AI Stocks Today: Oracle’s 13% Crash Reignites AI Bubble Fears as Nvidia, AMD and Micron Slide (December 11, 2025)

Artificial intelligence stocks were back in the spotlight on Thursday, December 11, 2025, as a brutal sell‑off in Oracle ignited fresh “AI bubble” worries and knocked many of the market’s biggest AI winners lower.

By mid‑session, the tech‑heavy Nasdaq Composite was down about 1%, the S&P 500 off roughly 0.3%, while the Dow Jones Industrial Average rose more than 1% to a record as money rotated out of AI‑heavy tech into more traditional blue chips. ^[1]

At the center of the storm: Oracle’s earnings, a massive jump in its AI spending plans, and a growing debate about whether the first wave of AI stocks has simply run too far, too fast.

Oracle’s AI Spending Shock Sets the Tone

Oracle’s quarterly results may end up being the single most important AI headline of the day.

The company missed Wall Street forecasts for key revenue metrics and issued a weaker‑than‑expected outlook.
At the same time, Oracle raised its fiscal 2026 AI‑related capital expenditure guidance by about $15 billion, taking its planned spending to around $50 billion. ^[2]

That combination — slower‑than‑hoped growth plus a huge spending ramp — sent Oracle shares down roughly 13–14%, their steepest one‑day fall since the early 2000s. ^[3]

Because Oracle is a crucial cloud and infrastructure partner for OpenAI and other AI players, its results are being read as a real‑world stress test of the AI boom:

Reuters notes that investors are suddenly focused on whether AI infrastructure spending is outpacing the speed at which profits can catch up, with some explicitly drawing parallels to the dot‑com bubble. ^[4]
Credit markets are reacting too: demand for credit‑default swaps tied to Oracle’s debt has surged as traders hedge against its aggressively debt‑financed AI build‑out. ^[5]

In short, Oracle became the poster child for AI valuation anxiety today — and the rest of the AI complex traded accordingly.

How Major AI Stocks Traded on December 11, 2025

Here’s how some of the most closely watched U.S. AI and AI‑adjacent names moved during Thursday’s session, based on intraday and latest available quotes:

Nvidia (NVDA) – Down about 3–3.5% around $177–178 per share.
- A Finviz report attributes the drop largely to spillover from Oracle’s results, which stoked fears that AI infrastructure spending could be unsustainably high and vulnerable to a pullback. ^[6]
- Nvidia remains up strongly year‑to‑date, but today’s move underscores how tightly it’s now tethered to every AI macro headline.
Advanced Micro Devices (AMD) – Down roughly 3%.
- AMD traded lower alongside Nvidia and other chipmakers as investors reassessed short‑term enthusiasm for the AI hardware cycle. A Reuters/Investing.com summary notes AMD among the group of AI chip names falling between about 3.1% and 4.2%. ^[7]
Micron Technology (MU) – Down about 2.7%, but still near record highs.
- Micron has been one of the market’s hottest AI beneficiaries this week, with Investopedia pointing out that its shares recently hit all‑time highs on optimism about high‑bandwidth memory demand for AI data centers. ^[8]
Broadcom (AVGO) – Down roughly 3–4% ahead of earnings.
- Broadcom, another key AI infrastructure name, slipped as traders braced for its post‑close earnings report. Both Investopedia’s pre‑market note and Reuters’ mid‑day wrap highlighted AVGO as an AI bellwether for how sustainable current data‑center spending really is. ^[9]
Arm Holdings (ARM) – Down about 5%.
- ARM, a high‑beta AI‑themed chip IPO from the recent cycle, saw one of the sharpest single‑day drops among major AI‑linked names, illustrating how sensitive newer, richly valued players are to shifts in sentiment. ^[10]
Mega‑cap AI platforms (MSFT, AMZN, META, GOOGL) – Mostly modest declines.
- Investing.com data shows Microsoft, Amazon and Alphabet each off around 1–2%, and Meta down less than 1%, reflecting pressure on AI‑exposed tech broadly — but not outright panic in the largest platforms. ^[11]
Crypto‑linked AI and data‑center names – Also under pressure.
- A Reuters global markets wrap highlights weakness in Bitcoin and related crypto stocks, with shares of companies tied to AI‑heavy data centers and digital assets sliding as the “AI bubble” narrative spilled into other speculative corners of the market. ^[12]

The pattern: high‑beta, AI‑pure‑play and infrastructure names bore the brunt of the selling, while diversified mega‑caps saw more measured pullbacks.

The “AI Bubble” Debate Intensifies

Today’s action didn’t happen in a vacuum. It sits squarely inside an ongoing argument on Wall Street: is AI in a bubble or just experiencing growing pains?

A Reuters special feature updated this morning pulls together views from executives, economists and prominent investors: ^[13]

Some industry leaders — including executives at ABB and SK Hynix — argue there is no AI “bubble” in the real economy, just bottlenecks and resource constraints as trillions of dollars of investment roll out over several years.
Others, like OpenAI CEO Sam Altman, openly acknowledge that investors are over‑excited, warning that “someone is going to lose a phenomenal amount of money” even as others make fortunes.
“Big Short” investor Michael Burry has taken explicit short positions in Nvidia and Palantir, using social media to warn of AI overvaluation.
UBS strategists report that many institutional investors already believe we’re in an AI bubble — but roughly 90% of those same investors are still holding AI‑related positions, betting the bubble has not reached its peak yet.

Against that backdrop, Oracle’s results are being interpreted less as a sign that AI is dead and more as a “show‑me” moment: the market now wants clear evidence that tens or hundreds of billions of dollars in AI capex can convert into earnings, not just headlines.

What Today’s Analysts Are Saying About AI Stocks (December 11, 2025)

Alongside the price action, several high‑profile research pieces on AI names hit the wires today. Here’s a tour through the most notable.

1. Hedge Funds’ Favorite AI Names

Insider Monkey’s “11 AI Stocks Analysts Are Watching Closely” highlights a basket of AI plays popular with hedge funds and Wall Street analysts. ^[14]

Key takeaways:

The piece opens by noting that futures were already under pressure this morning because Oracle, considered an “AI bellwether,” missed revenue expectations and sent its stock down double digits in pre‑market trading. ^[15]
Swissquote strategist Ipek Ozkardeskaya is quoted saying Oracle’s report “confirmed concerns around heavy AI spending financed by debt with an unknown timeline for revenue generation” — essentially the bear case playing out in real time. ^[16]
Morningstar analysts are more nuanced, cautioning that Oracle’s massive data‑center build requires faith that AI demand will stay strong for years, but also arguing that under‑investing now could be a bigger long‑term risk.

The article’s stock list is spread across semiconductors, cloud infrastructure, and application‑level AI, underscoring that hedge funds are still very much engaged in the space despite mounting volatility.

2. Nvidia: Titan of the AI Supercycle

A lengthy deep‑dive on Nvidia (NVDA) published by PredictStreet frames the company as the “trillion‑dollar titan” of the AI revolution and is arguably the most detailed single‑stock analysis of the day. ^[17]

Highlights:

Nvidia now powers over 90% of cloud‑based AI workloads and more than 80% of AI training GPUs, thanks to its dominant data‑center GPU lineup and the stickiness of its CUDA software ecosystem.
The piece notes FY2025 revenue of about $130.5 billion, up 114% year over year, and Q3 FY2026 revenue of $57 billion, up 62% YoY — extraordinary growth even by tech standards. ^[18]
Nvidia’s profitability metrics are eye‑watering: net income approaching $32 billion last quarter and huge free‑cash‑flow generation.
But valuation reflects that strength: the stock is trading around 45x earnings and roughly mid‑20s times sales on trailing metrics, leaving little room for execution missteps. ^[19]

Combined with today’s 3%+ drop on macro AI worries, the message is clear: Nvidia remains the core AI infrastructure winner, but expectations are sky‑high.

3. Nvidia, Micron and Vertiv: “Profitable AI Stocks to Buy for 2026”

A Zacks‑authored note, carried by Nasdaq, focuses on profitable AI‑exposed companies likely to benefit from the sector’s next leg of growth: Nvidia (NVDA), Micron Technology (MU) and Vertiv Holdings (VRT). ^[20]

The report emphasizes:

The global AI market is projected to surge from roughly $372 billion in 2025 to about $2.4 trillion by 2032, a compound annual growth rate above 30%. ^[21]
Nvidia’s trailing 12‑month net profit margin sits near 53%, Micron around 23%, and Vertiv roughly 11% — all firmly profitable, which Zacks argues is crucial as investors become more selective. ^[22]

Zacks’ conclusion: the next phase of the AI trade may favor companies that already generate strong earnings, rather than cash‑burning growth stories.

4. Palantir vs. AMD and Alibaba: Who Wins 2026?

Over on Nasdaq’s platform, a Motley Fool piece makes a bold prediction: two AI stocks — AMD and Alibaba — could be worth more than Palantir by the end of 2026. ^[23]

The article lays out several key points:

Palantir’s stock has been on a three‑year tear, leaving it with a market cap around $448 billion after gains of 167% in 2023, 340% in 2024 and another ~148% so far in 2025. ^[24]
Its fundamentals are undeniably strong — 63% revenue growth and a 51% adjusted operating margin last quarter — giving it a Rule of 40 score well above 100.
But valuation is extreme: Palantir is said to trade at nearly 100x 2026 revenue estimates and ~250x forward earnings, leading the author to argue that even great execution might not justify further big gains. ^[25]

By contrast:

AMD is targeting 60% annual data‑center revenue growth over the next 3–5 years, driven by AI accelerators, with AI‑specific revenue expected to grow ~80% annually. Management believes it can capture at least 10% of the AI compute market by 2030. ^[26]
Alibaba is highlighted for its rapidly expanding AI cloud business in China, with AI services revenue growing at triple‑digit rates and a forward P/E still well below many U.S. AI peers. ^[27]

The thesis: overvalued AI software high‑flyers may give up leadership to better‑priced infrastructure and cloud plays if growth expectations normalize.

5. Nvidia’s “Secret Portfolio” and the Applied Digital Outlier

A 24/7 Wall St. analysis revisits Nvidia’s small equity stakes in a handful of AI infrastructure companies, noting that many of them have stumbled this year — with one notable exception: Applied Digital (APLD). ^[28]

According to the article:

Applied Digital designs and operates high‑performance data centers used for AI and blockchain workloads, including a massive North Dakota campus supporting CoreWeave GPU clusters.
Its latest reported quarter showed 84% year‑over‑year revenue growth to $64.2 million, with losses narrowing and strong demand for AI training facilities. ^[29]
Analysts project roughly 28% EBITDA growth in fiscal 2026 and point to $16 billion in contracted leasesproviding visibility into long‑term revenue — though the stock trades at a rich multiple and still posts GAAP losses. ^[30]

The broader takeaway: “Pick‑and‑shovel” AI infrastructure plays are still capable of big upside, even as flagship AI names wobble.

6. Salesforce (CRM): A Different Kind of AI Winner

Not all AI headlines were negative today. A Finviz summary notes that Cantor Fitzgerald reiterated its “Overweight” rating and $325 price target on Salesforce (CRM), citing upside from the company’s Agentforce AI platform. ^[31]

Key points:

Salesforce has structured its AI pricing around seat‑based editions, pay‑as‑you‑go and pre‑commit options, plus new “Agentic Enterprise License Agreements” (AELAs).
Cantor says 16 AELAs are already in production, each adding more than $1 million in incremental annual recurring revenue, and Salesforce is seeing 10–20 new AI deal opportunities added to the pipeline every week. ^[32]

This highlights a broader theme: AI isn’t just chips and data centers. Enterprise software firms that successfully package AI into recurring‑revenue platforms could emerge as the next set of AI winners.

Funding and Deals: AI Still Raising Big Money

Even as public AI stocks wobble, private markets remain very active:

Harness, an AI‑driven software development platform, raised $200 million in a Goldman Sachs‑led round valuing the company at $5.5 billion, a roughly 49% jump from its last round. Harness helps enterprises automate software release workflows, and major banks like JPMorgan and Citigroup are both customers and investors. ^[33]
Serval, an AI startup focused on IT automation, secured funding that values it at around $1 billion in a Sequoia‑led round, adding another AI “unicorn” to the list. ^[34]
In perhaps the most eye‑catching deal of the day, Walt Disney announced a $1 billion equity investment in OpenAI along with a three‑year licensing agreement that lets OpenAI’s Sora video model use characters from Star Wars, Marvel and Pixar in short‑form AI video content. ^[35]

These deals suggest that, despite public‑market jitters, strategic and venture capital is still flowing aggressively into AI, especially where automation and content creation are concerned.

Macro Backdrop: Fed Cut Supports Risk Assets, But AI Is in “Show‑Me” Mode

Yesterday’s Federal Reserve rate cut — the third in a row, taking the fed funds rate into the 3.5–3.75% range — provided a broadly supportive backdrop for equities. Treasury yields fell again today, with the 10‑year around 4.1%, and the dollar weakened further. ^[36]

However:

Reuters notes that even as global equities edge toward record highs, today’s trading shows investors are increasingly selective, favoring small caps and non‑tech cyclicals while trimming exposure to richly valued AI names. ^[37]
Weekly U.S. jobless claims rose more than expected, providing a mild headwind to risk appetite but also bolstering the case for easier monetary policy in 2026. ^[38]

Put together, the macro backdrop still supports growth and tech — but valuation and profitability now matter more than the AI label alone.

Key Themes for AI Investors After Today’s Sell‑Off

For investors tracking AI stocks, today’s action on December 11, 2025, crystallizes several important themes:

AI Spending Is Moving From “Whatever It Takes” to “Prove It Works”
Oracle’s steep fall shows that markets are no longer rewarding AI capex for its own sake. Investors want to see how tens of billions in data‑center spending translate into revenue and margins — especially when financed with significant debt. ^[39]
First‑Wave Winners Are Volatile but Not Finished
Stocks like Nvidia, AMD and Micron are under pressure today, but their dominant market positions, fat profit margins and ongoing demand for AI infrastructure keep them firmly in the long‑term AI core, according to multiple analyst notes and deep‑dive reports. ^[40]
Valuation Gaps Are Driving a Search for “Second‑Wave” AI Plays
Pieces from Zacks, Insider Monkey and The Motley Fool all point to a rotation toward profitable, reasonably valued AI names — from cloud players like Alibaba to picks‑and‑shovels firms like Vertiv and Applied Digital. ^[41]
Enterprise AI Platforms Are Quietly Building Recurring Revenue
Salesforce’s Agentforce platform, along with similar enterprise offerings, illustrates a less flashy but potentially durable AI business model: embedding AI into subscription software and selling it via long‑term contracts. ^[42]
Private Markets and Strategic Deals Show AI Is Far from Over
From Harness and Serval’s fresh billion‑dollar valuations to Disney’s $1 billion OpenAI deal, capital is still pouring into AI infrastructure, tooling and content — even as public valuations get a reality check. ^[43]

Practical Considerations (Not Financial Advice)

Nothing in this article is individualized investment advice, but if you’re following AI stocks after today’s volatility, some general principles many investors consider:

Look beyond the ticker symbol “AI” – Focus on business models, margins, cash flow and competitive positioning, not just AI branding.
Differentiate layers of the AI stack – Chips, data‑center infrastructure, cloud platforms and end‑user applications all have different risk/return profiles.
Watch balance sheets and funding sources – Debt‑funded AI gambles can be vulnerable if growth disappoints, as the market reaction to Oracle shows.
Expect sharp swings – As Nvidia’s history of frequent 5%+ moves shows, even leaders can be extremely volatile in an AI‑driven market cycle. ^[44]

For now, December 11, 2025, will likely be remembered as the day AI stocks caught another reality check — not because AI is going away, but because the market is finally demanding that the numbers justify the narrative.