Goldman Sachs CEO David Solomon delivered a nuanced assessment of the US economic outlook in recent public remarks, projecting acceleration into 2026 while acknowledging current headwinds from trade policy implementation and softer labor markets. His comments come as Wall Street grapples with questions about whether massive AI infrastructure spending will deliver promised returns.
Economy Positioned for 2026 Acceleration
Solomon characterized the US economy as “in pretty good shape” during his remarks, pointing to powerful structural forces keeping growth on track despite near-term challenges. According to the Goldman Sachs chief, aggressive fiscal stimulus from developed-world governments combined with unprecedented infrastructure buildout for AI deployment continues driving economic momentum.
The data tells an interesting story about where we stand. Solomon noted that while third-quarter growth readings came in strong, the year-over-year trajectory from December 2024 to December 2025 will likely land slightly below 2% – marginally under trend but still reflecting economic resilience. What’s particularly significant here is his expectation that this represents a temporary slowdown rather than a sustained deceleration.
“I’m optimistic that we’re probably going to see an acceleration as we continued out into 2026,” Solomon stated, suggesting the economy will gain momentum as trade policy effects are absorbed and technology spending continues flowing through the system.
Trade Policy Creating Near-Term Uncertainty
The implementation of new trade policies emerged as a key variable in Solomon’s economic analysis. He emphasized that markets are still processing these changes, with their full impact on growth trajectories not yet clear. This creates a balancing act between supportive factors like fiscal stimulus and tech infrastructure spending against the headwinds from trade adjustments and heightened geopolitical fragility.
Solomon drew attention to an economic bifurcation that’s becoming increasingly apparent. The upper end of the economy continues spending robustly, while constraints are more visible among lower-income consumers. This split matters for understanding both overall economic health and potential policy responses ahead.
Labor Market Softness Warrants Federal Reserve Attention
One of the more striking elements in Solomon’s commentary centered on labor market dynamics. He acknowledged that hiring has slowed noticeably, with “labor numbers are a little bit softer” – a development the Federal Reserve is monitoring carefully.
The reasoning behind this softness reveals something important about the current technology transition. Solomon explained that major enterprises are pausing hiring decisions as they evaluate how AI and automation tools can transform their operations. This isn’t simply about cutting costs – it’s about strategic reassessment of how work gets done before committing to new headcount.
This hiring pause connects directly to broader questions about AI’s impact on employment. When asked about Federal Reserve rate cuts, Solomon indicated that competing forces between labor softness and inflation uncertainty make the path forward less predictable than market consensus might suggest. While markets currently price in approximately four rate cuts through late 2025, Solomon expressed caution about such precise forecasts given how dramatically conditions can shift.
AI Investment Reality Check
Solomon delivered perhaps his most candid assessment when discussing the massive capital deployment into AI infrastructure – a topic generating increasing concern among investors watching hyperscalers pour $350 billion into data centers and related buildout.
“Does that concern you, that mismatch?” he was asked about returns not matching the scale of investment. His response: “Sure. It concerns anybody that’s deploying capital.”
The Goldman CEO offered a framework for thinking about this investment cycle that draws on historical parallels. He pointed to inevitable winners and losers emerging from any major technology buildout, noting that “there’ll be a bunch of capital that was deployed that ultimately delivered very attractive returns. And there’ll be a lot of capital that was deployed that did not deliver returns.”
What stands out in this analysis is Solomon’s refusal to use the word “bubble” while simultaneously acknowledging clear warning signs. He observed that investors are “out on the risk curve because they’re excited,” and when excitement dominates, people tend to “think about the good things that can go right and they diminish the things you should be skeptical about.”
The historical comparison to 1998 proves illuminating – Solomon noted that similar concerns about internet investment proved premature, with the environment continuing another three years before the significant correction of 2001-2002. This suggests the current AI investment cycle may have considerable runway remaining, even if ultimate reckoning awaits.
Market Drawdown Expected Within 24 Months
Solomon didn’t shy away from near-term market outlook either. With the S&P 500 up approximately 15% year-to-date and global stocks at record highs, he stated plainly: “I wouldn’t be surprised if in the next 12 to 24 months we see a drawdown with respect to equity markets.”
This projection isn’t bearishness about AI’s long-term potential – Solomon called the technology expansion “super exciting” and emphasized that AI deployment into enterprises “can be very, very powerful.” Rather, it reflects recognition that markets have run ahead of fundamentals after a substantial rally.
The comparison of Nvidia‘s $4.5 trillion market cap to the combined market values of France, UK, Germany, and Italy crystallizes how concentrated and elevated valuations have become in the AI sector. Markets historically pull back after such runs, regardless of underlying technology merit.
M&A Activity Surging on Regulatory Shift
Solomon provided concrete data showing deal activity accelerating significantly, driven primarily by changed regulatory posture. Goldman Sachs just completed a $1 trillion M&A volume quarter, with large-cap deals (companies $10 billion or larger) up 100% year-over-year.
The regulatory environment shift represents a fundamental change for strategic planning. Solomon noted that for the past four years, the answer to nearly any significant strategic combination in the US was “no” from regulators. Now CEOs are testing boundaries of what transactions can enhance competitive position or expand scale.
This deal momentum should continue building through 2026, according to Solomon, as companies pursue combinations that were previously unthinkable under more restrictive regulatory oversight.
Goldman’s Technology Investment Dilemma
Solomon shared a revealing insight about Goldman Sachs’ own technology spending constraints. The firm will deploy approximately $6 billion on technology in 2025, but Solomon indicated he’d prefer spending $8 billion – constrained only by return requirements to shareholders.
This tension illustrates a broader corporate reality: AI and automation tools promise to unlock productivity that enables growth investment, but companies must balance innovation spending against immediate profitability demands. Solomon sees AI tools enabling Goldman to expand client service capacity and enter new business areas, but acknowledged specific job categories will see headcount reduction even as overall firm employment could grow with the enterprise.
His perspective on employment reflects optimism that productivity gains translate to business expansion rather than simple workforce reduction – a pattern he noted has held throughout 40 years of technological advancement in financial services.
Europe’s Capital Formation Challenge
Solomon addressed Europe’s struggle to produce globally significant tech companies, prescribing more aggressive risk capital deployment and true economic union operation. He emphasized that European savings and capital must flow more readily into the technology risk ecosystem to compete with US innovation dynamics.
The path forward requires capturing urgency around Capital Markets Union, encouraging cross-border consolidation in banking and exchanges rather than protecting national champions, and accelerating regulatory processes that currently move too slowly for technology sector needs.
What Investors Should Monitor
Several key variables emerge from Solomon’s analysis as critical watchpoints:
Labor market trajectory – Further softening could prompt more aggressive Federal Reserve easing, while stabilization might limit rate cuts. The hiring pause related to AI evaluation adds complexity to interpreting employment data.
Inflation persistence – Whether trade policy impacts prove one-time price adjustments or trigger sustained inflation pressure will significantly influence both Fed policy and economic growth paths.
AI investment returns – Early signals of which companies and approaches are delivering productivity gains versus those burning capital without results will begin reshaping market valuations.
Deal execution – Whether large strategic combinations actually close under new regulatory posture or face unexpected resistance will test CEO confidence and M&A pipeline sustainability.
Market resilience – How equities respond to inevitable pullbacks will reveal whether the bull market has sustainable foundation or vulnerable overextension.
The Bottom Line
Solomon’s remarks reflect confident optimism tempered by realistic risk assessment – an unusual combination in an environment where many commentators lean heavily toward either enthusiasm or alarm. His expectation of economic acceleration into 2026 rests on solid structural supports, even as near-term uncertainty around trade, labor, and inflation creates volatility.
The AI investment discussion proves particularly valuable for cutting through both hype and skepticism. Solomon acknowledges massive capital deployment will produce both spectacular winners and significant losers – the pattern of every major technology transition. His unwillingness to declare a bubble while noting clear complacency and predicting eventual drawdowns offers a balanced framework for thinking about current market positioning.
For investors, the message seems clear: maintain exposure to genuine AI beneficiaries while recognizing that near-term corrections are probable, perhaps inevitable. The technology’s transformative potential remains real even as specific valuations and timelines prove unrealistic.
The economic acceleration Solomon projects for 2026 depends critically on how trade policy absorption progresses and whether labor market softness reflects temporary AI-driven hiring pauses or more concerning structural weakness. The Federal Reserve’s navigation of these crosscurrents will prove crucial, though Solomon’s caution about rate cut forecasts suggests less certainty than market pricing reflects.
Goldman Sachs itself appears positioned to benefit from both surging M&A activity and continued growth in asset management, though the firm faces the same productivity-versus-headcount calculations as every major enterprise evaluating AI deployment.