Blind Spots in the AI Infrastructure Selloff

The recent selloff in AI infrastructure stocks stems from technical factors like profit-taking and crowded positioning rather than a decline in fundamental demand. Enterprise AI adoption remains economically compelling, as a $2 to $5 execution cost can save a company $55, suggesting significant room for growth beyond the current $11 monthly median token spend per employee. Jevons paradox indicates that increased model efficiency and lower costs will likely drive higher compute demand, which could double every six months and lead to a thousandfold increase over five years. While data centers face a potential 38-gigawatt power deficit by 2028 due to grid constraints and labor shortages, these obstacles represent temporary delays rather than structural dead ends. Solutions such as on-site generation and energy storage are expected to bridge the gap, supporting a long-term rise in demand for intelligence, compute, and power.