{
  "id": 3233593,
  "title": "The Fed doesn’t know who’s financing the $3 trillion AI boom",
  "url": "https://urgent.news/2026/08/25/the-fed-doesnt-know-whos-financing-the-3-trillion-ai-boom",
  "topic": "ai",
  "section": "AI",
  "published": "2026-08-25T09:00:00.000Z",
  "source": {
    "name": "Fortune",
    "slug": "fortune",
    "url": "https://fortune.com/2026/08/25/the-fed-doesnt-know-whos-financing-the-3-trillion-ai-boom/"
  },
  "original_language": "en",
  "account": "Artificial intelligence and monetary policy are drawing increasing attention from policymakers. Federal Reserve Chair Kevin Warsh and others highlight AI's potential to boost productivity and capacity, despite the investment boom straining resources before benefits emerge. However, this investment boom also creates a rapidly evolving financing ecosystem with less understood leverage, exposures, and vulnerabilities. Morgan Stanley estimates nearly $3 trillion in global AI-related infrastructure investment by 2028, with an estimated $1.5 trillion financing gap. This could raise resource utilization and prices in the short term, while automation, organizational changes, and new capital should raise potential output and lower unit costs over time. The mistake would be treating all pressure from this growth as an inflation problem requiring higher interest rates. Monetary policy can influence the investment and innovation that determine future supply. Economic history offers a counterfactual example: during the 1990s, despite unemployment being below the natural rate, the Fed largely resisted further rate increases, leading to continued unemployment and subdued inflation. The question today is: How much of the 1990s productivity boom would the U.S. have missed if the Fed had continued tightening? With AI, the damage could be permanent, as data centers, power capacity, human capital, financing expertise, and related businesses create cumulative advantages. If the investment occurs elsewhere, it may not return to the U.S. in the future. Focusing solely on inflation overlooks the rapidly changing financial architecture of the AI boom. Traditional monetary policy models give little independent weight to financial variables, focusing instead on inflation and employment or the output gap. A 2018 study by Patrick Moran and Albert Queralto found that when innovation and technology adoption are endogenous, monetary policy changes firms' incentives to develop and implement new technologies, affecting future productivity. The historical counterfactual of the 1990s demonstrates the importance of understanding how the investment is financed, the growing role of private markets, complex links among borrowers and intermediaries, and where leverage, maturity risk, and ultimate exposures lie. The Fed needs better data, better models, and a different allocation of intellectual resources to understand and address these financial vulnerabilities.",
  "summary": "The Fed spent the past few years relearning the dangers of underestimating inflation. The challenge now is complexity and financial innovation.",
  "key_points": [],
  "editors_take": null,
  "illustration": null,
  "coverage": {
    "outlets": 1,
    "also_reported_by": []
  },
  "ai_generated": true,
  "disclaimer": "Summaries, key points and the editor’s take are written by software from other outlets’ reporting and may contain errors — always check the linked original."
}