New York — 5:05 p.m. ET, Friday, December 26, 2025. U.S. markets have just wrapped up a light, post-Christmas session, and the “AI trade” is ending the year with the same story investors have been living with since 2023: enormous opportunity, enormous spending, and a growing debate over who captures the profits in 2026. [1]
Wall Street closed nearly flat on thin volume, but the details mattered for AI stocks: Nvidia gained after announcing a Groq-related inference technology move, while investors continued to digest a widening set of crosscurrents—rate-cut expectations, capital spending plans, and signs of rotation away from the most crowded mega-cap tech trades. [2]
Stock market backdrop: Quiet close, “Santa Claus rally” watch, and rate cuts back in focus
In Friday’s muted session, the Dow fell 0.04% to 48,710.97, the S&P 500 slipped 0.03% to 6,929.94, and the Nasdaq declined 0.09% to 23,593.10, according to Reuters. [3]
Strategists also highlighted that the market is still inside the closely watched “Santa Claus rally” window (the last five trading days of the year and the first two of the next). Carson Group’s chief market strategist Ryan Detrick told Reuters the market was “catching our breath” after a strong run and suggested there may be a continued upward bias during this seasonal stretch—while warning investors to expect volatility headlines again in 2026. [4]
Looking into next week, Reuters’ “Week Ahead” preview flagged two market-moving catalysts that can ripple directly into AI stock multiples:
- Fed minutes due Tuesday (from the Fed’s Dec. 9–10 meeting) that could reshape expectations for additional rate cuts. [5]
- Ongoing attention to rate-cut timing and leadership uncertainty at the Fed, which can amplify valuation swings for long-duration growth stocks (including many AI names). [6]
This matters because AI stocks are still priced on long-term growth assumptions. Even small changes in discount rates—or perceptions of “higher for longer”—can move the group quickly.
Top AI headline: Nvidia leans deeper into inference with Groq licensing and executive hires
The biggest single-company AI headline into the close: Nvidia agreed to a non-exclusive license for inference chip technology from startup Groq and is hiring Groq founder/CEO Jonathan Ross and other executives and engineers, Reuters reported. Groq said it will continue operating independently under new CEO Simon Edwards, after earlier market chatter about an outright acquisition. [7]
Why investors care: training is huge, but inference is the next battlefield
Nvidia dominates training workloads, but inference—the day-to-day “serving” of AI models to users—has become the arena where hyperscalers and rivals are pushing alternatives. Reuters explicitly framed inference as the more competitive segment for Nvidia, with AMD and startups like Groq and Cerebras aiming to challenge the incumbent. [8]
Antitrust and deal-structure risk is now part of the AI stock narrative
In a note cited by Reuters, Bernstein analyst Stacy Rasgon warned that antitrust scrutiny is a central risk in the growing trend of “buying talent + licensing tech” without formally acquiring companies—structures increasingly used by Big Tech. [9]
Nvidia rose about 1% on the day in the regular session, Reuters said. In late trading around the close, Nvidia was roughly $190 per share. [10]
The 2026 AI stock thesis, in one line: spending stays hot—investors demand proof of payoff
The most important “AI stocks” question heading into 2026 isn’t whether companies will spend. It’s whether the spending translates into margins, durable cash flows, and broad earnings growth beyond the Magnificent Seven.
A Reuters market outlook piece this week argued 2026 upside depends on three pillars: strong corporate earnings, a dovish Federal Reserve, and continued AI spending momentum. [11]
Forecasts: earnings growth broadens, but expectations are getting harder to beat
Reuters reported that S&P 500 earnings are projected up more than 15% in 2026, citing Tajinder Dhillon, LSEG’s head of earnings research, and that the earnings gap between the “Mag 7” and the rest of the market is expected to narrow. [12]
At the strategist level:
- Sam Stovall (CFRA) told Reuters that to repeat another big year, markets need “everything firing on all cylinders,” and he cited a 2026 year-end S&P 500 target of 7,400 (about 7% above levels at the time of reporting). [13]
- Reuters also noted some strategists’ targets imply 10%+ gains, citing Deutsche Bank’s 8,000 target in that same roundup. [14]
- Kristina Hooper (Man Group) told Reuters that broader earnings participation would help support double-digit returns. [15]
The pushback: AI may be “masking” the economy—and that can flip
A Reuters commentary warned the AI boom has been shielding markets from sharper macro edges, but that reliance cuts both ways if confidence in AI returns or spending falters. The column cited concerns that mega-cap AI spending has made markets more dependent on the theme’s continued credibility. [16]
AI chip stocks: demand is strong, but profitability and supply-chain politics are rising risks
Broadcom: booming AI backlog—plus margin pressure
Broadcom is a key “AI picks-and-shovels” name for custom AI chips (ASICs) and networking. Reuters reported Broadcom projected strong revenue, but warned that margins would dip due to a higher mix of AI revenue. Broadcom CFO Kirsten Spears specifically flagged an expected gross margin decline tied to that mix. [17]
Reuters also highlighted an investor concern that AI customer concentration and a rising share of systems sales could pressure margins, citing Kinngai Chan (Summit Insights) and Gil Luria (D.A. Davidson). [18]
Broadcom was around $352 late Friday.
AMD: MI400 in 2026, bigger “rack-scale” ambitions—and China constraints
AMD is positioning 2026 as a step-up year in accelerator competition. At an analyst day, Reuters reported AMD CEO Lisa Su said the data-center chip market could reach $1 trillion by 2030, driven heavily by AI, and that AMD’s MI400 series is targeted for 2026, alongside a complete server rack system. [19]
But geopolitics remain a tangible risk: Reuters reported Su said AMD has licenses to ship some MI308 chips to China and is prepared to pay a 15% fee to the U.S. government, while also noting China-issued guidance that state-funded data centers should use domestic AI chips—developments that could affect U.S. suppliers. [20]
AMD traded around $215 late Friday.
TSMC and the semiconductor supply chain: AI demand supports forecasts
AI doesn’t ship without capacity. Reuters reported TSMC raised its 2025 revenue guidance on expectations of continued robust AI demand and maintained its 2025 capital spending forecast. For AI stock investors, this supports the idea that the hardware buildout is still broad-based—from foundries to packaging to memory. [21]
Chip equipment: SEMI sees 2026 growth driven by AI logic and memory
Another “AI infrastructure” angle is chipmaking equipment. Reuters reported industry group SEMI forecasts global wafer fab equipment sales rising 9% to $126 billion in 2026, driven by expanding demand for logic and memory chips essential for AI. The report pointed to major suppliers including ASML, Applied Materials, KLA, and Lam Research. [22]
A longer-term wildcard: open-standard chips and RISC‑V pressure
A Reuters Breakingviews analysis argued that RISC‑V—an open-standard architecture—could have a breakout moment as AI reshapes chip design, particularly as firms seek alternatives to entrenched architectures. It also noted Nvidia has said it aims to expand CUDA to support RISC‑V (without a stated timeline), which could eventually broaden the AI software ecosystem beyond today’s dominant chip “languages.” [23]
AI platform stocks: Microsoft–OpenAI, Alphabet capex, and the business model shift
Microsoft and OpenAI: a restructuring path that supports massive capex
On the platform side, Reuters reported Microsoft and OpenAI reached a restructuring deal that refashions OpenAI as a public benefit corporation controlled by a nonprofit, with OpenAI CEO Sam Altman calling an IPO the most likely long-term path given the capital required to train and build AI systems. Reuters also reported Microsoft holds a 27% stake in the OpenAI entity described in the deal. [24]
A separate Reuters deep dive described how the deal was designed to satisfy multiple stakeholders (including regulators) and reflects the scale of capital needed for the next phase of AI infrastructure. [25]
Microsoft traded around $488 late Friday.
Alphabet: AI is driving cloud growth—and forcing capex higher
Alphabet is leaning into AI infrastructure spending as demand accelerates. Reuters reported Alphabet boosted projected 2025 capex to $91–$93 billion, while Google Cloud grew 34%, benefiting from demand for AI-powered infrastructure and analytics, including Vertex AI and its custom chips (TPUs). [26]
Alphabet traded around $314 late Friday.
The financing debate: big capex can mean more debt
Reuters also reported “jitters” have grown around the AI spending story partly because of financing needs—highlighting commentary from Larry Hatheway (Franklin Templeton Institute) and citing a note from Sage Advisory projecting AI capex rising to $600 billion by 2027 and net debt issuance reaching $100 billion in 2026. [27]
The new bottleneck for AI stocks: electricity, data centers, and “all-of-the-above” power
Investors used to treat “AI infrastructure” as chips + servers. In 2025, it’s increasingly chips + servers + power.
Reuters reported that Big Tech expanded beyond renewables into gas and nuclear deals to secure fast access to power generation for data centers—an “all of the above” strategy driven by AI growth. [28]
A separate Reuters report said the International Energy Agency expects global data-center power demand to double by 2030, putting nuclear back into the conversation as firms hunt for reliable, high-output energy sources. [29]
One concrete example: Reuters reported NextEra Energy expanded a partnership with Google Cloud tied to data center scaling and signed clean energy contracts with Meta, illustrating how AI demand is spilling into utilities and grid investment themes. [30]
Caution flag: not every enterprise is ready to absorb AI at hyperscale
Even with surging infrastructure spending, the “ROI timeline” remains a live debate—especially for software and enterprise adoption.
Reuters reported that while executives broadly agree AI is the future, some are reconsidering speed. Forrester predicted that in 2026 companies will delay about 25% of planned AI spending by a year, and Forrester analyst Brian Hopkins told Reuters the narrative of rapid change runs into slower human and organizational adoption cycles. [31]
For AI stock investors, this is a reminder: the infrastructure buildout can remain strong even as software monetization arrives in uneven waves.
Market is closed now: What AI stock investors should know before the next session
As of 5:05 p.m. ET, the NYSE core session (9:30 a.m. to 4:00 p.m. ET) has ended, though after-hours trading can continue into the evening on many venues. [32]
Before the next regular session (Monday, Dec. 29), here are the key things to track:
- Expect bigger swings on smaller volume
Reuters emphasized light trading conditions and noted year-end positioning can exaggerate price moves—especially in crowded AI trades. [33] - Watch rate-cut expectations and Fed communication
Next week’s Fed minutes (Tuesday) could move the entire AI complex by shifting discount-rate assumptions. [34] - Track AI spending “proof points,” not just spending totals
Investors are increasingly focused on whether capex translates into margins and durable revenue—exactly the issue raised in Reuters’ reporting on AI spending jitters and financing. [35] - Regulatory and geopolitical headlines can hit semis fast
Nvidia’s Groq structure highlights antitrust sensitivities, and AMD’s China shipment/licensing framework shows how policy can shape TAM and product strategy. [36] - Don’t ignore “picks-and-shovels” beyond GPUs
Semiconductor equipment forecasts (SEMI via Reuters) and foundry guidance (TSMC via Reuters) point to a broader AI supply chain that can move independently of any single mega-cap narrative. [37]
Bottom line for AI stocks heading into year-end
AI remains the dominant market storyline—powering earnings expectations, pulling forward capital spending, and reshaping M&A and “talent + licensing” deal structures. Today’s Nvidia–Groq news underscores a crucial shift: the next phase of the AI cycle is increasingly about inference at scale, not only model training. [38]
But the 2026 setup is more demanding than the 2023–2024 “easy money” AI narrative: investors are now weighing the cost of the AI buildout (capex, power, financing, margins) against the proof of payback (cash flow and broad earnings growth). The winners may still be the obvious leaders—but the market is signaling it will require clearer evidence, quarter by quarter, that AI spending is turning into sustainable profits.
References
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