U.S. markets are closed for Christmas, but the AI stock conversation is anything but quiet. After the Dow and S&P 500 finished at record highs in a shortened Christmas Eve session, investors are heading into the final stretch of 2025 and the opening weeks of 2026 with one question front and center: does the AI trade have another leg higher—or does the bill for all that infrastructure spending finally come due? [1]
On Dec. 25, three storylines dominate the “AI stocks” landscape:
- Nvidia’s new move in inference via a licensing-and-talent deal with AI chip startup Groq. [2]
- A fresh regulatory flashpoint for Meta after Italy’s antitrust authority ordered it to halt WhatsApp terms that could lock out rival AI chatbots. [3]
- Wall Street’s 2026 outlook, which increasingly hinges on whether corporate earnings can keep up with the scale—and financing structures—of the AI buildout. [4]
Below is what’s driving headlines today, what analysts are forecasting for 2026, and how investors are thinking about the next phase for AI stocks across chips, cloud, software, and the companies trying to monetize AI before capex fatigue sets in.
1) Nvidia (NVDA) and Groq: a deal that signals the next battleground—AI inference
The biggest AI stock headline on Dec. 25 is Nvidia’s agreement to license inference chip technology from Groq while also bringing Groq’s founder/CEO Jonathan Ross and other key leaders and engineers into Nvidia. Nvidia confirmed the licensing arrangement; Groq says it will continue to operate independently. [5]
Why this matters for AI investors:
- Inference is where the puck is moving. Training giant models made Nvidia the defining AI stock of this cycle—but the industry’s growth is increasingly shifting toward running models in production, at scale, with low latency and high efficiency (inference). Reuters notes Nvidia faces much more competition in inference than in training, with AMD and startups like Groq and Cerebras pushing hard. [6]
- It’s another “deal-spree” template: pay for technology and talent without a full acquisition. Reuters places the Nvidia-Groq structure in a broader pattern of Big Tech deals designed to capture talent and IP while potentially reducing antitrust friction compared with outright takeovers. [7]
- A reminder that “AI chips” are fragmenting into categories. Groq’s approach (including SRAM-based on-chip memory as described by Reuters) underscores that performance and architecture choices for inference don’t always look like training accelerators. That opens doors for specialized players—and raises the strategic premium for incumbents like Nvidia to absorb innovation quickly. [8]
Even in holiday-thinned trading, the market treated the news as strategically significant. Investor’s Business Daily framed the Groq arrangement as acquiring key technology and personnel rather than a full takeover. [9]
Near-term catalyst: Nvidia’s CES 2026 moment
Nvidia is also heading into a highly visible early-January catalyst: CES 2026, where CEO Jensen Huang is expected to discuss business outlook and roadmap items (including industrial AI and computing infrastructure themes). IBD highlighted the setup heading into CES and noted investor focus on technical levels and positioning. [10]
2) Meta (META) and WhatsApp: Italy’s antitrust order puts AI distribution under a spotlight
For AI stocks, “distribution” is becoming as important as model quality. That’s why Meta’s WhatsApp-related regulatory fight matters.
Reuters reports that Italy’s antitrust authority (AGCM) ordered Meta to suspend contractual terms that could prevent rival AI chatbots from operating on WhatsApp, as it investigates Meta for potential abuse of dominance. Meta called the decision “fundamentally flawed” and said it will appeal, according to Reuters. [11]
Why markets care:
- WhatsApp is a potential AI gateway—especially for consumer-facing chatbots, assistants, and business messaging automation. If regulators force open access, Meta may face constraints on how tightly it can bundle or privilege “Meta AI” in a messaging ecosystem. [12]
- Europe remains a tougher rule-set than the U.S. on Big Tech conduct, and Reuters notes the Italian probe has a parallel EU angle. For investors, that adds a persistent risk premium to AI monetization strategies that rely on platform gatekeeping. [13]
This story is a good reminder: in 2026, AI stock winners may not simply be the companies with the biggest models or the most GPUs—they’ll be the companies that can distribute AI at scale without triggering regulatory tripwires.
3) The AI capex supercycle into 2026: forecasts are massive—and investors are getting pickier
The most important “AI stocks” driver is still spending: data centers, chips, networking, power, and the software stack needed to deploy models in real businesses.
Reuters: AI spending is one of the swing factors for 2026 market returns
In a year-end markets analysis, Reuters argued that a “stellar” 2026 would likely require strong earnings, a dovish Fed, and strong AI spending—and warned that if companies pull back on previously guided capex, confidence in the AI return-on-investment story could crack. [14]
In other words: AI spending is now a macro variable, not just a tech-sector storyline.
Goldman Sachs: 2026 hyperscaler capex estimate rises to $527 billion
Goldman Sachs Research puts a number on what “big” looks like: it cites a $527 billion consensus estimate for 2026 capital spending for the hyperscaler AI cohort, up from $465 billion earlier in the year, and notes analysts have repeatedly underestimated AI capex in recent years. [15]
Goldman also points to a key market dynamic investors should take seriously going into 2026: dispersion. It argues investors are increasingly rewarding companies that show a clearer link between AI spending and revenue, while being more skeptical of debt-funded spending where operating earnings growth is under pressure. [16]
Financial Times: $620B global spending forecast for 2026—and OpenAI’s infrastructure ambitions
A separate macro datapoint comes from the Financial Times, which highlighted projections of global AI data center spending reaching $470 billion in 2025 and $620 billion in 2026, citing Morgan Stanley estimates, while also describing OpenAI’s ambitions around large-scale data center buildout. [17]
Financial Times: AI data center debt is being structured in new ways
The “how” of financing is becoming part of the AI stock thesis. The FT reported that major tech players and AI infrastructure firms have shifted over $120 billion of AI data center debt off their balance sheets via special purpose vehicles—structures that can help preserve credit optics but may obscure risk if AI demand slows. [18]
Investor takeaway: In 2026, it may not be enough to ask “who’s spending?” Investors are increasingly asking “who’s spending efficiently—and who’s carrying hidden leverage?”
4) AI stocks in focus: what today’s headlines imply for 2026 winners and losers
A) AI chips and inference: Nvidia’s crown is still heavy—competition is sharpening
Nvidia remains the bellwether AI stock, and today’s Groq move is best read as both defensive (protecting inference share) and offensive (absorbing talent and IP quickly). [19]
But investors are also tracking geopolitics. IBD highlighted Nvidia’s China-facing dynamics (including discussion around H200 and future timelines) as part of what traders are watching. [20]
What to watch into 2026:
- Inference economics: serving costs, latency, memory bandwidth, and power efficiency
- Competitive architectures: GPUs vs ASICs vs newer inference-specific designs
- Supply chain + export policy: where and to whom next-gen silicon can be sold
B) Cloud and AI infrastructure: the “returns on capex” debate is the real catalyst
The clearest message from Reuters and Goldman is that AI spending itself won’t automatically lift all AI stocks. Investors are increasingly sorting the market into:
- companies that can translate AI investment into near-term revenue and margin durability, and
- companies where the spending story looks riskier or more leveraged. [21]
C) Oracle (ORCL): the high-beta “AI infrastructure” stock with a debt narrative
Oracle is a prime example of how the AI trade has broadened beyond chips. Barron’s described Oracle’s volatile 2025, including investor sensitivity to debt, margins, and the implications of very large AI-related contracts tied to OpenAI. [22]
Whether you’re bullish or skeptical, Oracle reflects a broader 2026 theme: AI infrastructure winners may look less like classic software margin machines—and more like capital-intensive builders and landlords of compute.
D) Software and “next beneficiaries”: Datadog (DDOG) and The Trade Desk (TTD) show how messy the second phase can be
Not every AI story in 2025 produced a clean stock chart. A Dec. 25 commentary piece syndicated on Nasdaq argued that Datadog and The Trade Desk are among the AI-linked names that have pulled back sharply from prior highs—and framed that drawdown as a possible setup for 2026 if fundamentals catch up. [23]
You don’t have to buy the conclusion to see the signal: the AI trade is branching beyond hardware and hyperscalers into software, adtech, observability, cybersecurity, and workflow automation—but the market is demanding proof.
5) Another AI stock pipeline signal: IPOs may return in 2026
One of the more underappreciated “AI stocks” angles today is what’s coming next.
Investopedia reported that Motive Technologies, an AI-powered fleet management software company backed by Google Ventures, has filed for an IPO (NYSE symbol: MTVE). The report also notes broader expectations for an improved 2026 IPO environment and highlights how AI-branded offerings could become a major theme if risk appetite holds. [24]
Why this matters for public-market AI investors:
- A healthier IPO market often signals broader risk-on sentiment
- New listings can create fresh comps (and valuation pressure) for existing AI software names
- AI IPOs can either validate demand—or expose how hard monetization still is outside the hyperscalers
6) The biggest risks for AI stocks heading into 2026: regulation, geopolitics, and capex fatigue
Today’s news flow makes the 2026 risk map unusually clear:
Regulation risk is moving from “privacy” to “AI access and competition”
Meta’s WhatsApp issue is not just a headline—it’s a template for what can happen when a platform’s distribution power meets AI assistants and bots. [25]
Geopolitics is now a product roadmap issue
From export policy to regional supply constraints, the AI chip story is deeply political. Investors aren’t just valuing GPUs; they’re valuing where GPUs can be shipped and deployed. [26]
Capex fatigue is the market’s main “AI bubble” pressure valve
The “AI bubble” debate in late 2025 isn’t only about valuations—it’s about whether the spending wave can keep compounding without a confidence shock. Reuters explicitly flags that if companies pull back on capex guidance, markets could reassess the AI return profile quickly. [27]
What AI stock investors are watching next
With U.S. markets reopening after the holiday, the next actionable catalysts are straightforward:
- Early January positioning as liquidity returns and investors rebalance for the new year
- CES 2026 headlines, especially Nvidia’s roadmap signals and any new enterprise/industrial AI narrative traction [28]
- 2026 capex guidance season, where hyperscalers and AI infrastructure firms will have to defend spending plans with clearer ROI language [29]
- Regulatory developments in Europe, which could shape how AI assistants are distributed inside major platforms [30]
Bottom line
As of Dec. 25, 2025, the AI stock story is evolving from a single-track “GPU boom” into a multi-front market:
- Nvidia’s Groq move reinforces that inference is now the fiercest competitive arena. [31]
- Meta’s WhatsApp fight shows AI distribution is becoming a regulatory battleground. [32]
- 2026 forecasts point to extraordinarily large AI capex totals—but with investors increasingly selective about who deserves a premium multiple. [33]
This article is for informational purposes only and does not constitute investment advice.
References
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