As of 5:45 a.m. ET on Thursday, December 18, 2025, “AI stocks” are living through a familiar whiplash: the long-term narrative (exploding compute demand) is colliding with a near-term market question investors can’t ignore anymore—who pays for the next wave of AI infrastructure, and when do the profits show up?
Wednesday’s U.S. session delivered a clear message: Wall Street is still willing to back AI, but it’s becoming far more selective about where the risk sits—especially when leverage, capex, and multi-year payback periods enter the picture. [1]
Below is a full, publication-ready roundup of the key AI stock news, forecasts, and market analysis moving today (18/12/2025)—and what it may mean for the next trade.
AI stocks today: What just happened in markets, and why it matters
U.S. stocks fell again Wednesday, with AI-linked names among the biggest drags. The S&P 500 fell 1.16% and the Nasdaq Composite fell 1.81%, as investors returned to a theme that has periodically rattled AI leaders: valuation + debt + capex math. Nvidia fell about 3.8%, Broadcom dropped 4.5%, and Oracle slid 5.4%—moves that also pulled the broader chip complex lower. [2]
The framing from market strategists has sharpened: it’s less “AI is over” and more “AI spending is real, but returns are uneven, and the financing is getting complicated.” Reuters quoted Baird’s Ross Mayfield pointing to anxiety over capex levels and the “circular” nature of some AI spending, with OpenAI and mega buildouts at the center of that debate. [3]
That backdrop is why today’s early read matters: the market is splitting AI into winners with near-term cash flow (chips/memory) and higher-risk infrastructure plays (data centers/neoclouds/REIT-like builds). [4]
Micron jolts the AI chip trade: HBM demand is still running hot
If AI sentiment needed proof that demand hasn’t vanished, Micron just delivered it.
Micron shares jumped in early trading after the company issued an outsized profit forecast, highlighting its positioning in high-bandwidth memory (HBM)—a critical component for training and deploying generative AI models. Reuters noted Micron as one of only three major HBM suppliers (alongside Samsung and SK Hynix) and said Micron’s CEO expects memory markets to remain tight past 2026. [5]
Two details from Micron coverage stand out for AI-stock investors:
- Supply remains constrained: management described a situation where the company expects to meet only “half to two-thirds” of demand from several key customers in the medium term, a signal that the bottleneck is still real. [6]
- Capex is rising again: Reuters reported Micron increased its 2026 capex plans to $20 billion as it retools for AI data-center demand. [7]
And the forward-looking “forecast” angle that will get repeated across the AI complex: a Motley Fool write-up (citing Micron’s commentary) described Micron forecasting HBM total addressable market growth to roughly $100 billion by 2028 (from about $35 billion in 2025)—a powerful datapoint for anyone tracking the durability of AI compute buildouts. [8]
Why this matters today: in a tape worried about AI ROI, Micron’s results reinforce that the “picks-and-shovels” layer—especially memory tied directly to GPU/accelerator demand—can still produce near-term profits. [9]
Oracle’s data-center drama is the market’s AI stress test
If Micron represents AI’s cash-generating core, Oracle represents AI’s most controversial question: financing.
Oracle said its talks for an equity deal supporting a Michigan data center project remain on track without Blue Owl Capital, after reports of stalled negotiations hit the stock. Reuters described the project as part of the Stargate AI infrastructure push involving Oracle and OpenAI, with construction slated to begin in early 2026. [10]
Here’s why the story rattled markets:
- The project is massive (Reuters references a more than 1-gigawatt facility), and markets have become sensitive to who holds the equity risk and under what terms. [11]
- Investors are scrutinizing Oracle as its fortunes become increasingly tied to OpenAI and its infrastructure ambitions. Reuters noted Oracle shares have fallen sharply from mid-September highs, and the company has become a lightning rod for concerns about debt-funded AI buildouts. [12]
Other outlets amplified the “balance sheet” angle. Barron’s summarized investor concerns around debt and lease obligations while linking the episode to Oracle’s pressure to execute on large OpenAI-related commitments. [13]
MarketWatch, meanwhile, highlighted analysts arguing the panic may be overdone—but also acknowledged the market’s demand for clearer disclosure and timelines around the OpenAI and data-center pipeline. [14]
Translation for today’s AI-stock tape: the market is still bullish on AI usage, but it’s punishing uncertainty around who finances the buildout and how quickly it translates into cash flow. [15]
Data centers are everywhere—and that scale is now part of the stock story
The “AI infrastructure” trade isn’t just Oracle. It’s also neoclouds, REIT-like builds, utilities, and local politics.
Axios published fresh figures showing the U.S. has 4,149 operational data centers and 2,788 more under construction or planned (as of October 2025, per the report it cited). Virginia and Texas lead in both current and planned capacity. [16]
This matters for AI stocks today because:
- Data-center expansion is a macro tailwind for AI compute supply chains (chips, memory, networking, cooling, power infrastructure).
- It’s also a political and financing headwind, as projects face local pushback over energy use and permitting, and investors increasingly ask whether aggressive buildouts assume an “AI demand curve” that must stay steep for years. [17]
That tension—boom-era construction meets late-cycle skepticism—is exactly what showed up in Wednesday’s selling across AI-linked tech and power names. [18]
OpenAI’s new funding talk adds fuel—and also raises the stakes
One of the most consequential “AI market” stories today isn’t a public-company earnings report. It’s the capital needs of the ecosystem’s biggest demand engine.
Reuters reported OpenAI held preliminary talks about raising up to $100 billion at a valuation around $750 billion, citing The Information. Reuters also said OpenAI is preparing groundwork for a potential IPO that could value it as high as $1 trillion, with a possible filing as early as the second half of 2026. [19]
Why this moves AI stocks today:
- Bull case: More capital for OpenAI signals continued “compute hunger,” which supports demand for hardware, memory, cloud capacity, and data-center buildouts. Reuters explicitly tied the fundraise chatter to the industry’s appetite for computing power. [20]
- Bear case: The bigger the capital raise, the louder the market asks: what’s the business model, and who ultimately earns the ROI—model builders, cloud partners, or chip suppliers? Reuters noted investors remain cautious about indications of cooling demand or heavy investment not paying off as expected. [21]
This is also where the “circular spending” critique comes in: if one part of the ecosystem borrows heavily to build capacity for another part that is also raising capital, markets can start treating the chain as fragile—even if demand is genuine. [22]
Alphabet and Meta take aim at Nvidia’s moat—through software, not silicon
A key AI stock storyline today is not just “who has the fastest chip,” but “who owns the developer ecosystem.”
Reuters reported Google is working on an initiative internally called “TorchTPU” designed to make Google’s TPU chips run PyTorch more smoothly—an effort aimed at reducing reliance on Nvidia’s CUDA ecosystem by lowering switching costs for developers. Reuters also reported Google is working closely with Meta, which heavily supports PyTorch, and that Google is considering open-sourcing parts of the software to accelerate uptake. [23]
This matters for AI stocks today in two ways:
- For Nvidia (NVDA): The company’s strongest “moat” is widely viewed as software and developer lock-in, not just hardware. Any credible attempt to loosen that lock-in becomes a headline risk—even if impact takes time. [24]
- For Alphabet (GOOGL) and Meta (META): It signals hyperscalers are serious about diversifying away from Nvidia where possible, especially for inference costs and negotiating leverage. Reuters described TPU sales as a key growth engine for Google Cloud and said Meta’s interest ties to inference cost reduction and infrastructure diversification. [25]
In Wednesday’s session, Alphabet shares fell after the Reuters report, reflecting how intensely the market is parsing every move in AI infrastructure strategy. [26]
Taiwan’s AI export boom boosts the semiconductor thesis—while geopolitics stays hot
Not all AI-stock news is company-specific. Some of the strongest signals come from economies that sit at the heart of the supply chain.
Taiwan raises growth forecast on AI-driven exports
Reuters reported Taiwan’s central bank raised its 2025 growth forecast to 7.31% (from 4.55% previously), citing booming exports of tech goods to the U.S. and Taiwan’s role producing advanced semiconductors powering the AI boom for companies like Nvidia. Taiwan is home to TSMC, the world’s largest semiconductor contract manufacturer. [27]
Reuters also noted Taiwan’s trade surplus with the U.S. so far this year reached $143.8 billion, more than double last year’s figure, and said the central bank is monitoring U.S. tariff developments (with semiconductors excluded so far). [28]
Reuters: China’s “Manhattan Project” for AI chips
In another geopolitically charged report, Reuters said Chinese scientists built a prototype machine capable of producing cutting-edge chips—an effort described as China’s version of a “Manhattan Project” to rival the West in AI chips. Reuters reported the prototype is operational and generating extreme ultraviolet light but has not yet produced working chips, with a government goal of 2028 and sources suggesting 2030 is more realistic. The report referenced former ASML engineers and the centrality of EUV lithography technology. [29]
Why this matters for AI stocks today: supply chains and export controls remain a long-duration risk factor for semis and semiconductor equipment names—especially where “strategic tech” and national policy overlap. [30]
Regulatory risk shifts from chips to consumer pricing: Instacart faces FTC probe over AI tool
AI-stock investors are also being reminded that “AI” isn’t only data centers and GPUs—it’s pricing engines, personalization, and automation that can attract regulators.
Reuters reported the U.S. FTC is investigating Instacart over concerns tied to its AI-driven pricing tool (Eversight), after a study found different shoppers could see meaningfully different prices for the same items. Reuters said Instacart shares fell around 10% on the news and described a civil investigative demand from the agency. [31]
This matters beyond Instacart: it’s another example of how AI-driven optimization can generate policy scrutiny, which can quickly become a valuation factor for consumer platforms and ad-tech/commerce tech more broadly. [32]
AI education and upskilling is consolidating: Coursera to buy Udemy
One of the most direct “AI is changing real budgets” signals today: companies are still spending on training and workforce transformation—and platforms are reorganizing to capture that demand.
Reuters reported Coursera will acquire Udemy in an all-stock deal valuing the combined firm at about $2.5 billion, with Udemy holders receiving 0.8 Coursera shares per Udemy share. Reuters said the deal is expected to close in the second half of 2026 (subject to approvals) and is positioned around corporate training demand in areas like AI and data science. [33]
Udemy’s investor release framed the transaction as building skills “for the AI era,” reinforcing the narrative that the second-order AI economy (training, enablement, implementation) is still expanding even as markets question infrastructure financing. [34]
Mega-cap AI forecasts: Apple and Meta get fresh “AI upside” calls
Even as the AI trade gets tested, analysts are still publishing forward-looking calls around consumer AI and platform monetization.
- Apple: Investors.com reported Morgan Stanley raised its Apple price target and argued Apple could move from AI laggard to leader in 2026, pointing to expectations around a future Siri upgrade and Apple Intelligence driving upgrade cycles (per the note). [35]
- Meta: MarketWatch cited Rosenblatt Securities naming Meta a top pick for the first half of 2026, with a price target implying significant upside, and tied the thesis to spending discipline and a shift toward AI wearables. [36]
Whether those targets prove right or not, the important “today” takeaway is that the market debate is shifting from “who can build AI” to “who can monetize AI without blowing up margins.” [37]
Additional AI-stock headlines moving today
A few more notable, market-relevant items from today’s newsflow:
- Nvidia settles Valeo trade-secret lawsuit: Reuters reported Nvidia settled a U.S. lawsuit filed by Valeo related to driving assistance technology; details weren’t disclosed. For Nvidia investors, it potentially removes a legal overhang heading into 2026. [38]
- Fermi denies Amazon-tenant report: Reuters reported data-center REIT Fermi denied a report that Amazon was a prospective tenant tied to a stalled Texas project, highlighting ongoing volatility and uncertainty in some AI infrastructure-adjacent names. [39]
- Global “tech jitters” spillover: Reuters described AI infrastructure concerns pressuring global markets, with investors also watching multiple central bank decisions and inflation data. [40]
What to watch next for AI stocks today
With U.S. markets set to open in a few hours, AI-stock price action is likely to hinge on a short list of catalysts:
- Are “AI ROI” fears easing—or spreading? Watch whether capital-heavy names (data centers/neoclouds/infrastructure plays) stabilize after the latest funding headlines. [41]
- Micron’s read-through: If Micron’s guidance holds up through the morning, it may bolster sentiment in AI semis and memory-linked supply chains. [42]
- Any new detail on OpenAI funding or partnerships: More headlines here can quickly swing both the bullish “compute demand” narrative and the bearish “who finances it” narrative. [43]
- Macro data and rates: Investors are watching fresh inflation data and central bank expectations, which can directly impact high-duration growth valuations (including AI leaders). [44]
- Competitive shifts in AI accelerators: Developments like Google’s TorchTPU effort (and broader hyperscaler diversification) will keep Nvidia’s moat conversation front and center. [45]
This article is informational and reflects publicly reported news and commentary as of the timestamp above; it is not investment advice.
References
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