Late morning on Monday, December 15, 2025 (around 11:30 a.m. ET), “AI stocks” are once again doing what they’ve done all year: pulling the broader market narrative toward big, fast-moving bets on compute, data centers, and monetization—and then snapping back when investors start asking the same hard question: Where are the profits relative to the spending?
After last week’s sharp shakeout in AI-linked names, U.S. traders started this new week with a cautious rebound in mega-cap tech, while several AI bellwethers remained volatile amid a heavy calendar of economic reports and fresh analyst forecasts for 2026. [1]
AI stocks and the market today: a choppy rebound led by Nvidia and Tesla
In early trading, Wall Street’s major indexes inched higher as investors positioned for a data-packed week and watched whether AI shares could stabilize after last week’s swoon. At 9:35 a.m. ET, the Dow Jones Industrial Average was 48,557.21 (+0.20%), the S&P 500 was 6,849.85 (+0.33%), and the Nasdaq Composite was 23,286.32 (+0.39%), according to Reuters. [2]
AI-linked moves were a key part of that tape:
- Nvidia rose 1.1% and was poised to snap a four-day losing streak if gains held, while a broader chip index climbed 1.2%. [3]
- Tesla jumped 4.5%, powering strength in consumer discretionary. [4]
- ServiceNow slid 7.9% on takeover chatter and downgrade pressure. [5]
The Associated Press also described markets as mixed in morning trading, noting that AI industry stocks were “mixed” following “scary swings last week.” AP highlighted Nvidia up 1.1%, while Oracle fell again and Broadcom slipped. [6]
The takeaway for investors scanning AI stocks today: the market isn’t abandoning the AI theme—but it’s repricing the pace, cost, and payoff timeline of the AI buildout. [7]
Why AI stocks are swinging: the ROI question is back—and louder
Two forces are driving today’s AI-stock mood:
- Macro sensitivity is rising. Investors are bracing for key U.S. data this week—most notably delayed nonfarm payrolls for October and November, plus inflation and other activity reports that could move rate expectations. [8]
- The “AI capex vs. cash flow” debate has intensified. Bridgewater’s Greg Jensen warned Monday that the AI spending boom is entering a “dangerous” phase as Big Tech leans more on outside capital to fund mounting costs, raising the odds the market is approaching a bubble-like setup. [9]
Bridgewater’s note points to a structural tension investors can’t ignore: data centers, power, and chips require massive upfront spending—and markets want clarity on who earns attractive returns after the infrastructure is built. [10]
Nvidia stock today: China demand headlines plus a fresh open-source push
No stock better captures today’s AI crosscurrents than Nvidia—and it’s in the headlines for both hardware demand and software strategy.
1) Reuters: Nvidia weighs more H200 output as China demand builds
Reuters reported that Nvidia has told Chinese clients it is evaluating adding production capacity for H200 AI chips after orders exceeded current output, according to sources. [11]
The report ties demand to a major policy development: Reuters says U.S. President Donald Trump stated the U.S. would allow Nvidia to export H200 processors to China and collect a 25% fee on such sales. However, the Reuters report also notes Chinese government approval was still pending, and Chinese officials had discussed potentially bundling H200 purchases with domestic chip requirements, according to sources. [12]
For AI-stock investors, this matters because it hits three levers at once—volume, geopolitics, and margins—and each one can move semiconductor valuations quickly.
2) Reuters: Nvidia launches Nemotron 3 open-source models
In a second headline, Nvidia unveiled a new family of open-source AI models, the third generation of its “Nemotron” large-language models, aimed at writing, coding, and multi-step tasks. Reuters reported the smallest model (Nemotron 3 Nano) was released Monday, with two larger versions planned for the first half of 2026. [13]
Nvidia framed the models as faster, cheaper, and smarter than prior offerings—an important positioning move as open-source models from Chinese labs proliferate and are increasingly used by developers and companies. [14]
This is also strategically notable because Nvidia is best known for selling the picks-and-shovels (GPUs), yet it’s increasingly trying to anchor an ecosystem—tools, models, and workflows that make the GPU spend “stickier” even as competition grows in custom silicon and inference economics. [15]
Oracle and Broadcom: the AI infrastructure “payoff worries” that won’t go away
Even with today’s bounce in some chip names, investors are still digesting the shockwaves from last week’s AI infrastructure selloff.
AP reported that Monday morning:
- Oracle sank another 4.3% after a 12.7% tumble last week (its worst week in more than seven years, per AP).
- Broadcom fell 2.7%. [16]
The core concern: AI spending may not produce a big-enough payoff in profits and productivity to justify the scale of investment. That fear has become more visible as companies guide to higher capital expenditures, face financing questions, or warn about margin pressure in certain AI product mixes. [17]
2026 forecasts are splitting Wall Street: bullish index targets vs. bubble warnings
One reason AI stocks are so reactive today is that major forecasters are publishing sharply different roadmaps for 2026—and those roadmaps imply very different winners.
Citi: S&P 500 to 7,700 by end-2026, AI still a key theme
Reuters reported that Citigroup set a 2026 year-end target of 7,700 for the S&P 500, citing robust earnings and sustained tailwinds from AI investment. Citi also estimated S&P 500 EPS at $320 by end-2026 (vs. ~ $310 consensus cited by Reuters) and laid out a bull case of 8,300 and bear case of 5,700. [18]
But the most important nuance for AI-stock pickers is Citi’s expected rotation: the firm said the AI infrastructure buildout remains a key theme, while the market focus may shift from AI “enablers” to AI “adopters,” producing a “winner versus loser” dynamic. [19]
In plain English: it may stop being enough to merely sell compute; investors may increasingly reward companies that can turn AI into measurable revenue growth or efficiency gains.
Bridgewater: a “dangerous” phase as external funding rises
Bridgewater’s Jensen warned that with costs rising beyond internal cash flows, companies are turning to outside funding—and cited a UBS report that AI data center/project financing deals surged to $125 billion through November 2025 vs. $15 billion in the same period of 2024. [20]
That’s the kind of acceleration that can support a boom—but also raise fragility if the returns don’t scale with the buildout.
BCA Research via MarketWatch: AI boom could turn to bust in 2026
MarketWatch reported that BCA Research expects the AI investment boom to reverse into a bust next year, arguing capital spending has reached levels comparable to the dotcom era (as characterized in the report) and forecasting large downside targets for major indexes. [21]
Whether or not investors accept that specific forecast, its presence in today’s news cycle helps explain why AI stocks are being traded with a shorter leash: rallies are being sold faster, and guidance-related surprises are being punished harder.
Analyst outlook for AI chip stocks: “best ideas” lists still feature the usual giants
Despite the volatility, bullish analyst notes are still landing—especially for semiconductors.
Barron’s reported that Jefferies analyst Blayne Curtis highlighted Broadcom, Nvidia, and KLA as top semiconductor picks going into 2026, with Buy ratings and targets of $500 (Broadcom), $250 (Nvidia), and $1,500 (KLA), pointing to ongoing AI-driven demand and product cycles (including Nvidia’s roadmap into 2026). [22]
Separately, Investing.com reported Piper Sandler reiterated an Overweight rating and $280 price target on AMD, citing upcoming platform milestones (including Helios expected in mid-2026, per the note) and continued AI accelerator traction. [23]
The message across these calls is consistent: AI chip demand remains real, but the market is increasingly discriminating between (a) durable platform leaders, (b) margin structures, and (c) who captures the next wave of inference and data-center networking spend.
Enterprise AI software stocks: ServiceNow’s deal talk highlights a new risk—AI disruption itself
AI’s impact isn’t confined to chip makers. It’s increasingly colliding with the business models of the software companies that sell automation and workflow tools.
Barron’s reported ServiceNow fell after reports it is nearing a deal to acquire cybersecurity startup Armis for up to $7 billion, alongside a KeyBanc downgrade to Underweight with a $775 target. The analyst cited rising risks to the SaaS model and warned of a potential “Death of SaaS” narrative that’s begun impacting the broader market. [24]
Reuters also flagged ServiceNow’s decline in its market report, linking the drop to a report about advanced talks for the Armis deal. [25]
This is a subtle but important shift for AI-stock coverage in 2025: AI is no longer just a growth driver—it’s also a competitive threat. Investors are now asking which software platforms are being enhanced by AI and which might be commoditized by it.
Palantir stock: government AI demand remains a stabilizer
While some “AI software” stories are about disruption, Palantir delivered a more straightforward catalyst: contract durability.
Palantir announced a three-year renewal of its contract with France’s domestic intelligence agency (DGSI), extending a relationship that dates back nearly a decade, according to a company press release distributed via Business Wire. [26]
For investors, the relevance is simple: in a market that’s nervous about AI ROI, multi-year government renewals are the kind of visibility that can support a premium—especially when many AI narratives depend on future adoption curves.
Tesla stock and “AI autonomy”: robotaxi testing heats up, and Waymo looms large
If Nvidia is the face of AI compute, Tesla is increasingly being traded as a high-beta bet on AI autonomy.
Reuters reported Tesla shares hit their highest in nearly a year after CEO Elon Musk said Tesla was testing robotaxis without safety monitors in the front passenger seat; Musk also posted that “testing is underway with no occupants in the car.” [27]
Reuters added key context: Tesla’s limited robotaxi service in Austin launched earlier in 2025 with geo-fencing and a human safety monitor, while Alphabet’s Waymo remained the market leader with more than 2,500 commercial robotaxis and roughly 450,000 paid rides per week (as reported by CNBC and cited by Reuters). [28]
For AI-stock investors, the autonomy trade is compelling—but it’s also where execution risk, regulation, and competition can swing valuations dramatically.
What to watch next for AI stocks this week
With AI stocks sitting at the intersection of mega-cap positioning and macro rate expectations, the next catalysts aren’t only product announcements—they’re also economic prints.
Reuters noted investors are monitoring:
- Delayed nonfarm payrolls data for October and November (Tuesday)
- Additional reports on business activity, weekly jobless claims, and inflation later in the week
- A slate of Fed official remarks [29]
AP also highlighted the week’s major economic releases and explained why they matter: markets are trying to infer whether the Fed is more constrained by labor weakness or inflation persistence—an important sensitivity for high-duration growth stocks, including many AI leaders. [30]
Bottom line: AI stocks are shifting from “buy everything” to “prove it”
Today’s AI-stock tape isn’t just about whether AI is “real.” The market broadly agrees the AI buildout is real. What’s changing is the pricing mechanism:
- Capex is no longer assumed to be value-creating by default. [31]
- Roadmaps and adoption matter more—from Nvidia’s model ecosystem push to Tesla’s robotaxi testing claims. [32]
- 2026 forecasts are diverging, which typically keeps volatility elevated. [33]
For investors and readers tracking AI stocks on the U.S. market today, the story of December 15, 2025 is clear: the AI trade isn’t over—but it’s growing up fast.
References
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