The 2026 Global Intelligence Crisis - Citadel Securities
The year is 2026. The unemployment rate just printed 4.28%, AI capex is 2% of GDP (650bn), AI adjacent commodities are up 65% since Jan-23 and approximately 2,800 data centers are planned for construction in the US*. In spite of the current displacement narrative – job postings for software engineers are rising rapidly, up 11% YoY.
Indeed Job Postings: Software Engineers + Overall Postings, Daily and 21dma
The more important question insofar as it relates to the AI displacement narrative is: how intensely is AI being used for work? We can tease out the answer from a subset of the St Louis Fed data that buckets by frequency of AI use. We would posit that if AI represents imminent displacement risk, the real time population data would show an inflection upwards in the daily use of AI for work. The data seems unexpectedly stable and presents little evidence of any imminent displacement risk (solid lines at the bottom of the chart).
Displacing white collar work would require orders of magnitude more compute intensity than the current level utilization. If automation expands rapidly, demand for compute definitionally rises, pushing up its marginal cost. If the marginal cost of compute rises above the marginal cost of human labor for certain tasks, substitution will not occur, creating a natural economic boundary. This dynamic contrasts sharply with narratives assuming frictionless replication of intelligence. Even if algorithms improve recursively, economic deployment remains bounded by physical capital, energy availability, regulatory approvals, and organizational change.
For AI to generate a sustained macro contraction one must assume that labor income falls and no compensating rise occurs in investment, fiscal transfers, or external demand. The surge in new business formation is an interesting point of reference here.