Data Centers are the focus of increased scrutiny and renewed interest as more and more power consumption and resource statistics show eye-popping figures.
A significant aspect of energy consumption is dedicated to data center cooling systems, which are crucial for maintaining optimal operating temperatures and preventing hardware failure. Current estimates suggest that data centers account for 3% of global electricity consumption, with predictions indicating a rise to a potential 10% by 2030.
Furthermore, the electricity used to maintain data centers is generated from irreplaceable fossil fuels and is directly contributing to carbon dioxide and greenhouse gases.
Additionally, a predominant method, water-based cooling, utilizes vast amounts of water, putting undue pressure on local water sources.
OpenAI’s AI ChatGPT relies heavily on water, with estimates suggesting it uses up to 500 milliliters of water for a series of five to 50 prompts.
The Global Data Center Market achieved a valuation of $196.9 Billion in 2023. It is projected to exhibit steady growth, reaching $464.6 Billion by 2032, with a compound annual growth rate (CAGR) of 10.30% during the forecast period (2024–2032). However, resolving security, operational efficiency, and environmental impact issues will be critical to continuing this growth trajectory, reports Straits Research.
Here, experts in the field offer their predictions for what 2025 holds for data centers:
Designing data centers with resiliency at the core: Considering the high-power requirements of AI and GPU clusters, everything is now larger and denser, which introduces new challenges to designing “the modern data center.” Facilities and campuses over the next 5-10 years will need significant upsizing, from 100-300 megawatts for most hyperscale campuses today to the gigawatt level corresponding with 1M+ projected GPU clusters. 2025 will be the year developers more broadly advance on planning for designs that meet those requirements.
Nonetheless, AI data centers must still be designed with uptime in mind to ensure GPUs don’t suffer outages at the wrong time, mid-training or during an inference call. While some degree of failure is expected in large GPU clusters, that is at the hardware level. A data center outage has the potential to be catastrophic and damage very expensive GPUs in a thermal runaway event.
The largest AI and cloud companies still provide their services with underlying always-on service level agreements which flow through to the data center providers supporting them. New data center entrants, predominantly from the crypto mining sector, appear to be developing data centers faster, yet with lower resiliency—making them a risky match for AI and cloud deployments.
While data center investment is an increasingly smaller proportion of overall infrastructure spending over time (as related to hardware/networking for GPUs), building to lower resiliency is like putting low octane gasoline in a high-performance sports car—it may work in a pinch, but runs the risk of killing the engine eventually.—Tom Traugott, SVP of strategy at EdgeCore Digital Infrastructure
Power constraints will drive regional shifts in data center locations: As major tech hubs like Virginia and Texas reach their energy capacity limits, the demand for large-scale data analytics, quantum computing, and AI will prompt a shift in where new data centers are built. Regions with untapped power reserves, like parts of the Midwest, will emerge as prime locations for future data center development. This geographic shift will influence where technology companies expand as they seek proximity to available energy sources and where computing occurs. Additionally, companies will form strategic partnerships with regional utilities to secure long-term energy contracts, leading to a new wave of investment in energy infrastructure specifically designed to support the growing power needs of new technologies. This shift could also incentivize regions to focus on developing renewable energy sources to attract companies in other high-tech categories.—Ocient CEO Chris Gladwin
Greater adoption of hybrid cloud failover clustering: Enterprises will increasingly implement hybrid cloud architectures, combining on-premises data centers with public cloud platforms for failover clustering. This setup will ensure high availability and disaster recovery while offering flexibility and cost-effectiveness. Organizations will prioritize failover solutions that seamlessly bridge on-prem and cloud environments, allowing IT teams to leverage the cloud's resilience without abandoning existing infrastructure.—Cassius Rhue, VP of customer experience, SIOS Technology
Nuclear-powered AI data centers offer a sustainable future: As AI models grow in complexity and scale, the demand for computing power and energy consumption will soar. Nuclear energy, a clean and reliable source of power, will emerge as a critical solution to power AI data centers. This will not only address the energy needs of AI but also reduce carbon emissions and contribute to a sustainable future. Nuclear-powered AI data centers will help us maintain uninterrupted operation of AI data centers, and will be able to scale to meet the needs of large-scale AI infrastructure.—LogicMonitor’s general manager of AI, Karthik Sj
Maximizing GPU utilization becomes the new standard: In 2025, as the size of AI model training datasets continue to grow exponentially, maximizing GPU utilization will become the primary design goal for modern data centers. Organizations will face mounting pressure to optimize their expensive GPU infrastructure investments. This shift will drive innovations in hardware and software design to sustain the massive read bandwidths necessary for training and minimize checkpoint-saving times that cause training pauses. Success will be measured by how effectively data centers can keep their GPU resources busy while managing larger model checkpoints and growing data requirements.—Haoyuan Li, founder and CEO, Alluxio