The performance of markets in 2026 is likely to hinge on a few key themes or events, one of which will surely relate to AI, automation, and bubbles. Even though U.S. large-cap valuation metrics are at or near their highest historical observations, the U.S equity market is not necessarily in a bubble if new technology can deliver labor cost savings that are transformative for corporate profitability.
The chart provides a simplified model of potential U.S. labor-cost savings from the productivity revolution now underway. The chart assumes U.S. labor-cost growth of 5% per annum, with efficiency gains from AI, robots, and driverless vehicles that reduce labor costs by 2% in 2026, growing to a 20% savings by 2036.1.2. Stated another way, the model assumes that new technologies lower the labor-cost growth rate from 5% to 4%. The present value of the total savings from slowing wage growth is estimated at about $62 trillion using a 5% discount rate.
There are important qualifiers to this analysis. First hyperscaler and semiconductor stocks have captured most of the market gains so far, but the potential labor savings are expected to ultimately be broad-based and realized by companies across the wider economy. Second, the labor cost savings depend on successful AI adoption and implementation, which in turn requires massive investment that carries the associated risks of capital misallocation and losses.
Identifying and investing in AI-adopting companies that successfully navigate the transition from human labor to capital-intensive technology should be an important theme in 2026.
1.Based on BEA’s ‘Total wages and salaries, BLS’ series (FRED code BA06RC1A027NBEA), nominal U.S. wages and salaries have grown at about 5% per year since the early 1980’s
2.The Penn Wharton Budget Model assumes current generative AI tools deliver labor cost savings of roughly 25% on average on affected tasks, with case studies ranging from 10% to 55%, and projects that average savings will grow from 25% to 40% over the coming decades.