Data Centers Will Increase Their Electricity Consumption by 26% in 2026

Artificial intelligence is no longer just pressuring chip manufacturers, cloud providers, or infrastructure teams. It is also transforming global energy planning. Gartner predicts that the worldwide electricity consumption of data centers will reach 565 TWh in 2026, a 26.4% increase from the estimated 447 TWh for 2025. This figure confirms that computing capacity is becoming an electrical issue before an IT concern.

This data matters because it signals a phase shift. For years, data center growth could be managed through efficiency improvements, server consolidation, virtualization, and renewable energy contracts. Generative AI has disrupted some of that balance. AI-optimized servers consume significantly more power, require more advanced cooling, and increase rack density to levels that many traditional data centers cannot accommodate.

Gartner also estimates that the global power demand of data centers will rise from 104 GW in 2025 to 132 GW in 2026, a 27% increase. By 2030, the firm forecasts demand will reach 290 GW. The core message is clear: energy availability will be one of the key factors determining who can scale AI services and who will be waiting for permits, grid connections, or new generation capacity.

AI now almost weighs as much as traditional servers

The most significant part of the report lies in the distribution of power consumption. Conventional servers will continue growing, but at a very moderate pace. Gartner projects an increase from 193 TWh in 2025 to 195 TWh in 2026, and 200 TWh in 2027. The larger jump comes from AI-optimized servers, which will go from 95 TWh in 2025 to 175 TWh in 2026, and 258 TWh in 2027.

This leap means that by 2027, the electricity used by AI servers will surpass that of conventional servers. It’s a symbolic milestone but also a practical one. Data centers are being redesigned around training loads, inference, language models, AI agents, and systems with GPUs or specialized accelerators.

Cooling and supporting infrastructure also see strong growth. According to Gartner, this segment will rise from 159 TWh in 2025 to 195 TWh in 2026 and 243 TWh in 2027. The data shows that it’s not enough to just look at GPUs. Every new AI cluster demands power distribution, liquid or hybrid cooling, backup systems, power conversion, pumping, security, internal networking, and thermal management.

In practice, AI electricity consumption is distributed between hardware that performs computations and all the supporting systems that keep that hardware operational without interruptions. Therefore, many data center investments now focus on total electrical capacity, grid access, power purchase agreements, on-site generation, water supply, or alternative cooling systems, beyond just IT megawatts.

Electricity now becoming the new bottleneck

The most critical insight from Gartner isn’t the TWh figures, but the idea that AI capacity is beginning to be constrained by energy availability. Until recently, the visible bottleneck was GPUs. Now, many regions are realizing that having capital and chips isn’t enough if there’s no contracted electric power, available substations, or permissions to expand the grid.

This shift affects all users of data centers, not just large AI labs. If hyperscalers, cloud providers, and big platforms absorb all available capacity, companies needing colocation, private cloud, managed services, or regional infrastructure may face higher prices, longer lead times, and fewer location options.

The International Energy Agency also warns that data center electricity consumption could double by 2030, reaching around 945 TWh in its baseline scenario. Gartner’s estimate is even more aggressive, projecting over 1,200 TWh for 2030. While these projections differ, they all point to the same core message: digital infrastructure is shifting from a marginal consumer to a key actor within the electrical system.

In the US, this pressure is already evident in regions with high data center densities. In Europe, the European Commission has begun drafting minimum energy efficiency standards and labeling schemes for data centers, focusing on water use, clean electricity, and operational efficiency. Regulations are not accidental; expanding AI may clash with climate goals, aging electrical grids, and strained energy markets.

What operators and companies should do

For data center operators, ensuring energy supply will become a top priority—even before finalizing all commercial contracts. The decision of where to locate a campus will no longer rely solely on connectivity, tax benefits, or proximity to clients. Power grid capacity, connection speed, renewable availability, power purchase agreements, efficient cooling options, and social acceptance will also be critical factors.

Gartner recommends infrastructure and operations leaders prioritize efficiency improvements, secure grid access, invest in high-efficiency cooling, and explore edge architectures to reduce some of the pressure on large centralized campuses. Not all AI workloads need to run in the same type of facility or at the same density levels.

For user companies, the lesson is pragmatic. AI won’t be just a line item in the budget. It will entail energy costs, cloud costs, inference costs, storage expenses, and governance. Before deploying agents, internal assistants, or automation at scale, it’s wise to understand where they run, how much they consume, which provider supports the load, and what guarantees exist regarding continuity and price.

Software efficiency will also need improvement. Smaller models, quantization, cache reuse, inference planning, appropriate hardware selection, and reducing unnecessary calls can have direct economic impacts. In a limited energy scenario, optimization will shift from being a technical preference to a financial necessity.

The race for artificial intelligence is entering a less visible but more decisive phase. Headlines will continue talking about models, agents, and new chips. However, the more fundamental question increasingly shaping the market is where everything is plugged in. If Gartner is correct, 2026 will be the year when data center electricity consumption stops being a concern for specialists and becomes a strategic decision for any AI-dependent business.

Frequently Asked Questions

How much will data center electricity consumption grow in 2026?

Gartner predicts that global data center electricity consumption will reach 565 TWh in 2026, a 26.4% increase from the estimated 447 TWh in 2025.

How much power will data centers demand in 2026?

Global power demand is expected to grow from 104 GW in 2025 to 132 GW in 2026, according to Gartner. By 2030, it could reach 290 GW.

When will AI servers surpass conventional servers?

Gartner estimates that AI-optimized servers will surpass conventional servers in electricity consumption by 2027.

Why is AI’s electricity consumption such a concern?

Because energy availability could limit new data centers, increase costs for cloud capacity, and delay AI projects. It also puts additional strain on electrical grids, cooling systems, sustainability efforts, and energy planning.

via: gartner