AI Investment Boom Creates New Challenges for Federal Reserve
The Federal Reserve is facing a significant challenge as it navigates the rapid growth of artificial intelligence (AI) and its associated $3 trillion investment boom. According to Morgan Stanley, nearly $3 trillion will be invested in global AI-related infrastructure through 2028, with an estimated $1.5 trillion external financing gap.
While some argue that the pressure from this buildout is an inflation problem requiring higher interest rates, others warn that treating every sign of pressure as such may obscure a more immediate challenge: AI's rapidly evolving financing ecosystem, whose leverage, exposures, and vulnerabilities are not well understood. The Fed needs to focus on understanding how investment in AI is being financed, including the growing role of private markets and complex links among borrowers and intermediaries.
The 1990s provide a relevant historical counterfactual. In the mid-1990s, unemployment fell below its natural rate, and the Fed was under pressure to tighten. However, Chairman Alan Greenspan entertained the possibility that models were wrong and productivity growth had raised the economy's speed limit, resisting further rate increases.
The risk of missing AI investment cycles could leave lasting scars on American productivity and competitiveness. The Fed should prioritize understanding the rapidly changing financial architecture of AI, which is creating a large and evolving financing ecosystem with significant leverage, exposures, and vulnerabilities.