Incremental increases in material production won't significantly move the needle on energy consumption. The next 10x in per capita energy use will be driven by two main factors: expanding aviation to billions of people and the explosive growth of AI compute, which acts as a 'per capita' increase in intelligence.

The primary constraint on AI development is shifting from semiconductor availability to energy production. While the US has excelled at building data centers, its energy production growth is just 2.4%, compared to China's 6%. This disparity in energy infrastructure could become the deciding factor in the global AI race.

Data over the last 40 years shows that the percentage change in gross world product moves in lockstep with the percentage change in gross energy consumption. A 5-10% fall in energy supply, as threatened by the conflict, will almost certainly trigger a 5-10% fall in global GDP.

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.

According to the IEA, the global competition in artificial intelligence will be decided not just by technology, but by the availability and cost of electricity. Data centers are incredibly power-intensive, making energy a critical, and often overlooked, factor for AI supremacy.

Economic growth is a direct function of the reduction in the price of energy. Nations with access to cheap, locally available energy are almost uniformly wealthy, regardless of their system of governance, while those without it are almost uniformly poor.

Markets often over-focus on relative interest rate policy when analyzing currencies. During an energy crisis, the macroeconomic effect of rising oil prices is a far more powerful driver. The disproportionate negative impact on energy-importing economies like Japan and Europe will weigh on their currencies more than any central bank actions.

Historical data from 2008 and 2021-22 shows a strong correlation between oil price spikes and significant downturns in semiconductor stocks. In both periods, the sector declined by roughly 30%. This suggests energy market volatility is a direct leading indicator of financial risk for tech investors.

Headline GDP figures can be misleading in an environment of high immigration and inflation. Metrics like per-capita energy consumption or the number of labor hours needed to afford goods provide a more accurate picture of individual well-being, revealing that many feel poorer despite positive official growth numbers.