AI stocks are heading into the final stretch of 2025 with a familiar contradiction: demand signals still look strong, but the market’s tolerance for “priced-for-perfection” narratives is thinning fast. On Tuesday, December 23, the AI news cycle hit nearly every layer of the stack—chips, cloud, data centers, power, autonomous systems, and even the legal plumbing underneath generative AI.
Below is a comprehensive roundup of the key AI-stock headlines dated Dec. 23, 2025—plus what they mean for investors watching Nvidia, Microsoft, Alphabet (Google), Amazon, Meta, AMD, Broadcom, Taiwan’s chip ecosystem, and China’s rapidly scaling AI complex.
The big picture: AI spending is enormous—and it’s still accelerating
One number helps explain why AI stocks remain the gravitational center of global markets: Goldman Sachs estimates the major AI “hyperscalers” spent nearly $400 billion on AI-related capex in 2025 and could spend almost $530 billion in 2026. [1]
That kind of money doesn’t just buy GPUs. It buys data centers, networking, power contracts, batteries, cooling, and the increasingly scarce commodity tying the whole boom together: electricity.
Demand check: Taiwan’s export orders surge on “robust AI demand”
A fresh macro datapoint out of Taiwan reinforced the “AI demand is still real” side of the tug-of-war.
Taiwan said November export orders rose 39.5% year over year to $72.92 billion, the fastest growth in nearly five years and well above the 30.1% increase forecast in a Reuters poll. Telecom orders jumped 69.4% and electronic products rose 47.9%, as AI and high-performance computing demand stayed strong into year-end. [2]
Why AI-stock investors care: Taiwan is home to TSMC—still the most important manufacturing chokepoint for cutting-edge chips. When Taiwan’s export-order engine is humming, it’s often a tell that the AI hardware pipeline (servers, boards, networking gear, components) is still pulling hard.
Now the catch: the same report flagged uncertainty around trade policy and geopolitics. [3] The AI trade is increasingly a story of demand growth colliding with political friction.
AI capex goes global: ByteDance plans a massive 2026 AI infrastructure push
One of the most market-moving themes for AI stocks in 2025 has been the sheer concentration of spending among a few U.S. giants. Today’s news shows the capex wave is widening.
TikTok owner ByteDance is planning 160 billion yuan (about $22 billion) in capital expenditures for 2026, with a large share tied to AI infrastructure and AI chips, according to Reuters reporting. [4]
ByteDance isn’t a public stock, but this matters for publicly traded suppliers across the AI value chain:
- Semiconductors and accelerators (where global supply is strategic and politically sensitive)
- Server manufacturing and component ecosystems
- Data-center power, cooling, and grid upgrades
- China’s domestic AI hardware and cloud ambitions
The investment implication is not “everyone wins,” but rather: AI demand is no longer a purely U.S.-hyperscaler story. The buyer universe is broadening—while the geopolitics around who can buy what, and from whom, keeps getting sharper.
Data centers and power: the AI boom’s least glamorous bottleneck becomes the star
If 2024–2025 was the era of “GPU scarcity,” late 2025 is increasingly the era of “power scarcity.” Two major Dec. 23 stories underline that the market’s AI center of gravity is shifting toward infrastructure.
Goodman + CPP Investments launch a A$14 billion European data-center partnership
CPP Investments and Australia’s Goodman Group announced a A$14 billion (€8 billion) European data center partnership, structured 50/50, with an initial capital commitment of A$3.9 billion (€2.2 billion) to develop projects in Frankfurt, Amsterdam, and Paris. The initial portfolio includes four projects totaling 435 MW of primary power and 282 MW of IT load, with construction starts enabled by secured power connections and permits and targeted commencements by June 30, 2026. [5]
Reuters framed the same deal as a deeper push into Europe’s fast-growing AI infrastructure market. [6]
Why this is AI-stock relevant:
- It reinforces that data-center capacity is being financed like a strategic asset, not just real estate.
- It supports the broader thesis behind data center operators, electrical equipment suppliers, and grid-adjacent industrials that have become “AI picks-and-shovels.”
- It also hints at a 2026 dynamic investors will be forced to price: who gets power first—and how expensive that power becomes.
Alphabet buys clean-energy developer Intersect in a $4.75B deal amid AI push
Alphabet announced it will acquire clean energy developer Intersect for $4.75 billion in cash plus assumed debt, as Big Tech spends aggressively to expand the computing and power capacity needed for AI. Reuters said Intersect has $15 billion of assets operating or under construction, and projects representing about 10.8 gigawatts of power are expected to be online or in development by 2028. [7]
This is the AI-stock story hiding in plain sight: the winners of the next phase may not be the companies with the flashiest models, but the ones that can reliably secure energy + land + permits + transmission—and do it faster than their rivals.
Rotation risk (and opportunity): investors look to Chinese AI as U.S. bubble fears grow
One of the most consequential “AI stocks today” headlines wasn’t about a new model release—it was about capital flows.
Reuters reported that global investors are increasing bets on Chinese AI companies, seeking the “next DeepSeek” and diversifying as concerns grow about a speculative bubble in U.S.-listed AI stocks. The story highlighted blockbuster debuts by Chinese chipmakers Moore Threads and MetaX, and noted interest in Chinese tech platforms and chip supply chains via names like Alibaba, Baidu, Tencent, and SMIC, as well as China-focused ETFs including KWEB and CNQQ. [8]
Key market takeaway: even investors who remain bullish on U.S. frontier AI are increasingly treating geographic diversification as a risk-management tool—especially as AI becomes a geopolitical race rather than just a product cycle.
But Reuters also included a caution from fund managers: some newly listed Chinese chipmakers are being valued more on excitement than fundamentals. [9] That’s not a China-only issue—it’s the AI trade’s universal tax.
The hidden risk to watch in 2026: depreciation accounting becomes a Wall Street talking point
Every bull market has a moment when investors stop asking “how fast is it growing?” and start asking “how real are the earnings?” On Dec. 23, Reuters highlighted a debate that sounds dull—but can move multi-trillion-dollar stocks.
A Reuters commentary said investor chatter about big tech depreciation schedules is a “hidden risk” into 2026, pointing to criticisms—popularized by Michael Burry—suggesting companies like Nvidia (and also Oracle) may be using long depreciation periods that can make profits look higher in the near term. The column also noted that several “Magnificent Seven” companies have extended assumed useful lives of certain assets amid surging capex since 2020, and warned that with tech stocks priced for perfection, intensified scrutiny could trigger reassessments. [10]
Important nuance: depreciation is mostly an accounting representation, not a cash outflow, and the Reuters piece explicitly said there’s no indication of fraud. [11]
Why it still matters for AI stocks: the AI era is capex-heavy. The more the market focuses on return on invested capital, free cash flow, and “how long does this hardware stay economically useful,” the more accounting assumptions can become catalysts—especially during thin-liquidity periods or when macro sentiment turns.
Legal and safety headlines add pressure to the AI narrative
AI stocks don’t just trade on demand—they trade on whether the underlying AI systems can be deployed at scale without exploding into lawsuits, recalls, or regulatory lockdowns. Dec. 23 brought multiple reminders.
Copyright lawsuit names Google, OpenAI, Meta, Anthropic, Perplexity—and xAI
Reuters reported that investigative journalist and author John Carreyrou, along with five other writers, sued xAI, Anthropic, Google, OpenAI, Meta, and Perplexity, alleging the companies used copyrighted books without permission to train AI systems. Reuters noted the case is the first to name xAI as a defendant and that the plaintiffs are not pursuing a class action. [12]
For public-market investors, this is part of a larger, unresolved question: how expensive does “clean” training data become, and does the industry migrate toward licensing, synthetic data, or new legal frameworks? Each path has margin implications.
Amazon’s Zoox recalls 332 vehicles over automated driving software error
Reuters reported Amazon’s self-driving unit Zoox is recalling 332 U.S. vehicles due to an automated driving system software issue that could cause vehicles to improperly cross the center line or stop in the path of oncoming traffic near intersections; the company issued a free software update. [13]
This isn’t about generative AI hype—it’s about the reality that “AI in the real world” comes with regulator-grade consequences. For AI-adjacent stocks in autonomy and robotics, safety credibility is part of the valuation.
Samsung’s Harman buys ZF’s ADAS business for $1.8B
Samsung Electronics said its Harman unit will acquire German supplier ZF Friedrichshafen’s advanced driver assistance systems business for 1.5 billion euros (about $1.77B–$1.8B), securing technologies like front-facing vehicle cameras and ADAS controllers. Reuters quoted Samsung projecting the ADAS and central vehicle controller market could grow from 62.6 trillion won in 2025 to 97.4 trillion won in 2030. [14]
Translation for investors: while AI “software” gets the headlines, the next scale wave in automotive AI will be won by whoever controls reliable sensor stacks, compute, and integration—areas where Samsung is clearly trying to buy time and capability.
What this means for AI stocks: the trade is broadening—and getting more complicated
The Dec. 23 news cycle points to three investor realities likely to define AI stocks into 2026:
AI is no longer a single bet on a single company. The market is treating AI as an ecosystem spanning chips, clouds, data centers, energy, and industrial infrastructure. Deals like Goodman/CPP and Alphabet/Intersect show that investors may need to track power capacity as closely as model benchmarks.
Valuation debates are evolving from “growth vs. growth” into “capex vs. returns.” When hyperscalers are spending hundreds of billions annually, the market will increasingly reward evidence of monetization and punish signs of diminishing returns—or even just a lack of clarity.
Geopolitics and law are now part of AI fundamentals. Capital is flowing toward China’s AI complex partly because investors want diversification. At the same time, export controls, trade policy, and copyright litigation can all become material risks, not background noise.
AI stocks in focus today: the names investors are watching most closely
This isn’t a recommendation list—think of it as the “AI headlines are most likely to touch these tickers” map:
- AI chips & compute: Nvidia, AMD, Broadcom, (and the Taiwan supply chain led by TSMC) [15]
- Cloud & model platforms: Microsoft, Alphabet (Google), Amazon, Meta [16]
- Data centers & power: Goodman Group (ASX: GMG) and infrastructure partners; plus power-linked spending trends across Big Tech [17]
- China AI exposure: Alibaba, Baidu, Tencent, SMIC, and China-tech ETFs used for theme access [18]
- Autonomy and automotive AI: Amazon (Zoox), Samsung (Harman/ADAS) [19]
Bottom line
AI stocks today are being pulled by two forces at once: continued, global-scale demand (Taiwan’s orders, ByteDance capex, hyperscaler spending) and mounting skepticism about what all that spending ultimately produces (returns, accounting optics, litigation risk, safety realities). The next leg of the AI trade won’t be decided purely in GPU specs—it will be decided in power availability, deployment at scale, and the cold, boring math of cash flow.
References
1. www.reuters.com, 2. www.reuters.com, 3. www.reuters.com, 4. www.reuters.com, 5. www.cppinvestments.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.reuters.com, 13. www.reuters.com, 14. www.reuters.com, 15. www.reuters.com, 16. www.reuters.com, 17. www.cppinvestments.com, 18. www.reuters.com, 19. www.reuters.com
