December 22, 2025 is closing out the year with a striking split-screen for investors: artificial intelligence is still the engine behind global equity momentum, while precious metals are suddenly screaming for attention.
On one side, AI-linked stocks helped lift Asian markets at the start of the week, with chip and chip-equipment names in Japan and Taiwan among the notable movers. [1]
On the other, gold and silver surged to fresh all-time highs, powered by rate-cut expectations, safe-haven demand, and a weakening dollar narrative that’s kept commodities in the spotlight. [2]
That tension—“AI as the growth story” vs. “silver as the shock absorber (and maybe more)”—is now shaping how analysts and investors are thinking about 2026. It’s also the backdrop for a sharper question that’s starting to dominate market conversations heading into the new year:
If AI is truly moving from hype to cash flow, where will the profit growth show up first—and which sectors are best positioned to lead?
Today’s headlines that frame the 2026 debate
Several major developments from Dec. 22, 2025 are already influencing how the market is positioning for 2026:
Precious metals break records
Reuters reported that gold crossed $4,400 per ounce for the first time, with spot gold hitting a session record of $4,420.01 and silver printing a record of $69.44 per ounce. Reuters also noted gold’s roughly 68% year-to-date rise and silver’s 139% year-to-date jump. [3]
“AI euphoria” meets valuation reality
A Reuters market commentary warned that U.S. equity valuations look stretched, highlighting that the S&P 500’s Shiller P/E is above 40, near levels associated with the late-1990s dot-com era. The piece also underscored how concentrated the market has become, with the five largest U.S. tech names (including Nvidia, Apple, Alphabet, Microsoft, and Amazon) collectively valued above multiple major benchmarks and national markets, per Goldman Sachs analysis cited by Reuters. [4]
Global equities still follow the AI signal
Associated Press coverage showed markets “mixed,” but reinforced a key point: AI-related sentiment continues to ripple globally, with Asian shares responding to the late-week U.S. rebound and renewed strength in AI-adjacent names (including chipmakers and chip equipment companies). [5]
The “AI trade” broadens beyond chips
Business Insider highlighted a growing theme in institutional circles: the AI boom is real, but the opportunity set extends beyond semiconductors, including “pipes and plumbing” plays such as telecom networks and satellite-related infrastructure. [6]
Taken together, today’s news cycle is delivering a blunt message: AI remains central—but the market is demanding proof of profitable adoption, and it’s increasingly open to alternatives.
AI’s next profit engine: why credit cards and retailers are in the crosshairs for 2026
A Yahoo Finance segment published this weekend explicitly framed 2026 as the year AI could drive profit growth for credit cards and retailers, signaling how mainstream the “AI monetization” narrative has become heading into next year. [7]
Even without relying on a single segment’s thesis, the logic is straightforward: payments and retail sit directly on top of consumer behavior data, transaction flows, and operational complexity—three areas where AI can produce measurable financial outcomes.
Where AI can expand margins in card issuing and payments
For credit card issuers, networks, and fintech platforms, AI-driven profit levers tend to fall into four buckets:
- Fraud prevention and loss reduction
AI systems can flag anomalies faster and reduce false positives, potentially lowering chargebacks and operational overhead. This becomes more urgent as both defenders and fraudsters deploy more sophisticated tools. - Smarter credit underwriting and limit management
AI-assisted risk models can adjust exposure dynamically (within regulatory constraints), potentially improving approval rates while controlling delinquencies. - Personalized offers and rewards optimization
When offers are more relevant, card usage tends to rise—and so do interchange-driven revenues and loyalty economics. - Next-generation customer service automation
AI can deflect routine service interactions and speed up dispute resolution, lowering cost-to-serve.
Retailers: AI isn’t just marketing—it’s inventory, pricing, and conversion
Retail is often described as a “thin-margin” industry. That’s precisely why AI matters: small changes in forecast accuracy, shrink reduction, fulfillment efficiency, and conversion can translate into meaningful earnings impact.
In practice, retailers are pushing AI deeper into:
- Demand forecasting and inventory placement (fewer stockouts, less overstock)
- Supply-chain routing and labor scheduling (lower fulfillment costs)
- Personalized merchandising and recommendations (higher basket size)
- Returns management and fraud detection (lower leakage)
- Assortment optimization (higher gross margin mix)
But there’s also a bright line risk: pricing AI is now under scrutiny. Barron’s recently reported that Instacart’s parent faced an FTC investigation tied to AI-enabled pricing tools, underscoring how quickly “margin tech” can become a regulatory story. [8]
Agentic commerce: the AI catalyst that could connect cards and retail
One of the most important bridges between “credit cards” and “retailers” in the 2026 AI story is agentic commerce—AI systems that don’t just recommend products, but can complete purchases.
Visa has been aggressively pushing that narrative. In its own update, the company said it is working with 100+ partners globally on Visa Intelligent Commerce, with 30+ partners building in its sandbox and 20+ agents/agent enablers integrating, and that the ecosystem has already produced hundreds of controlled, real-world agent-initiated transactions. [9]
A separate industry report echoed the scale of that ambition: Visa expects millions of consumers to use AI agents for holiday purchases by the start of the next year’s holiday season, and cited research indicating 47% of U.S. shoppers already use AI tools for at least one shopping task (like price comparisons or personalized recommendations). [10]
Why this matters for profit growth:
- If AI agents increase conversion and repeat purchase rates, retailers benefit from higher sales efficiency.
- If AI agents reduce checkout friction and improve authorization quality, payments networks benefit from higher transaction volumes and better fraud controls.
- If agents enable “always-on shopping” (subscriptions, replenishment, automated deal hunting), both ecosystems can see more predictable demand.
The catch: agentic commerce only scales if trust, security, and consumer consent are solved—meaning fraud, chargebacks, and identity verification become even more central to the AI roadmap.
The 2026 sector playbook: Technology still leads—healthcare gains momentum
A popular forward-looking take circulating in markets comes from Finbold, which asked OpenAI’s ChatGPT model to identify equity sectors with durable earnings power for 2026. The model’s two picks were:
- Technology
- Healthcare [11]
Why technology keeps the crown (for now)
Finbold’s AI-driven view is that tech remains the “primary engine” because AI adoption continues to drive spending on cloud, semiconductors, and digital infrastructure, including data centers, networking, software platforms, and automation tools. [12]
That argument aligns with a broader Wall Street reality: AI is still in a heavy buildout phase.
Goldman Sachs Research recently reported that the consensus estimate for 2026 capex among hyperscaler AI companies is $527 billion, up from $465 billion earlier in the quarter—another reminder that AI spending forecasts have consistently been revised higher. [13]
But Goldman also flagged a crucial nuance: investors are getting more selective. The firm described rotation away from parts of the AI infrastructure complex where earnings growth is pressured and capex is debt-funded, and pointed to growing focus on AI platform stocks and productivity beneficiaries as the trade evolves. [14]
In other words, “tech leadership” in 2026 may look less like a uniform chip rally—and more like a sorting mechanism between proven monetizers and perpetual spenders.
Why healthcare is suddenly back in the conversation
Finbold argued healthcare combines defensive demand with innovation upside, as AI accelerates drug discovery, diagnostics, personalized medicine, and operational efficiency, potentially opening new revenue streams. [15]
Reuters’ market commentary reinforced this theme with valuation context: it reported that healthcare stocks trade at a 28% discount to global equities, a level seen only twice in 30 years in the columnist’s analysis, and noted that on those prior occasions the sector returned more than 20% over the following 12 months. [16]
Healthcare also sits at the intersection of two investor priorities for 2026:
- fundamental earnings durability, and
- AI-enabled productivity that can be measured in time-to-diagnosis, R&D cycle speed, and administrative cost reduction.
Beyond Nvidia: the “picks-and-shovels” AI trade expands to networks, energy, and utilities
One of the more interesting stories in today’s AI market is how frequently experienced investors are warning that “chips aren’t the whole story.”
Business Insider summarized comments from Diameter Capital’s Scott Goodwin (a credit investor overseeing about $25 billion), who argued the long-run AI opportunity includes less obvious bottlenecks—such as the fiber and network infrastructure needed to move data once AI systems shift from training to large-scale deployment. [17]
Reuters’ market commentary made a parallel point from an equities lens: even within the AI theme, investors can gain exposure via clean energy, grid infrastructure, and utilities that power data centers—often at lower valuation multiples than the most crowded AI names. [18]
This is also where the credit-card/retail AI story connects back to infrastructure: if AI becomes embedded in commerce flows, the “always-on” compute-and-network stack becomes mission-critical, not optional.
“Silver, not silicon”: why 2026 could have a surprising market leader
Against that AI-heavy backdrop, an explicitly contrarian thesis has been gaining attention: the next major market leader in 2026 may not be AI at all—it could be silver.
A Seeking Alpha analysis framed the case directly, arguing silver could offer better 2026 return potential than AI-exposed tech stocks and expressing deteriorating sentiment around the AI trade. [19]
And today’s tape is giving silver advocates fresh ammunition.
Reuters reported silver reached a record $69.44/oz, and emphasized that its sharp year-to-date rise has been driven by a mix of industrial demand, investment demand, and supply constraints—plus macro forces like rate-cut expectations and a weaker dollar. [20]
This matters for the AI narrative in a subtle way: AI isn’t just software—it’s physical infrastructure. Data centers, power systems, electronics, and advanced manufacturing all rely on commodity inputs. If inflation expectations remain sticky or geopolitical risks persist, investors may keep bidding for real assets even while AI remains a core growth theme.
The biggest risks investors are watching into 2026
The emerging 2026 consensus is not “AI is over.” It’s closer to: AI is becoming normal—and that changes how markets price it.
Here are the major risk lines showing up across today’s coverage:
1) Valuation and concentration risk in U.S. equities
Reuters highlighted elevated valuation signals and extreme concentration in mega-cap tech, the exact setup that often increases market fragility if leadership narrows or sentiment shifts. [21]
2) Regulatory scrutiny of AI-driven pricing and consumer outcomes
The Instacart/FTC story illustrates how quickly AI margin tools can move from “innovation” to “investigation,” especially in pricing, discrimination, and transparency debates. [22]
3) Financing and “residual value” risk in the AI hardware cycle
Diameter Capital’s warning about the difficulty of forecasting long-term hardware value speaks to a real issue: if chips age faster than expected, parts of the AI capex cycle could face write-downs, refinancing stress, or repricing. [23]
4) Macro shocks that reward hedges
Today’s precious-metals surge—alongside risk headlines—shows how quickly macro conditions can refocus investors on hedges and liquidity. [24]
What to watch next: the three signals that could decide 2026 leadership
As 2026 approaches, the market is likely to keep rotating between AI optimism and diversification. Three signals could determine which theme dominates:
- Measurable AI profit uplift in consumer-facing sectors (payments, retail, insurance)
Look for margin expansion tied to fraud reduction, conversion gains, and operating expense declines. - The “platform phase” of AI investing
If capex remains high but investors demand higher ROI, platform software and productivity beneficiaries may outperform pure infrastructure plays. [25] - Whether commodities remain structurally bid
If rate-cut expectations, geopolitical stress, and industrial demand persist, silver’s momentum could remain a serious competing narrative. [26]
Bottom line: The 2026 market story is shaping up as a contest between AI-driven profit execution (especially in credit cards and retail), sector rotation into healthcare as both a defensive and innovation play, and precious metals—especially silver—as a breakout “anti-euphoria” alternative. And as today’s news shows, investors are already positioning for all three. [27]
References
1. www.ksat.com, 2. www.reuters.com, 3. www.reuters.com, 4. www.reuters.com, 5. www.ksat.com, 6. www.businessinsider.com, 7. finance.yahoo.com, 8. www.barrons.com, 9. investor.visa.com, 10. www.digitaltransactions.net, 11. finbold.com, 12. finbold.com, 13. www.goldmansachs.com, 14. www.goldmansachs.com, 15. finbold.com, 16. www.reuters.com, 17. www.businessinsider.com, 18. www.reuters.com, 19. seekingalpha.com, 20. www.reuters.com, 21. www.reuters.com, 22. www.barrons.com, 23. www.businessinsider.com, 24. www.reuters.com, 25. www.goldmansachs.com, 26. www.reuters.com, 27. www.reuters.com
