Following three consecutive years of robust yet highly volatile returns for technology stocks, as 2026 approaches, Wall Street's focus is shifting from pure hardware hype to a deeper examination of AI investment returns and the sustainability of market breadth. According to the latest outlook report from Goldman Sachs' top tech trader, Peter Callahan, although the Nasdaq 100 Index ultimately rose over 20% in 2025, it was far from a year of easy gains. Callahan pointed out that while the "Mag 7" collectively contributed approximately $3.5 trillion in market cap growth during 2025, this pace has shown signs of slowing compared to the $5.4 trillion in 2024 and $4.8 trillion in 2023. Furthermore, internal market divergence reached extreme levels, with over 30% of the components in the Nasdaq 100 Index finishing the year in negative territory.

As investors increasingly focus on whether generative AI (GenAI) can deliver on its hefty capital expenditure promises over the next 12 months, market sentiment is undergoing a subtle shift. Callahan emphasized that the core of the current debate revolves around the sustainability of the path for AI infrastructure spending—for instance, potentially reaching $3 trillion to $4 trillion annually by 2030 based on Nvidia's data—and when this massive investment will translate into tangible productivity gains. To clarify this complex market environment, Callahan has outlined ten core questions that will determine the trajectory of tech stocks in 2026. These questions not only pertain to specific sector rotations but also touch upon the fundamental logic of macroeconomic and technological cycles. Ten Key Questions Determining the 2026 Trajectory Callahan explicitly posed the following ten questions in his report that will dominate the market narrative in 2026:

Where will the AI debate lead? Will the focus shift to "Physical AI" (robotics, autonomous vehicles, smart glasses)? Which companies will emerge as the winners in productivity enhancement? How will regulation and Return on Invested Capital (ROIC) evolve? How will (application) software companies repair their valuations? What looming challenges will the software industry face over the next 12-24 months? Is it the end of the per-seat pricing model, the rise of Agents, utilization issues, or commoditization competition brought by Large Language Models (LLMs)? What is Apple's narrative? Entering 2026, is Apple a defensive growth stock or an AI story? Can foldable phones act as a catalyst? Why is App Store growth slowing? What are the broad implications of a commodities supercycle? Considering the price trends of storage products like DRAM, HDD, NAND, as well as gold, silver, and copper, which other areas face supply constraints? Who can absorb price increases, and who cannot? What does GenAI-driven "efficiency" mean? If it implies layoffs, will the market view it as a positive signal of productivity gains or a negative factor pressuring the economy and non-farm payroll data? Which internet companies are the most compelling buys amidst debates on profit margins and competition? For instance, investors are vigorously debating the prospects of companies like META. Is an inflection point coming for cyclical industries? Will 2026 witness a cyclical turnaround in housing, commercial real estate (CRE), ISM data that has been below 50 for three consecutive years, analog semiconductors, or the automotive industry? Can Hardware and Semiconductor AI stocks lead the market again? Or will debates about gross margins, spending visibility, or intensified competition suppress market sentiment? How will the market's view on Large Language Models (LLMs) evolve? Will they trend towards "commoditization"? Is it a competitive market with multiple players or one dominated by a few? Is it about Artificial General Intelligence (AGI) or Artificial Superintelligence (ASI)? What role will Chinese models play? Will the focus shift to productization and implementation, or remain a contest of "raw intelligence"? What are the current blind spots? What topics are unmentioned now but will become consensus by 2026? Is it Agentic commerce, the return of SaaS stocks, or specific use cases for AI productivity?

2026 Outlook: Searching for Second Derivatives and Mean Reversion Reflecting on 2025, the most notable market characteristic was "divergence." Callahan noted that despite low volatility at the index level, single-stock volatility was extremely high. While tech stocks performed well overall, semiconductors and network infrastructure sectors led by a significant margin, being viewed as the most crowded trades for investors; in contrast, telecommunications, payments, and application software sectors lagged. Looking ahead to 2026, Callahan believes the return prospects for the Nasdaq 100 Index remain solid, but gains may be more concentrated in the first half of the year. This is because the index recently underwent a period of consolidation and faces a "wall of worry," such as concerns about the sustainability of AI spending, which often creates a favorable environment for stocks to climb. Regarding investment themes, Callahan suggests focusing on the "broadening" trade, where capital flows from crowded AI infrastructure stocks to other areas. He believes investors will search for the "second derivative" of AI in 2026—namely, discounted stocks that leverage AI to reduce costs, improve product discovery, or drive new revenue streams, rather than just the hardware providers "selling shovels."