The Global Data Center Boom in the AI Era: Energy, Water, and Powering the Cloud

Overview

The B1M examines a rapid global build-out of data centers driven by AI and cloud services, highlighting where centers cluster, how much power and water they consume, and the pressures they create on utilities and communities.

• The world now hosts over 11,000 data centers in 174 countries, with the USA home to a third and Virginia leading regional clusters.
• Data centers are a major energy sink, with projections showing growth that could outpace national scales and increase electricity demand significantly by 2030.
• Cooling and water supply become critical constraints, pushing firms to explore liquid cooling and other water-smart approaches.

Read on for a deeper dive into where these centers are, what they consume, and the options being explored to keep the lights on and the data flowing.

Overview: The data center boom in the AI era

The B1M outlines one of the fastest building booms the world has ever seen in data centers, describing a global construction frenzy tied to the meteoric rise of AI and the digital economy. The video emphasizes that humanity is increasingly dependent on large-scale data centers, which are growing in number and size as AI models become more capable and more widely deployed. It also flags the environmental and community costs of this expansion, including power and water demands and the pushback from nearby residents and policymakers.

Global footprint and regional clustering

The data center ecosystem is now truly global, with more than 11,000 facilities spread across 174 countries. A little over a third are in the United States, with prominent clusters in Texas and California. Virginia emerges as the state with the most centers, illustrating how data centers cluster around power networks and climate conditions. The UK and Germany also feature prominently in Europe, while other regions show more dispersed distribution. This footprint is essential to maintain the functionality of modern life, from shopping and banking to video communication and social media, but it also concentrates demand in specific places that must be able to support it.

Energy and water demands: the scale of the challenge

The video notes that the data center industry could account for roughly 3 to 4 percent of global electricity consumption, a staggering figure given the scale of data-driven activity. With AI driving much of the recent growth, the demand has accelerated further, pressing grids and water systems to keep up. The capacity installed globally now exceeds 122 gigawatts, a figure the B1M uses to illustrate just how large data-center power needs are in comparison with major energy projects like the UK’s Hinkley Point C reactor.

As AI systems process billions of prompts daily, the energy and water required to support these operations grow rapidly. AI contributed a notable share of center electricity usage by 2024, with potential for AI to dominate a larger fraction in subsequent years, highlighting the tension between digital growth and infrastructure limits.

"Without data centers, there'd be no doom scrolling, no long video calls that really could have been an email or memes that just refused to die." - The B1M

Cooling, water, and the technology mix

Cooling is a central design consideration for data centers. Traditional air cooling is effective but energy-intensive, especially when scaled to megaproject-level facilities. Liquid cooling is becoming more common in the AI era, offering energy and space advantages but increasing the demand for reliable water supply. This creates a tension with public water systems that are often already stressed, particularly in the US where many systems have limited surplus capacity to support industrial-scale users.

Mitigation, innovation, and the path forward

To address these pressures, the industry is pursuing a mix of strategies, including better cooling methods, investments in on-site renewables, and grid upgrades so that data centers do not drive up energy bills for surrounding communities. Some firms are even exploring more radical approaches like underground data centers or partnerships with nuclear providers using low-carbon energy sources, including nuclear fusion and small modular reactors. While these options are not viable for every company, they illustrate the breadth of potential pathways to meet AI-driven demand while reducing environmental impact.

Software tools and digital twin technology are positioned to help hyperscalers plan and operate more efficiently. Companies like IES provide simulation and optimization services that can model dynamic IT loads, rack layouts, and cooling configurations within local climate contexts, helping to de-risk infrastructure decisions and reduce energy, carbon, and water use. White papers and case studies are framed as resources to help operators design AI-ready, future-proof facilities that align with evolving regulatory and grid-connection requirements.

Community impact and social considerations

As data centers proliferate, concerns about water stress, electricity bills, and noise or pollution have grown in some locales. The Virginia example—nicknamed Data Center Alley—highlights how local opposition can lead to project cancellations. The video emphasizes that community engagement and proactive planning are essential to managing these concerns and that balancing the benefits of digital growth with public health and environmental considerations remains a central governance challenge.

"the recent media focus on the negative effects of water use in particular has actually been a bit overblown because it's not a major issue everywhere." - Shauli

Conclusion: shaping the future of data center infrastructure

Looking ahead, data centers are set to become even larger and more widespread, driven by the AI-driven era. The challenge will be to implement changes that improve efficiency, reduce environmental impact, and maintain reliability while continuing to support the digital services that societies rely on. The video closes by pointing to the IES white paper as a resource for understanding how dynamic simulation can enhance CFD modeling and drive energy and water efficiencies in AI-enabled facilities, underscoring the role of advanced design tools in this transition.

"If there's enough available to spare, it's still the best way to tackle that all important cooling problem." - Shauli