Goldman Sachs has released its highly anticipated 2026 market outlook, projecting continued gains for the S&P 500 alongside massive acceleration in AI capital expenditures and a fundamental shift in how AI investments play out in the market.
The investment bank forecasts the S&P 500 will reach approximately 7,600 by year-end, representing a 12% gain and marking another year of double-digit returns, though at a more moderate pace than the 16% surge seen in 2025. This optimistic outlook is underpinned by strong earnings growth, robust economic expansion, and critically, increased productivity gains from artificial intelligence adoption.
AI spending among hyperscalers is projected to surge 36% to $539 billion in 2026, according to Goldman’s analysis, with further growth to $629 billion expected in 2027—a 17% increase. This massive capital expenditure reflects the continued buildout of AI infrastructure by major tech companies, though strategists note that spending growth may eventually slow as companies face pressure to justify these investments with tangible profits.
Perhaps most significantly, Goldman identifies 2026 as the beginning of “Phase 3” of the AI trade—a new chapter that will fundamentally reshape which companies benefit from artificial intelligence. While Phase 2 was characterized by heavy infrastructure spending, Phase 3 will be defined by three key shifts: slowing capital expenditure growth rates, broader AI adoption across industries, and the emergence of a new group of AI winners beyond the initial infrastructure providers.
The bank emphasizes that companies will need to demonstrate actual earnings improvements from AI-related productivity gains before investors embrace them as long-term beneficiaries. This marks a maturation of the AI investment thesis, moving from speculation about potential to demands for proven results.
Goldman also predicts that cyclical investments will outperform early in 2026, supported by economic acceleration, stimulus measures, and less severe tariff impacts than feared. The firm highlights middle-income consumer stocks and nonresidential construction as particularly attractive. Additionally, M&A activity is expected to rise 15%, with completed transactions already rebounding 75% in 2025 to surpass $1.9 trillion, driven by strong economic conditions and increased business confidence.
Key Quotes
As spending and debt grow, so do the necessary eventual profits to justify ongoing investments
Goldman Sachs strategists highlighted the mounting pressure on AI companies to demonstrate returns on massive capital expenditures, signaling that the era of spending without clear profitability metrics may be ending.
We believe companies will need to demonstrate earnings uplifts from AI-related productivity before investors will embrace them as likely long-term beneficiaries
This statement from Goldman’s strategists underscores the shift from speculative AI investing to a results-driven approach, where companies must prove AI delivers measurable business value.
As AI adoption increases, so will the clarity surrounding which stocks belong as part of the ‘Phase 3’ group of revenue beneficiaries
Goldman’s team suggests that 2026 will reveal a new class of AI winners beyond infrastructure providers, as broader adoption clarifies which companies can successfully monetize artificial intelligence.
Corporates should be able to enjoy the revenue tailwinds from economic acceleration without facing the trade-offs from increased wage pressures or Fed tightening that often characterize late-cycle environments
The bank’s strategists explain why AI-driven productivity gains create a unique economic environment where companies can grow revenues while maintaining margins, a key factor supporting continued market gains.
Our Take
Goldman’s analysis reveals a maturing AI investment landscape that separates hype from sustainable value creation. The projected slowdown in capital expenditure growth rates—from 36% in 2026 to 17% in 2027—suggests hyperscalers are approaching peak infrastructure spending, shifting focus toward utilization and monetization. This transition creates both risks and opportunities: infrastructure-focused AI plays may face headwinds, while companies demonstrating genuine productivity gains could emerge as new market leaders. The $539 billion spending figure also highlights AI’s economic magnitude—this level of investment will drive innovation but also creates enormous pressure for returns. Companies that fail to translate AI capabilities into earnings growth will likely face investor skepticism, potentially triggering a shakeout that separates viable AI businesses from those riding the hype cycle. The broader implication is clear: AI is transitioning from a speculative technology bet to a fundamental business requirement, with measurable impacts on productivity, profitability, and competitive positioning.
Why This Matters
This Goldman Sachs outlook signals a critical inflection point for the AI industry and broader technology markets. The projected $539 billion in AI capital expenditures for 2026 represents one of the largest infrastructure buildouts in modern economic history, comparable to previous transformative technology waves like the internet boom and mobile revolution.
The transition to “Phase 3” of the AI trade has profound implications for investors and businesses alike. While early AI winners were primarily infrastructure providers—chip manufacturers, cloud platforms, and data center operators—the next phase will reward companies that successfully monetize AI through productivity gains and revenue growth. This shift means businesses across all sectors must demonstrate tangible ROI from AI investments rather than simply participating in the hype cycle.
For workers and society, this evolution suggests AI is moving from experimental technology to core business infrastructure, potentially accelerating job displacement in some sectors while creating new opportunities in others. The emphasis on productivity gains also indicates that AI’s economic impact is becoming measurable and material, validating years of investment and development while raising the stakes for successful implementation.