Reviews examine major studies, forecasts, and institutional reports shaping the AI-energy debate. Each review distills the evidence, tests the assumptions, and explains what the findings mean for grids, data centers, markets, infrastructure strategy, and policy.
AEO2026 reframes its “Reference Case” as a control, not a forecast, and reveals a structural shift: electricity demand—driven by data centers and AI—is now the primary system variable, with load shape (continuous vs peak) redefining grid costs and planning
Brandon Owens
Energy is shifting from a single constraint (cost) to a multi-constrained system—power, materials, supply chains, and policy. Clean tech is scaling on economics, but fragility is rising. The transition now hinges not just on deployment, but on aligning constraints across the system.
Brandon Owens
The White House AI framework accelerates infrastructure at unprecedented speed—but exposes 10 systemic risks, from rising grid fragmentation and cost shifting to reliability, market and governance gaps, as a “Shadow Grid” emerges outside traditional oversight.
Brandon Owens
The IEA’s 2026 report shows energy innovation is now central to competitiveness and security. Public investment drives long-term returns, resilient grids are essential, and institutional capacity—not resources alone—will define leadership in the twenty-first century energy transition.
Brandon Owens
The OECD AI report offers a governance framework for advanced AI, but it is platform-centric. As AI embeds into grid operations and hyperscale load, governance must shift from model oversight to physical consequence—linking compute to megawatts, reliability margins, and ratepayer impact.
Brandon Owens