# S&P 500 target stays at 8,000 despite AI selloff as capital discipline could extend growth cycle

By Riza Dagoc

Canonical URL: https://www.tokenpost.com/news/investing/53611
Published: 2026-11-11T05:40:37.000Z
Updated: 2026-11-11T05:40:37.000Z
Section: Investing

> Jim Thorne kept his year-end S&P 500 target at 8,000, calling the AI selloff a liquidation event. He said capital discipline could extend the investment cycle beyond 2030 and broaden market gains.

Jim Thorne maintained his year-end S&P 500 target of 8,000, describing the AI stock selloff as a liquidation of excessive positions. He argued that greater capital discipline and lower interest rates could extend the investment cycle and broaden market gains.

The sharp retreat in Nasdaq and AI stocks reflected forced selling rather than the end of the growth cycle, in Thorne’s assessment. More measured spending on AI infrastructure could sustain investment for longer, while gains spread to companies using AI and to cyclical sectors.

In a November 10 interview with David Lin, Thorne, chief market strategist at Wellington Altist Private Wealth, reaffirmed his bullish outlook for the S&P 500. He attributed the recent selling to hedge funds unwinding positions they had allowed to become excessive.

Thorne described bottoming as a process and cautioned against treating short-term volatility as evidence that the broader trend had ended. His 2027 outlook put the S&P 500 at 10,000, based on index earnings per share of $450, a 4% yield on the 10-year Treasury and a price-to-earnings multiple of 22.

For AI investment, Thorne said efficient capital allocation would become more important as companies moved beyond spending everything available to avoid falling behind competitors. He argued that stronger spending discipline could extend the cycle beyond 2030. Lower near-term capital expenditure could also allow major cloud operators to turn free-cash-flow positive sooner.

Financing conditions would increasingly separate stronger businesses from weaker ones, he said. High-quality hyperscalers should secure the capital they need, while lower-quality data center operators could struggle to obtain funding. Thorne projected US capital expenditure of $1 trillion to $1.5 trillion in 2027, supporting continued earnings momentum.

Greater spending discipline could also intensify computing scarcity, Thorne said. He expected data center construction to continue, with a more measured investment pace extending constraints on capacity. He also anticipated that data centers would increasingly be required to cover their own electricity costs.

Thorne expected market opportunities to broaden beyond companies benefiting from power and memory shortages or GPU demand. He identified businesses using AI to improve margins as a potential next area of market interest. Falling energy costs and interest rates could also help cyclical sectors that had missed the AI rally participate in the recovery, supporting more balanced portfolios heading into 2027.

Underlying that outlook was his view that AI-driven growth obscured weakness elsewhere in the US economy. Productivity gains and declining unit labor costs did not describe conditions across every sector, he said. Interest-sensitive businesses outside AI had been under pressure from what he considered excessive Federal Reserve tightening over recent years.

Thorne argued that the neutral interest rate—the rate consistent with economic balance—could differ across sectors, with cyclical businesses needing substantially lower rates than current levels. He called for the Fed to cut rates and focus on housing and sectors left outside the AI investment boom, describing lower borrowing costs as a potential catalyst for broader market participation.