TLDR: The burgeoning growth of artificial intelligence is dramatically escalating energy demands on data centers, pushing the industry to aggressively pursue energy-saving solutions and sustainable power sources. Projections indicate a significant increase in electricity consumption and infrastructure investment over the coming years, with AI workloads becoming a dominant factor.
The relentless expansion of artificial intelligence (AI) is creating an unprecedented surge in electricity demand, compelling data centers worldwide to embark on an urgent quest for energy-saving solutions and sustainable power infrastructure. As AI models become more sophisticated and widely adopted, the energy footprint of the digital world is growing at an alarming rate, posing significant challenges for existing power grids and climate-neutrality ambitions.
According to Deloitte, while data centers are projected to account for approximately 2% of global electricity consumption, or 536 terawatt-hours (TWh), in 2025, the power-intensive nature of generative AI training and inference could nearly double this figure to 1,065 TWh by 2030. If anticipated improvements in AI and data center processing efficiency do not materialize, this consumption could even exceed 1,300 TWh. Critical power to support data center components like GPUs, CPUs, storage, cooling, and networking is expected to almost double between 2023 and 2026, reaching 96 gigawatts (GW) globally, with AI operations potentially consuming over 40% of that power. Worldwide, AI data centers’ annual power consumption is expected to reach 90 TWh by 2026, a tenfold increase from 2022 levels.
The US Energy Information Administration and Goldman Sachs forecast record-high energy demand in the US for 2025 and 2026, driven significantly by data centers supporting AI and cryptocurrency. US power consumption is expected to hit 4,179 billion kWh in 2025 and 4,239 billion kWh in 2026. Globally, Goldman Sachs predicts data center power demand will increase by 50% by 2027, potentially rising by as much as 165% by the end of the decade compared to 2023. By 2027, analysts project power demand to reach 84 GW, with AI-driven workloads accounting for 27% of the market.
This escalating demand necessitates substantial investment in grid upgrades, with Goldman Sachs estimating approximately $720 billion will be needed through 2030. The industry is responding by focusing on a combination of innovative and energy-efficient data center technologies and a shift towards more carbon-free energy sources. Companies are exploring advanced cooling systems, optimizing server resources, and integrating Battery Energy Storage Systems (BESS) into data centers to stabilize renewable energy sources like wind and solar.
Collaboration between utilities and data centers is also expanding, leveraging AI to optimize power profiles and manage off-grid operations using backup sources. Schneider Electric highlights that data center operators are shifting focus towards accelerated computing capacity tailored for AI requirements, underscoring the need for expanded infrastructure and efficient power and cooling solutions.
Major players like OpenAI are at the forefront of this infrastructure build-out. OpenAI CEO Sam Altman stated, “AI can only fulfill its promise if we build the compute to power it. That compute is the key to ensuring everyone can benefit from AI and to unlocking future breakthroughs.” OpenAI, in partnership with Oracle and SoftBank, plans to establish five new data center sites in Texas, New Mexico, Ohio, and a yet-to-be-announced Midwest location as part of its “Stargate project.” This massive undertaking is expected to involve 10 gigawatts of computing power and cost $500 billion, with current announcements bringing the project to almost 7 gigawatts of capacity and over $400 billion in the next three years.
The financial sector is also taking note, with companies like EMCOR Group, Inc. (EME) benefiting directly from the AI hyperscale data center spending boom and the massive energy and infrastructure growth required to support it. Zacks.com reported on September 26, 2025, that AI hyperscalers are projected to spend roughly $400 billion in capital expenditure in 2025 alone, with global data center infrastructure spending set to hit $7 trillion by 2030. Large AI data centers can consume as much electricity as a midsize city, contributing to a projected 75% growth in U.S. electricity demand by 2050. This necessitates doubling transmission capacity and quadrupling nuclear capacity over the next 25 years, alongside expanding natural gas, solar, and other sources.
Also Read:
- Stargate Initiative Expands with Five New AI Data Centers Across U.S.
- Generative AI Fuels Explosive Data Centre Expansion Across Africa
The drive for energy efficiency is not just about meeting demand but also about environmental responsibility. Data centers are actively seeking ways to reduce their environmental footprint, making sustainable energy solutions a critical component of their future strategies.
