Goldman Sachs analysts predict that mega-cap tech stocks struggling in early 2026 could stage a significant comeback later this year, despite the challenging start for the AI trade. The Magnificent Seven stocks have underperformed the S&P 500 as investors rotate away from big tech, but the investment bank has identified three key catalysts that could restore market leadership for companies like Meta, Microsoft, Amazon, and Alphabet in the second half of 2026.
According to Goldman Sachs, while AI gains are expected to continue broadening beyond mega-cap names in the near term, hyperscaler return dispersion should begin to narrow as specific market conditions materialize. The analysts emphasized that these tech giants maintain strong fundamentals despite recent market weakness.
AI Revenue Growth Could Revive Mega-Cap Tech Stocks
The first catalyst Goldman Sachs identified centers on accelerating AI-related revenue growth among major technology companies. According to the analysts, demonstrating increasing revenue tied to AI investments would ease investor concerns about overspending on artificial intelligence infrastructure and capital expenditures.
The investment bank noted that visible AI revenue growth would provide investors with clarity on the pathway to AI monetization. This transparency would help justify the massive capital spending programs that have raised eyebrows on Wall Street in recent quarters.
Goldman pointed to recent Big Tech earnings as evidence of this dynamic already playing out. While all hyperscalers raised their capital expenditure outlooks, stock market reactions varied significantly based on revenue performance and growth indicators.
Microsoft shares fell following reports of weak cloud growth, while Amazon dropped after providing an inline sales guidance. In contrast, Meta’s stock surged on the strength of its robust advertising revenue and strong revenue outlook, demonstrating that investors reward companies showing tangible AI monetization progress.
Deceleration in AI Spending Growth Expected
The second catalyst involves a projected slowdown in AI capex growth rates. Goldman Sachs expects AI capital expenditure growth to peak in 2026 before beginning to decelerate, which would allow investors to better assess the true earnings potential of these technology companies.
Current hyperscaler spending levels are approaching historic highs, with AI investments on pace to consume 92% of cash flows from operations. This rate exceeds levels seen during the dot-com bubble, raising questions about sustainability and return on investment.
According to the analysts, a deceleration in capital expenditure growth would provide investors with line of sight to a trough in free cash flows. This visibility would enable more traditional earnings-based valuations rather than speculative assessments based primarily on future AI potential.
Market Rotation from Cyclical Stocks May Reverse
The third catalyst Goldman identified relates to broader macroeconomic conditions and sector rotation dynamics. The stock market has recently experienced significant rotation away from tech stocks into cyclical names, partly driven by fears about AI transforming the global economy and potentially displacing established technology leaders.
However, the analysts expect this trend to reverse as economic growth moderates. According to Goldman economists, a shift in the macroeconomic backdrop from accelerating growth to decelerating growth should push investors back toward secular growth stocks like mega-cap tech companies.
Goldman’s economic team forecasts that US economic growth will support cyclical stocks during the first half of 2026. Additionally, they expect these economic growth tailwinds to peak around mid-year before slowing in the second half of 2026, potentially triggering renewed interest in technology stocks.
The timing and magnitude of any mega-cap tech recovery remain uncertain and will largely depend on how these three catalysts develop throughout the year. Investors will be closely monitoring quarterly earnings reports and economic data for signs that the anticipated inflection point is approaching.
