THIS IS THE WORRYING PART

Over 1.17 million jobs were cut in the U.S. last year, the highest number since the pandemic. 600,000 jobs were cut in just the first two months of 2026.

Major layoffs include: • U.S. Government: 317,000 • UPS: 78,000 • Amazon: 30,000 • Intel: 25,000 • Citigroup: 20,000 • Nissan: 20,000 • Microsoft: 15,000 • Verizon: 13,000 • Accenture: 11,000 • Salesforce: 4,000 • Block: 4,000 A significant portion of these layoffs is due to artificial intelligence (AI). Companies are publicly stating that smaller teams can now accomplish the same work. This is happening amid the weakest office hiring market since 2008. The risk is straightforward. The U.S. economy relies on consumer spending. High-income workers generate most of that demand. When jobs paying $150,000–$200,000 are replaced by software, company profits increase, but household incomes decrease. There is also a secondary ripple effect: Companies cutting staff are also selling products and services to the same income group. If layoffs driven by AI broadly reduce household incomes, demand for retail, fintech, SaaS, travel, and business services will weaken. Short-term profits may rise, but in the long run, customer numbers will decline. If this spreads, spending will weaken. Housing, cars, travel, subscription services, and credit quality all become sensitive. You may see increased productivity and strong corporate profits while the underlying income base declines. This is how you build a GREY ECONOMY—output increases, but broad participation in that growth diminishes. The labor market needs to adapt to this transition before demand begins to weaken at the core of the economy.