New York University finance professor Aswath Damodaran on AI earnings and cash returns

In a blog post dated October 8, 2026, NYU Stern Professor Aswath Damodaran ↗ detailed how AI capital expenditures (capex) influence US equities through accounting and market mechanisms. Damodaran's research focuses on valuation, corporate finance, and portfolio management, providing frameworks often used to assess the relationship between market pricing and corporate fundamentals.

He observed that despite a 54 basis point rise in the ten-year treasury yield to 5.29% in September 2026, US market capitalization grew by $2.5 trillion, with technology contributing nearly $1.5 trillion. This resilience stems from massive spending by AI builders (hyperscalers) converting into revenue for suppliers like chipmakers and power companies, thereby boosting aggregate corporate earnings.

However, this earnings surge has not translated proportionally into shareholder cash returns. S&P 500 companies returned only 63% of their earnings via dividends and buybacks over the last twelve months, the lowest level since 2004. This disconnect occurs because capex reduces free cash flow, and some AI builders use extended amortization schedules to mitigate immediate earnings hits.

Damodaran estimated the implied equity risk premium at 3.70%, falling below 4% for the first time this year. He argues that markets are pricing in the success of AI businesses; if AI fails to deliver, stock prices will correct before accountants write down assets. Investors face choices between betting fully on AI, following consensus, remaining skeptical, or shorting the trend, with Damodaran himself favoring core holdings plus increased cash reserves for balance.