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Global electricity consumption by data centres is expected to grow 26% in 2026 as artificial intelligence workloads fuel unprecedented demand for computing infrastructure, according to new forecasts from Gartner.
The research firm expects data centres worldwide to consume 565 terawatt hours (TWh) of electricity in 2026, up from 447 TWh in 2025, highlighting the growing energy footprint of the AI industry.
According to Linglan Wang, power availability is emerging as one of the biggest constraints on AI expansion.
"Surging demand for compute-intensive AI workloads is driving unprecedented data center power growth, while AI capacity is now constrained by power availability, making data center power security the new battleground for scaling and protecting margins in the global AI race," Wang said.
The report projects worldwide data centre power demand to rise from 104 gigawatts (GW) in 2025 to 132 GW in 2026, before more than doubling to 290 GW by 2030 as enterprises and hyperscalers expand AI infrastructure.
AI-optimized servers are expected to account for an increasingly larger share of electricity consumption. Gartner estimates these systems will consume 175 TWh in 2026, an 84% increase from 95 TWh in 2025, representing nearly one-third of total data centre power usage.
By comparison, electricity consumption from conventional servers is forecast to remain relatively flat, increasing only from 193 TWh to 195 TWh over the same period.
Cooling systems and supporting infrastructure are also becoming significant power consumers. Gartner expects electricity use for cooling and related infrastructure to increase 23% to 195 TWh in 2026, reflecting the higher thermal requirements of AI clusters.
The findings underscore how the rapid adoption of generative AI is reshaping infrastructure priorities across the technology industry. While much of the focus has been on AI chips and data centres, access to reliable power is increasingly becoming a critical competitive advantage.
Gartner estimates total data centre electricity consumption could exceed 1,200 TWh by 2030, raising concerns that existing power grids may struggle to support future AI infrastructure expansion.
The research firm said infrastructure and operations leaders should prioritize energy efficiency upgrades, secure long-term grid access and invest in advanced cooling technologies to manage growing power requirements.
It also recommended greater adoption of edge computing architectures to reduce pressure on centralized data centres and improve the sustainability of AI deployments.
The forecast highlights a broader shift in the AI economy, where access to electricity is becoming as strategically important as access to chips, capital and talent. As enterprises and hyperscalers race to deploy larger AI models and agentic workloads, power availability is increasingly shaping where and how next-generation data centres are built.
The research firm expects data centres worldwide to consume 565 terawatt hours (TWh) of electricity in 2026, up from 447 TWh in 2025, highlighting the growing energy footprint of the AI industry.
According to Linglan Wang, power availability is emerging as one of the biggest constraints on AI expansion.
"Surging demand for compute-intensive AI workloads is driving unprecedented data center power growth, while AI capacity is now constrained by power availability, making data center power security the new battleground for scaling and protecting margins in the global AI race," Wang said.
The report projects worldwide data centre power demand to rise from 104 gigawatts (GW) in 2025 to 132 GW in 2026, before more than doubling to 290 GW by 2030 as enterprises and hyperscalers expand AI infrastructure.
AI-optimized servers are expected to account for an increasingly larger share of electricity consumption. Gartner estimates these systems will consume 175 TWh in 2026, an 84% increase from 95 TWh in 2025, representing nearly one-third of total data centre power usage.
By comparison, electricity consumption from conventional servers is forecast to remain relatively flat, increasing only from 193 TWh to 195 TWh over the same period.
Cooling systems and supporting infrastructure are also becoming significant power consumers. Gartner expects electricity use for cooling and related infrastructure to increase 23% to 195 TWh in 2026, reflecting the higher thermal requirements of AI clusters.
The findings underscore how the rapid adoption of generative AI is reshaping infrastructure priorities across the technology industry. While much of the focus has been on AI chips and data centres, access to reliable power is increasingly becoming a critical competitive advantage.
Gartner estimates total data centre electricity consumption could exceed 1,200 TWh by 2030, raising concerns that existing power grids may struggle to support future AI infrastructure expansion.
The research firm said infrastructure and operations leaders should prioritize energy efficiency upgrades, secure long-term grid access and invest in advanced cooling technologies to manage growing power requirements.
It also recommended greater adoption of edge computing architectures to reduce pressure on centralized data centres and improve the sustainability of AI deployments.
The forecast highlights a broader shift in the AI economy, where access to electricity is becoming as strategically important as access to chips, capital and talent. As enterprises and hyperscalers race to deploy larger AI models and agentic workloads, power availability is increasingly shaping where and how next-generation data centres are built.
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