARM.

Together, they examined how clean energy and AI can work in tandem.

Ed Miliband, Secretary of State for Energy Security and Net Zero, reinforced the UK’s ambitions: “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.”

The government’s plans include the expansion of clean power infrastructure to reduce connection delays and ensure data centres can access renewable energy sources.

This move toward clean electricity is designed to enable AI technologies to flourish without exacerbating carbon emissions.

Innovation as a survival strategy

Innovation is becoming not just a competitive edge but a necessity.

Cadence reports that 86% of respondents believe failing to adopt new technologies will bring serious or moderate consequences.

The top risks include falling behind competitors, 37%, financial losses at 30% and an inability to meet growing AI demands, scoring 27%.

Encouragingly, organisations are becoming more confident in their ability to use advanced technologies. Six in 10 respondents report increased confidence over the past year, rising to 68% in South America.

Aitor Zabalegui, Senior Principal Application Engineer at Cadence, explains that this regional variation stems from adoption patterns.

“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,” he says.

“In the same way, certain regions have been able to jump straight into certain data centre 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.”

Technology leaders are also optimistic about integrating renewable energy into their operations.

According to Cadence, 63% already use renewable energy sources in their data centres, with another 19% planning to do so.

A substantial 84% feel confident in their organisation’s ability to incorporate renewables. Still, a small portion, 9%, remains opposed, often citing local grid issues or perceived reliability concerns.

Cadence’s findings suggest a broader cultural and operational shift is needed.

Leaders must foster better collaboration between IT, sustainability and business functions to ensure their data centre strategies are fit for AI.

This means not only adopting new technologies but investing in infrastructure and redesigning operations around energy efficiency.

Cadence concludes that change requires leadership and tailored solutions.

Decision-makers should focus on technologies and innovations that serve their unique operational goals, rather than adopting one-size-fits-all strategies.

This focus on customisation and integration can improve progress while reducing environmental impact.

As governments and businesses align on clean energy and digital transformation, the path forward is clear: innovation, efficiency and sustainability must work hand-in-hand if data centres are to support the AI revolution without exhausting our planet’s resources.

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