According to the International Energy Agency, energy consumption in data centers is expected to double by 2026, with much of this driven by AI’s extensive need for computational power.

But here’s the paradox: AI is currently causing the global energy footprint to grow, but it also holds the key to cutting it down. The question is, can AI and sustainability truly co-exist?

The AI conundrum

AI is fueling breakthroughs across sectors, from real-time language translation to advanced medical diagnostics, but this comes at a price. AI workloads are extremely resource-intensive, requiring data centers to ramp up their storage, processing, and power capacities.

For example, AI queries demand approximately ten times the electricity of traditional Google searches, with a single ChatGPT request consuming up to 2.9 watt-hours of power. Large hyperscale data centers, needed to accommodate the AI boom, demand more than 100 megawatts, with an annual electricity consumption equivalent to the electricity demand from around 350,000 to 400,000 electric cars.

To handle such high demands, data centers rely on advanced hardware, which in turn requires extensive cooling solutions to prevent overheating. These cooling systems — typically powered by electricity — are crucial but also add considerably to the energy footprint of data centers.

As AI models grow larger and more complex, they create an escalating need for infrastructure that consumes even more power, pushing energy demands to unprecedented levels.

Yet, in a peculiar twist, AI is also being called on as the solution to this very crisis. Data centers have turned to AI-powered cooling systems, using algorithms that adjust temperature and airflow based on real-time data to reduce cooling costs and cut down emissions.

Advancing AI for global sustainability goals

It’s not enough for AI to make data centers efficient — it needs to help data centers align with broader sustainability targets set by global initiatives. Countries worldwide are setting rigorous carbon reduction targets, and data centers, as heavy energy consumers, are squarely in the spotlight.

Take AI-driven predictive analytics, for example. AI systems can track energy efficiency in real time, automatically adjusting processes to prevent waste. They also identify hotspots and areas where air cooling is inefficient, creating intelligent cooling systems.

AI’s ability to distinguish between, and choose the optimum, energy sources is also invaluable as data centers incorporate renewable energy into their power mix. With wind, solar, and hydro energy production fluctuating based on weather and time, AI algorithms can predict energy generation patterns and adjust consumption accordingly.

This flexibility enables data centers to draw more energy from green sources when they are abundant, minimizing reliance on carbon-intensive alternatives.

Through advanced data modeling, AI can also optimize the design and layout of server farms, ensuring that equipment operates within ideal energy efficiency parameters. By analyzing usage patterns, AI makes it possible for data centers to plan ahead, reducing unnecessary system redundancies, and ensuring that infrastructure remains lean without compromising service reliability.

These advancements don’t just optimize operations; they enable data centers to actively contribute to global climate goals and reduce their carbon footprint in real, measurable ways.

The EU’s rating system

The European Union's new reporting program for data centers, embedded in the European Energy Efficiency Directive (EEED), represents a bold and necessary step toward addressing the escalating energy demands of the digital economy.

Under this framework, data centers with an IT power demand greater than 500 kW are now required to track and disclose their energy consumption, renewable energy use, water and waste heat management, PUE, and other critical performance indicators.

However, regulatory compliance alone will not be enough to meet the EU’s ambitious sustainability targets. Data centers are under pressure to not only track their performance, but to continuously improve it. This is where AI steps in. With AI, data centers can go beyond static compliance to build dynamic, adaptive systems that continuously optimize every aspect of their operation.

True sustainability with AI

AI has unquestionably opened the door to new efficiencies, smarter infrastructure, and real-time environmental monitoring. But as the technology advances, the real test lies in how effectively it can transform data centers from huge energy consumers to champions of sustainable practices.

AI-driven systems that predict, adapt, and optimize data center resources are leading the way, showing that it’s possible to meet the world’s growing demand for data while working towards a greener future. The next challenge is whether these advancements can scale fast enough to keep pace with AI’s explosive growth and truly make data centers part of the solution, rather than part of the problem.