Kirkland & Ellis

This article explores the growing public opposition to data center expansion and investigates the reasons behind this trust gap, seeking solutions to bridge the divide.

Small Modular Reactors (SMRs) are progressing through regulatory approvals and manufacturing development, with increasing focus on industrial uses like data centers, driven by accelerating artificial intelligence power demands.

CoreWeave's announcements at NVIDIA GTC 2026 and Bell Canada's 300 MW development in Saskatchewan indicate a strategic pivot towards integrated artificial intelligence infrastructure, where power, platforms, and sovereign capacity are key determinants of future scale.

Nscale is advancing a power-centric artificial intelligence infrastructure strategy, integrating data centers, GPU fleets, and energy development through its AIPCorp acquisition, Microsoft collaboration, and planned NVIDIA Vera Rubin system deployments across its expanding U.S. and European portfolio.

Schneider Electric executives Marc Garner and Jim Simonelli discussed at NVIDIA GTC 2026 how artificial intelligence infrastructure is necessitating a fundamental redesign of data centers, encompassing digital twins, liquid cooling, grid integration, onsite power, and the transition to higher-density electrical architectures.

SoftBank's 10 gigawatt Ohio project, supported by the Department of Energy leasing federal land and AEP assisting with transmission, represents a significant new benchmark for artificial intelligence data centers, emphasizing power and infrastructure.

TerraPower's Natrium reactor has received Nuclear Regulatory Commission construction approval in 18 months, indicating a streamlined licensing process for advanced nuclear technology with potential applications for powering artificial intelligence data centers and high-density infrastructure.

This article examines the accelerating development of artificial intelligence data centers and the challenges posed by existing assumptions about power, delivery timelines, and community acceptance, which are being tested by real-world constraints.

High-temperature superconducting wire is emerging as a critical technology for delivering, distributing, and monetizing power within data centers as artificial intelligence campuses scale towards gigawatt capacity.

As artificial intelligence data center infrastructure expands, the industry faces a significant test of credibility, requiring it to secure public trust and maintain its social license to operate with regulators, communities, and ratepayers.

In the current artificial intelligence era, future-proofing data centers involves strategically balancing the need for speed, scale, and flexibility while avoiding overbuilding in the face of demand uncertainty.

The rapid growth of data centers is being hampered not by a lack of demand, capital, or customers, but by insufficient electrical power due to a grid that cannot expand quickly enough to meet escalating needs.

Following his keynote at GTC 2026, Jensen Huang described artificial intelligence infrastructure as a comprehensive industrial system where inference, token economics, and synchronized data center construction will dictate future expansion.

The scaling of artificial intelligence campuses to gigawatt levels presents a major execution challenge that requires aligning utilities, construction firms, and suppliers into a unified, coordinated system.

At NVIDIA GTC 2026, Jensen Huang detailed the architecture of the AI factory, including Rubin systems and inference pipelines, highlighting optical networking and Nvidia's blueprint for developing large-scale AI infrastructure.

Four industry leaders convened to examine the operational, technical, and organizational capabilities essential for delivering next-generation data centers as AI infrastructure projects scale in size and speed.