Global data center energy use will more than double by 2030, but announced capacity is not a reliable guide to future growth. Power constraints, commercial realities and inference efficiency will shape how much capacity is ultimately built.
Location changes the carbon of AI inference by hundreds of times but its cost varies by only about 15%. Where latency and sovereignty allow, siting workloads on cleaner grids can cut emissions at little or no additional cost.
The European Commission has presented its final EED rating label for data centers, introducing significant changes related to energy consumption, water usage and waste heat reuse.
Unclear goals and mismatched expectations can undermine DCIM projects if not addressed early. This report provides a roadmap of questions and considerations for buyers and suppliers to align, not just at the outset, but for the long-term.
Meta's decision to give away its latest large language model challenges the narrative around AI infrastructure.
This report highlights results from vendor and product supplier respondents to the Uptime Institute Global Data Center Survey 2026 and provides an insight into the spending strategies, technology adoption and other issues facing their customers.
Drones can be used to surveil or potentially attack data centers, but operators have limited options to respond. Aviation and airspace regulations restrict intervention, even when drones are flying over a facility.
The US state of Virginia has retained its sales-and-use-tax exemptions for data centers but is imposing a new tax on electricity use: a move that highlights the trade-offs, uncertainties and potential spread of industry-specific taxation.
For years, the industry has celebrated a reassuring trend: despite a growing number of outages, resiliency has continued to improve. But as AI-driven expansion accelerates, that long-running improvement may be about to stall: or even reverse.
A new framework from the Electric Power Research Institute (EPRI) creates a classification system for data center demand response capabilities to help promote grid flexibility and, in turn, support the continued growth of digital infrastructure.
Internal efforts to maximize token use, combined with changes in LLM pricing structures, have rapidly increased enterprise AI spending. Yet there is often limited visibility into whether such expenditures are creating value.
AI data centers are racing ahead, but the grid isn't keeping up: operators need to rethink how they connect to, generate and manage energy to unlock expansion without overwhelming already strained generation and transmission systems.
In AI model training, idle GPUs — not high prices — are the biggest driver of cost, with poor utilization quietly burning tens of thousands of dollars in wasted compute capacity.
Policymakers across the US are reassessing tax incentives for data center operators, reflecting shifting priorities around infrastructure, costs and community impacts.
Growing public opposition to data center development has pushed many data center companies to invest in media and promotional campaigns. But, as opposition intensifies, this type of outreach is unlikely to sway public opinion.
Jay Dietrich
Dr. Owen Rogers
Dr. Tomas Rahkonen
John O'Brien
Max Smolaks
Douglas Donnellan
Peter Judge
Andy Lawrence
Rose Weinschenk