The Next Growth Wave Could Be Stronger—and More Sustainable

The article argues that U.S. growth is being supported by productivity gains, cleaner technology, and a shift toward higher-value service jobs, with non-farm productivity cited at 4.9% in Q3 2025 versus 4.4% GDP growth. It highlights AI-related efficiency improvements and falling emissions alongside rising output, implying a constructive backdrop for equities. The piece is broadly bullish on growth and suggests GDP could reach 5% in late 2026.

Analysis

This is less a broad “GDP is good” note than a regime argument that the marginal dollar of growth is becoming more capital-intensive, software-intensive, and margin-accretive. That matters for equities because productivity-led expansion tends to widen operating leverage for asset-light businesses while compressing the bargaining power of labor-heavy or input-heavy models. Goldman’s framing also implicitly favors firms with AI exposure and pricing power: if output can rise without commensurate headcount or materials growth, the winners are the toll collectors on compute, software, and workflow automation rather than cyclical volume names.

The second-order effect is that this kind of growth is not inflationary in the traditional sense, which should extend the duration of multiple support for quality growth and cap the downside for financial conditions. But the market may be underestimating the lag: productivity shocks usually hit earnings before they show up cleanly in macro data, so the next 2-4 quarters could see a widening gap between “AI beneficiaries” and the rest of the index. Goldman’s own stock-call implication is also important: if the index they are referencing is meaningfully more levered to productivity/AI than the S&P, relative outperformance can continue even in a choppy tape, but the leadership can become crowded fast.

The contrarian risk is that investors may be extrapolating a temporary AI burst into a durable trend too early. If capex, energy costs, or regulation slow AI deployment, the productivity narrative can fade while valuation multiples remain elevated, which is the classic setup for underperformance in the second half of the cycle. The cleanest tell over the next 1-3 months is whether breadth improves beyond mega-cap AI winners; if not, the “outperformance” trade is likely just a narrow factor trade rather than a true broad-based equity upswing.

Key Decisions for Investors

• Go long GS vs. XLY/S&P proxy on a 1-3 month horizon: buy GS and hedge with SPY, targeting a 5-8% relative outperformance if the market continues to reward productivity/AI-levered franchises.
• Add to AI infrastructure beneficiaries (MSFT, NVDA) on pullbacks over the next 2-6 weeks; the setup favors companies that monetize productivity gains directly, with upside sustained by earnings revisions rather than multiple expansion alone.
• Pair trade: long software/workflow automation (MSFT, NOW) vs. short labor-intensive cyclicals (UAL, MCD, or a basket of staffing/leisure names) for 1-2 quarters; the thesis is margin expansion from labor displacement and efficiency gains.
• Buy a 3-6 month call spread on QQQ rather than outright calls; if the growth narrative persists, upside should be incremental and concentrated, but call spreads reduce the risk of paying peak crowding premium.
• If macro data start to show slower AI capex or weaker productivity prints over the next 1-2 quarters, trim crowded winners first and rotate into quality value/defensives; the trade is vulnerable to a sentiment unwind even if fundamentals remain acceptable.