Contrary to popular belief, recent electricity price hikes are not yet driven by AI demand. Instead, they reflect a system that had already become less reliable due to the retirement of dispatchable coal power and increased dependence on intermittent renewables. The grid was already tight before the current demand wave hit.

The massive computing power required by AI is causing energy demand in developed nations to rise for the first time in years. This shifts the energy conversation from a supply issue to a pressing political one, as policymakers must balance costs, reliability, and grid stability for consumers.

The push for massive overbuilding of solar/wind and gigantic battery farms is not an optimal grid strategy. It's a workaround that became popular only because of a pre-existing belief that building new, reliable baseload nuclear power was not an option.

Despite staggering announcements for new AI data centers, a primary limiting factor will be the availability of electrical power. The current growth curve of the power infrastructure cannot support all the announced plans, creating a physical bottleneck that will likely lead to project failures and investment "carnage."

Traditional energy models incorrectly started with climate supply targets. A more accurate approach models fundamental demand drivers first (population, GDP), revealing a massive, underestimated need for all energy types to meet future growth, challenging supply-centric narratives.

Unlike typical diversified economic growth, the current electricity demand surge is overwhelmingly driven by data centers. This concentration creates a significant risk for utilities: if the AI boom falters after massive grid investments are made, that infrastructure could become stranded, posing a huge financial problem.

From the 1980s to 2010s, improvements in appliance and industrial efficiency kept net electricity demand flat. This masked growing energy service needs and allowed the underlying grid infrastructure to stagnate without significant investment, creating today's bottleneck.

The restructuring of the U.S. electricity sector wasn't purely ideological. It was a direct response to regulated utilities making massive, incorrect bets on demand growth, building unneeded power plants, and causing prices to skyrocket for captive customers. Competition was introduced to shift this investment risk from consumers to private investors.

Most of the world's energy capacity build-out over the next decade was planned using old models, completely omitting the exponential power demands of AI. This creates a looming, unpriced-in bottleneck for AI infrastructure development that will require significant new investment and planning.