Gartner’s New Forecast Reveals AI’s Energy Challenge
Artificial intelligence is pushing data centres into a new phase of growth. But behind the rapid expansion of AI workloads, a major challenge is emerging: electricity. According to the Gartner data centre electricity forecast, global data centre electricity consumption is expected to grow 26% in 2026, reaching 565 terawatt hours (TWh), up from 447 TWh in 2025.
The shift highlights how AI adoption is changing the way enterprises think about infrastructure. Computing power is increasing, but energy availability is becoming a key factor in scaling future AI environments.
AI workloads become the biggest driver of power demand
Gartner points to compute-intensive AI workloads as the main reason behind rising data centre electricity consumption. Global data centre power demand is expected to increase 27% in 2026, reaching 132 gigawatts (GW), compared with 104GW in 2025. By 2030, this demand is projected to reach 290GW.
The growing use of AI-optimised servers is playing a major role. Gartner estimates these servers will account for 31% of data centre power consumption in 2026, and their electricity usage is expected to surpass traditional servers by 2027. This shift shows how AI infrastructure is changing the balance inside modern data centres.
Power availability becomes a new infrastructure challenge
As AI systems require more processing capacity, energy access is becoming a bigger concern for data centre operators. Gartner estimates data centre electricity consumption could cross 1,200TWh by 2030, creating pressure on existing power availability.
For infrastructure and operations leaders, the focus is moving beyond simply adding computing capacity. Efficiency improvements, better resource planning, and stronger power management are becoming critical parts of future data centre strategies.
Cooling and efficiency take centre stage
Higher power usage also increases the need for better thermal management. High-efficiency data centre liquid cooling upgrades and other cooling improvements are becoming important considerations as workloads become more demanding.
Along with cooling, enterprises are expected to focus on smarter infrastructure decisions, including edge computing and optimised workloads, to manage growing AI requirements.
Enterprises prepare for an energy-driven AI future
The Gartner data centre electricity forecast reflects a major shift in the technology landscape. AI growth is creating new opportunities, but it is also bringing a new infrastructure challenge — managing power at scale.
As AI-optimised server electricity demand continues to grow, enterprises will need to balance performance, efficiency, and sustainability. The next phase of AI expansion may depend not only on computing capability, but also on how effectively organisations manage the energy behind it.
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