Updated: Dec. 25, 2025 | 10:20
U.S. stock markets are closed for Christmas Day, but the AI-stock narrative hasn’t paused. Heading into the holiday, Wall Street finished a shortened Christmas Eve session at fresh records, and much of the day’s “AI stocks” conversation is now being shaped by three forces: (1) Nvidia’s latest talent-and-tech grab via a licensing structure, (2) rising forecasts for 2026 AI infrastructure spending, and (3) intensifying regulatory and geopolitical friction around how AI gets deployed—whether through chips, cloud, or consumer platforms. [1]
Below is the full read on the key headlines and the most widely cited forecasts and analyses circulating on December 25, 2025—and what they imply for the AI stocks trade as the year-end “Santa Claus rally” window begins. [2]
Markets are shut, but AI stocks set the tone into year-end
On Christmas Eve (Wednesday, Dec. 24), U.S. equities ended at record highs in thin holiday trading—an important backdrop because most AI leaders sit inside the same mega-cap and semiconductor clusters that often steer index direction. Reuters reported the Dow and S&P 500 closed at all-time closing highs in the shortened session, with traders pointing to a rebound in AI-linked names as part of the lift. [3]
AP’s market wrap echoed the same closing levels and noted the holiday schedule: U.S. markets closed early on Dec. 24 and remain closed on Dec. 25, with light liquidity expected around year-end. [4]
Why it matters for AI stocks: into the final trading stretch of 2025, price action can be exaggerated (up or down) by low volume. That tends to amplify headline-driven moves—especially in high-ownership AI bellwethers like Nvidia, Microsoft, Alphabet, and Meta.
Nvidia takes another “license + leaders” swing—this time with Groq
The biggest single AI-stock headline dominating Christmas Day coverage is Nvidia’s agreement with AI chip start-up Groq—not as a clean acquisition, but as a non-exclusive technology license paired with the hiring of key executives and engineering talent.
Reuters reported that Groq’s founder Jonathan Ross (a former Google engineer who helped start Google’s AI chip program) and Groq’s president Sunny Madra, along with other engineering team members, will join Nvidia; Groq said it will continue operating independently under a new CEO. [5]
The structure is notable because it mirrors a growing Big Tech pattern: buying capability without technically “buying” the company—often seen as a way to reduce antitrust exposure compared with a full M&A deal. Reuters explicitly pointed to recent examples across Microsoft and Meta, and flagged that regulators have been scrutinizing these talent-and-tech arrangements even when they are not formal acquisitions. [6]
What investors are reading into it today
- Inference is the prize. Reuters described Groq as part of a wave of inference-focused challengers, and noted Nvidia CEO Jensen Huang has been positioning the market shift “from training to inference” as central to Nvidia’s durability. [7]
- Antitrust risk doesn’t disappear—just changes shape. One analyst cited by Reuters argued the licensing structure may preserve the “fiction of competition” even as leadership and technical talent move to Nvidia—language that captures why this style of deal can still draw regulatory attention. [8]
- Competitive pressure is real. Whether from custom silicon inside hyperscalers or from specialized inference players, Nvidia is responding by pulling more of the ecosystem closer—technology, people, and distribution.
Geopolitics stays welded to Nvidia’s China story
Even on a holiday, Nvidia’s China pipeline remains a live catalyst because any change in export permissions can swing expectations around revenue, supply allocation, and pricing power.
Reuters reported Nvidia aims to begin shipping H200 AI chips to China by mid‑February 2026, contingent on Beijing’s approval. The report included details on expected initial shipments from existing stock and framed the move as a major policy shift tied to the Trump administration allowing H200 sales to China with a fee. [9]
Investor takeaway today: Nvidia’s near-term direction is still a blend of product cycle (Blackwell/Rubin vs. Hopper), supply, and policy. When markets reopen, any incremental update on approvals, licensing reviews, or China-side restrictions can move the stock—and often spills over into peers across the AI chip complex.
Intel enters the AI stock conversation again—via politics, industrial policy, and foundry doubts
Intel isn’t the headline “AI winner” of this cycle the way Nvidia has been—but today’s coverage places Intel back in the AI narrative because of how critical domestic manufacturing capacity has become to the U.S. AI supply chain story.
In a Reuters profile published this week and heavily discussed today, Intel CEO Lip‑Bu Tan is described as securing an unusual agreement in which the U.S. government invested $5.7 billion for nearly a 10% stake, giving Intel a “too-strategic-to-fail” aura and potentially reshaping expectations of U.S. industrial policy going forward. [10]
The same Reuters report also delivered a market-moving detail: Nvidia tested Intel’s 18A manufacturing process but “stopped moving forward,” according to sources. [11]
What that means for “AI stocks” broadly
- It underscores a persistent tension: the world wants more AI chips, but the most advanced production still concentrates heavily in a small set of fabs—and customer qualification is unforgiving.
- It also reinforces why “AI stocks” is no longer just a software story. Foundries, packaging, equipment, memory, and power are all part of the same trade.
Big Tech’s AI capex forecasts keep climbing for 2026—and the market is getting pickier
The most important “forecast” theme today is not a single price target—it’s the scale of expected AI infrastructure spend and how unevenly investors may reward it.
Goldman Sachs: 2026 hyperscaler AI capex estimate rises again
Goldman Sachs Research wrote on Dec. 18 that the consensus estimate for 2026 capex among hyperscaler AI companies is now $527 billion, up from $465 billion earlier in the earnings season—continuing a pattern of upward revisions that analysts have repeatedly underestimated. [12]
Just as important: Goldman highlighted that investors are rotating away from AI “big spenders” where operating earnings are under pressure and capex is debt-funded, and expects the next phase of the AI trade to involve AI platform stocks and productivity beneficiaries. [13]
Financial Times: the AI infrastructure era looks bigger—and riskier—than many expected
A Financial Times analysis published today described 2025’s AI boom as dominated by the companies building core AI infrastructure, with projected global spending rising sharply—citing a jump to $470 billion in 2025 and $620 billion in 2026 (attributed in the piece to Morgan Stanley estimates). [14]
The FT also emphasized that today’s enthusiasm comes with echoes of prior cycles (including dotcom-era overbuild concerns), even as power constraints have limited excess supply—so far. [15]
Bottom line: The market is treating “AI spending” less like a blanket positive and more like a question: Who can spend big and still protect margins, execution, and balance sheet flexibility?
Power and data centers: the “hidden” AI stock catalyst that keeps getting louder
If there’s one non-obvious theme that keeps showing up across December 25 coverage, it’s this: electricity and site development are becoming limiting factors for AI growth, not just chips.
Alphabet’s AI power push: Intersect acquisition
AP reported Alphabet agreed to buy Intersect, described as a data center energy specialist, for $4.75 billion to help meet the electricity needs of AI and data centers, with Intersect continuing to operate independently after the deal closes. [16]
Microsoft: more data center buildout
A local business report published today said Microsoft is building another data center in the San Antonio area, including a $400 million colocation center in Medina County projected to complete in 2028—one more datapoint in the long lead-time build cycle behind cloud and AI demand. [17]
Why it matters for AI stocks: Investors are increasingly forced to treat AI scale as a physical build problem. That shifts attention toward utilities, grid constraints, long-term power contracts, and the companies that can finance (or creatively structure) these projects.
Semiconductor equipment forecast: AI demand is pushing the supply chain to record levels
For investors who see “AI stocks” as a full-stack theme (not just Nvidia), the equipment outlook is a major forward indicator—because tools orders often precede capacity coming online.
SEMI said in a December 16 forecast that global semiconductor manufacturing equipment sales are expected to reach $133 billion in 2025, then $145 billion in 2026, and $156 billion in 2027—with growth “driven primarily by investments related to AI,” including leading-edge logic, memory, and advanced packaging. [18]
SEMI also projected wafer fab equipment (WFE) rising to $115.7 billion in 2025 (upwardly revised versus its mid-year outlook), citing stronger-than-expected investment in DRAM and high-bandwidth memory to support AI computing. [19]
This is the quiet reinforcement behind the AI-stock bull case: even as sentiment swings around valuations, the industrial spend forecast remains pointed upward.
Regulation becomes a direct AI-stock catalyst: Meta and WhatsApp’s chatbot gate
AI adoption isn’t only about chips and capex—it’s also about distribution. And distribution is increasingly regulated.
Reuters reported Italy’s antitrust authority ordered Meta to suspend certain WhatsApp contractual terms suspected of restricting rival AI chatbot providers, describing the terms as potentially abusive of dominance and harmful to market access and innovation. Reuters also noted coordination with a parallel European Commission investigation. [20]
Why investors care: Messaging platforms are becoming major “front doors” for consumer and small business AI. Any move to lock down those doors can become an antitrust flashpoint, which in turn can affect product roadmaps, partnerships, and monetization strategy.
What AI-stock investors are watching next
When markets reopen (and liquidity returns), here are the catalysts most likely to shape near-term moves—based on the December 25 news flow and forecasts:
- Deal scrutiny: Whether regulators treat “license + talent” structures as de facto acquisitions (especially when paired with major platform power). [21]
- AI capex credibility: The market is still bullish on AI spending totals, but increasingly judgmental about who spends and how it’s financed. [22]
- China export pathway: Any concrete updates on approvals, conditions, or retaliatory constraints could ripple across semis and cloud. [23]
- The “power bottleneck” trade: More deals like Alphabet–Intersect, more data center permitting headlines, more debate over who gets megawatts first. [24]
- Supply chain confirmation: Equipment and memory investment forecasts are implying multi-year AI buildout—watch for follow-through in orders and guidance. [25]
A note on risk (because Google News readers will ask)
AI stocks have delivered extraordinary returns, but today’s coverage also reinforces the key risks that can reprice the sector quickly:
- Overbuild and ROI uncertainty (especially if usage growth doesn’t match the infrastructure being financed). [26]
- Regulatory interventions that reshape distribution channels, partnerships, or platform access. [27]
- Geopolitical whiplash around exports, tariffs, and cross-border approvals. [28]
- Execution risk in manufacturing roadmaps and foundry competitiveness—where even “tests” and “pauses” can become market events. [29]
Disclosure: This article is for informational purposes only and does not constitute investment advice.
References
1. www.reuters.com, 2. www.reuters.com, 3. www.reuters.com, 4. apnews.com, 5. www.reuters.com, 6. www.reuters.com, 7. www.reuters.com, 8. www.reuters.com, 9. www.reuters.com, 10. www.reuters.com, 11. www.reuters.com, 12. www.goldmansachs.com, 13. www.goldmansachs.com, 14. www.ft.com, 15. www.ft.com, 16. apnews.com, 17. www.expressnews.com, 18. www.semi.org, 19. www.semi.org, 20. www.reuters.com, 21. www.reuters.com, 22. www.goldmansachs.com, 23. www.reuters.com, 24. apnews.com, 25. www.semi.org, 26. www.ft.com, 27. www.reuters.com, 28. www.reuters.com, 29. www.reuters.com
