Brandon Owens
Brandon N. Owens is an energy innovation executive, author, and founder of AIxEnergy, writing on AI, infrastructure, electrification, grid modernization, and intelligent energy systems.
New York City
https://www.linkedin.com/in/owensbrandon/
The Moratorium Map: How the AI Boom Is Redrawing the Geography of Power and Permission
A new AIxEnergy dataset tracks 234 policy actions across 230 geographies, revealing how local governments, states and power systems are turning access to land and electricity into a negotiated form of permission.
Brandon Owens
The Climate Outside the Fence: Why cooling conditions belong in every AI data-center siting model
The International Energy Agency’s July 2026 Electricity Mid-Year Update identifies expanding data-center capacity as one of the structural forces accelerating global power demand. The IEA expects worldwide electricity consumption to grow 3.6 percent in 2026 and 3.8 percent in 2027, reaching approximately 30,700 terawatt-hours. Its more focused April assessment of energy and artificial intelligence estimates that data-center electricity consumption increased 17 percent in 2025, while consumption
Brandon Owens
The Federal AI Land Rush Is an Execution Test
Washington is opening energy sites and military bases to data center developers. The early record shows that federal site control can remove one bottleneck, but it does not erase the harder sequence of leasing, environmental review, power procurement, interconnection, financing, and construction.
Morgan Bazilian
IEA Confirms Data Centers Are Reshaping Global Electricity Demand
The IEA expects global electricity demand to grow 3.6% in 2026 and 3.8% in 2027. In the United States, data centers are the main growth driver, while renewables expand, gas generation rises, and emissions increase modestly in 2026.
Brandon Owens
China’s Tungsten Controls Expose a Semiconductor Chokepoint
WF6, a critical semiconductor gas, remains available despite reports of Japanese production exits. Yet China-linked tungsten feedstock controls, price spikes, concentrated supply, and 18–24-month qualification cycles expose a deeper bottleneck AI-driven chip demand cannot quickly solve.
Morgan Bazilian