Analysis: AI Unlikely to Become a Savior for US Debt, Slow Productivity Growth Coupled with Tax Base Erosion Could Worsen Debt Dilemma

June 17. A research note from Guolian Minsheng Securities points out that, despite market hopes that AI-driven productivity gains will ease pressure on U.S. national debt, historical experience and current realities suggest AI is unlikely to replicate the debt resolution successes seen in the post-World War II era or during the Clinton administration in the short term. By the end of 2025, U.S. national debt is projected to hover near $38 trillion, with net interest payments approaching $1 trillion. The report outlines three strategies to reduce the debt-to-GDP ratio: lowering interest rates, boosting economic growth, and shrinking fiscal deficits. Historically, the U.S. has completed two major debt reduction cycles: between 1946 and 1974, it relied on post-war high growth and technological transformation, cutting the debt ratio from over 100% to roughly 20% over three decades. In the 1990s, leveraging the internet revolution and Clinton administration fiscal discipline, it posted an average annual primary budget surplus of about 3.2% between 1996 and 2001. Today, however, AI-powered debt reduction faces two key constraints. First, AI productivity dividends carry a significant time lag. University of Pennsylvania estimates show AI will only lift total factor productivity by 0.05 to 0.1 percentage points in 2026 and 2027, with its contribution not reaching around 0.2 percentage points until the early 2030s—far too little to offset current fiscal pressures. Second, AI concentrates factor returns heavily on capital, systematically eroding the tax base. U.S. individual income and payroll taxes together make up roughly 85% of federal revenue, and AI-driven labor displacement and wage suppression will directly impact this core tax source. Corporate income tax accounts for only about 10% at a flat 21% rate, plus tech giants’ cross-border tax avoidance, making it nearly impossible to fill the personal tax gap. This creates a paradox: the more technology thrives, the more the tax base shrinks. The research report identifies potential solutions: raising capital gains and top wealth tax rates, imposing a “digital services tax” on commercial gains from large AI models, and exploring a “robot tax” to subsidize tech-displaced workers. But all face structural dilemmas: challenges in cross-border tax administration for AI elements, tech giants’ strong political lobbying power, and unilateral tax hikes suppressing innovation. The report concludes that financial and tax adjustments in the AI era will be a long-term institutional tug-of-war, and the U.S. debt dilemma remains a major near-term obstacle for the U.S. economy to overcome.