Goldman Sachs trading team 2026 three major U.S. stock trades: Focus on "AI trading" next steps

Goldman Sachs' trading department focuses its 2026 U.S. stock investments on the deepening phase of AI applications, shifting from infrastructure investment to actual productivity enhancement. This shift reflects the market's more cautious assessment of which companies can truly convert technology into profitability after three years of AI frenzy.

According to Goldman Sachs derivatives strategist Brian Garrett, the three main thematic trading strategies include: going long on companies that use AI to enhance productivity, going short on discretionary consumer goods companies targeting low-income groups, and a pair trade of going long on high-quality AI stocks while shorting weak AI stocks.

Analysis indicates that these strategies aim to capture market opportunities arising from the "K-shaped recovery" of the U.S. economy and the differentiation of AI applications, reflecting the transition of AI technology from the investment phase to the application phase, as well as the increasingly stringent selection criteria for AI-related investments.

Goldman Sachs' chief market strategist Tony Pasquariello noted in the first annual report that the macro backdrop remains favorable for the stock market in 2026. Goldman Sachs economists expect global economic growth of 2.8% in 2026, higher than the market consensus of 2.5%, with all regions continuing to expand, and the Federal Reserve will further moderate interest rate cuts.

Goldman Sachs' co-head of global banking markets Ashok Varadhan recently stated in a podcast that "the U.S. is the preferred destination for investment." This judgment is based on Goldman Sachs economists' forecast of 2.6% economic growth in the U.S. in 2026, significantly above the market consensus of 2.0%, with growth momentum coming from reduced tariff drag, tax cuts, and a loose financial environment.

AI Applications Entering the Productivity Enhancement Phase

Goldman Sachs' U.S. AI Productivity Beneficiaries Index shifts the investment focus from "infrastructure" such as semiconductors and data centers to companies that actually apply AI technology to reduce costs and improve profit margins.

The index constituents are non-tech, non-AI companies, but all have proposed specific plans to integrate AI into their workflows. Since the third quarter of 2024, the index has begun to outperform the S&P 500 equal-weight index in terms of earnings performance.

Goldman Sachs expects this trend to continue, as the potential impact of AI applications on labor productivity exceeds that of the S&P 500 and Russell 1000 indices in terms of baseline earnings per share.

The index constituents cover industries such as banking/insurance, retail/warehouse operators, transportation/logistics, healthcare, and dining. Goldman Sachs believes that these companies have the greatest potential to enhance operational efficiency through AI technology, and the effects have begun to show in their financial reports.

Shorting Low-Income Consumer Sector in K-Shaped Economy

Goldman Sachs' trading team stated that despite strong GDP growth in 2025, the labor market shows weakness, particularly with negative job growth in the summer months, and the unemployment rate rising from 4.1% in June to 4.6% in November. The characteristics of a K-shaped economy remain significant, with low-income groups continuing to bear high price pressures, while high-income groups see substantial growth in asset wealth.

The index of non-essential goods companies targeting low-income consumers recommended by Goldman Sachs underperformed the S&P 500 and S&P 493 indices in 2025. The bank expects this theme to continue in 2026, as low-income consumers continue to struggle amid an affordability crisis. **

Goldman Sachs' U.S. Macro Team reported on December 1:

"The pressures faced by low-income consumers—including more limited borrowing capacity and weaker income growth—and the slowdown in immigration may be reflected in poor performance. Our distribution income growth forecast indicates that low-end consumption will continue to perform poorly in 2026, with weak job growth and OBBBA cuts to SNAP and Medicaid benefits dragging down income growth for low-income households."

According to a previous article from Wall Street Insight, a survey by the University of Michigan in early December showed: "Consumers saw slight improvements on several dimensions compared to November, but the overall sentiment remains gloomy, with consumers continuing to mention the burden of high prices. Similarly, labor market expectations have improved slightly, but remain relatively bleak."

Market Shifts to Quality AI Stock Selection

After three consecutive years of soaring AI trading (with the Goldman Sachs AI Index rising about 284%, while the S&P 500 rose about 80%), the market has begun to more cautiously assess the fundamentals of AI stocks.

In recent months, numerous negative news reports have shaken investor confidence, leading the market to refocus on traditional metrics such as profitability, balance sheet strength, credit quality, and free cash flow.

Two months ago, Goldman Sachs categorized AI stocks into "High-Profit AI" Index and "Weak AI" Index, using balance sheet strength, credit quality, and free cash flow resilience as distinguishing factors.

Goldman Sachs recommended a pair trading strategy that goes long on high-profit AI stocks and short on weak AI stocks, aiming to benefit from the increasingly stringent market selection.

Key distinguishing metrics for this strategy include net profit margin, earnings per share, debt levels, free cash flow, and credit ratings. Goldman Sachs believes that this pair trading can isolate quality from weak stocks, adapting to the market's trend of increasingly strict standards for AI investments.