Shares of CoreWeave fell as much as 10% in extended trading on Thursday, as investors focused on margin pressure and aggressive capital spending plans, even after the artificial intelligence-focused cloud infrastructure provider posted stronger-than-expected fourth-quarter revenue.

The company reported revenue of $1.57 billion, ahead of the $1.55 billion forecast by analysts polled by LSEG. Revenue grew 110% year over year, underscoring the intensity of demand for AI compute capacity.

CoreWeave posted a loss per share of 89 cents for the quarter. Adjusted earnings before interest, tax, depreciation, and amortization came in at $898 million, below the $929 million consensus from StreetAccount, suggesting profitability metrics lagged revenue expansion.

The mixed performance came against a backdrop of heightened investor sensitivity toward AI-linked stocks, following recent developments at Anthropic that triggered sharp selling across segments of the sector.

Nvidia supply constraints and massive capital push

CoreWeave’s business model remains tightly intertwined with Nvidia, whose graphics processing units power most advanced AI workloads. CEO Mike Intrator told analysts on a conference call that Nvidia’s chips remain in short supply.

Average prices for Nvidia’s H100 processors in the fourth quarter were within 10% of where they began the year, while older A100 prices increased in 2025, Intrator said. The pricing stability for H100 chips, despite supply constraints, indicates sustained demand from hyperscalers and AI model developers.

CoreWeave is leaning heavily into expansion. The company plans to target at least $30 billion more than its 2025 capital expenditures for 2026. For 2025, total capex stood at $10.31 billion. That scale of projected investment signals an aggressive build-out of data center infrastructure, even as financing conditions remain tight and debt levels elevated.

As of Dec. 31, CoreWeave carried $21.37 billion in debt, a substantial balance for a company that went public just last March. The leverage underscores the capital-intensive nature of AI infrastructure and may partly explain the market’s cautious reaction despite revenue growth.

Power capacity — a critical constraint in AI infrastructure — continues to expand. CoreWeave ended the year with 850 megawatts of active power capacity, above the 827 megawatts analysts had projected. Contracted power reached 3.1 gigawatts, and the company aims to add more than five gigawatts beyond its current contracted footprint by 2030.

The scale of that ambition reflects a long-term bet that demand for AI compute will continue to accelerate, driven by large language models, enterprise AI deployment, and inference workloads.

Backlog surge, competitive positioning, and sector divergence

CoreWeave’s revenue backlog swelled to $66.8 billion from $55.6 billion at the end of the third quarter, providing visibility into future cash flows. The backlog growth suggests customers are locking in long-term compute commitments amid persistent chip scarcity.

The company supplies AI model developers such as Google and OpenAI, placing it at the center of the generative AI ecosystem. During the quarter, CoreWeave also announced a deal with model builder Poolside and launched an object storage service, broadening its product suite beyond pure GPU compute.

The storage offering positions CoreWeave to compete more directly with established hyperscalers, including Amazon Web Services, though the company remains primarily a specialist in high-performance AI cloud infrastructure.

It also increased a credit facility to $2.5 billion from $1.5 billion, bolstering liquidity as it ramps up capital expenditures.

“In 2025, CoreWeave became the fastest cloud platform in history to surpass $5 billion in annual revenue,” Intrator wrote in a blog post, highlighting the speed of the company’s scale-up.

Despite Thursday’s after-hours decline, the stock had risen 36% so far in 2026 as of the regular session close. That performance contrasts sharply with the nearly 22% drop in the iShares Expanded Tech-Software Sector Exchange-Traded Fund over the same period, signaling that investors have differentiated between AI infrastructure providers and broader software names.

Still, the earnings reaction suggests that growth alone is no longer sufficient. Investors are weighing capital intensity, chip supply constraints, debt levels, and margin trajectories more closely as the AI trade matures.

Executives are scheduled to discuss results and provide guidance on a conference call beginning at 5 p.m. ET.

A global race to build out artificial intelligence infrastructure is now colliding with the consumer electronics market, and smartphones are emerging as one of the first casualties.

The International Data Corporation (IDC) projects that global smartphone shipments will plunge 12.9% this year to 1.12 billion units, down from 1.26 billion devices shipped in 2025. If realized, it would mark the steepest annual contraction in more than a decade, a stark reversal for an industry that had been stabilizing after years of post-pandemic volatility.

At the center of the disruption is a severe shortage of RAM, driven by surging demand from AI-focused data centers and high-performance computing environments. Memory manufacturers are reallocating capacity toward high-margin server-grade DRAM and high-bandwidth memory (HBM), components essential for training and running large AI models. Smartphones, which rely heavily on commodity DRAM, are being squeezed out in the process.

“The memory crisis will cause more than a temporary decline; it marks a structural reset of the entire market, fundamentally reshaping long-term TAM (Total Addressable Market), the vendor landscape, and the product mix,” said Nabila Popal, senior research director with IDC’s Worldwide Quarterly Mobile Phone Tracker.

Her framing points to more than a cyclical downturn. For years, the smartphone market has been defined by incremental innovation, longer replacement cycles, and intense price competition. Now, input cost inflation is colliding with maturing demand, forcing a reassessment of volume expectations and profitability models.

Prices rise, consolidation looms

IDC expects smartphone average selling prices (ASP) to climb 14% this year to a record $523. The pricing surge reflects both higher memory costs and the broader inflationary pressures embedded in semiconductor supply chains.

“We expect consolidation as smaller players exit, and low-end vendors face sharp shipment declines amid supply constraints and lower demand at higher price points. Although shipments will witness a record drop, Smartphone ASP is projected to rise 14% to a record $523 this year,” Popal said.

The squeeze is particularly acute in the entry and mid-tier segments, long considered the volume backbone of the industry. These devices operate on thin margins and are highly sensitive to component cost swings. When memory prices spike in multiples, vendors face a binary choice: pass costs on to consumers or downgrade specifications.

Carl Pei, co-founder and CEO of Nothing, underscored the pressure facing manufacturers.

“Brands now face a simple choice: raise prices by 30% or more in some cases, or downgrade specs. The ‘more specs for less money’ model that many value brands were built on is no longer sustainable in 2026,” he said.

He added that “some markets, particularly entry and mid-tier segments, are likely to shrink by 20% or more, and brands that have historically dominated these segments will struggle.”

The comment signals a broader shift in competitive dynamics. Smaller brands without scale advantages or long-term supply agreements may struggle to secure memory at viable prices. Larger vendors with diversified portfolios and stronger balance sheets are better positioned to absorb volatility, potentially accelerating consolidation across the Android ecosystem.

Emerging markets under strain, relief distant

IDC forecasts that the Middle East and Africa will see shipments fall by more than 20% year-over-year. China is projected to decline 10.5%, while Asia Pacific (excluding Japan and China) is expected to drop 13.1%.

These regions are critical to global volumes. In many of them, smartphone penetration remains below saturation levels, and growth has historically been driven by affordable devices. A double-digit contraction there suggests that price sensitivity is already biting.

Higher ASPs in cost-conscious markets risk elongating replacement cycles even further. Consumers may delay upgrades, opt for refurbished devices, or shift toward older models with discounted pricing. That dynamic could dampen the industry’s long-term Total Addressable Market, reinforcing IDC’s “structural reset” thesis.

The outlook also diverges sharply from earlier projections. Last year, Counterpoint estimated a relatively modest 2.6% decline in shipments. IDC’s 12.9% forecast highlights how rapidly the memory supply-demand equation has tightened, largely due to the intensity of AI-related capital expenditure.

IDC expects RAM prices to stabilize by mid-2027, implying that the industry could face at least another year of elevated component costs. Until then, smartphone makers will operate in an environment where volume growth is constrained not by lack of consumer interest in connectivity, but by competition for silicon from AI infrastructure.

The broader signal is that capital and capacity are migrating toward AI. As hyperscalers and enterprises pour billions into data centers, semiconductor supply chains are being reprioritized. Smartphones, once the dominant driver of semiconductor demand, are now competing with AI workloads for the same memory resources.

In one of the most aggressive workforce reductions in the fintech sector this year, Block said it will eliminate more than 4,000 roles — nearly 40% of its global staff — as part of a structural reset aimed at embedding artificial intelligence deeper into its operations.

The announcement, made alongside fourth-quarter earnings, sent the company’s stock up more than 24% in extended trading, reflecting investor approval of a strategy that pairs margin expansion with technological automation.

Chief Executive Jack Dorsey described the decision as deliberate and forward-looking rather than reactive.

“Today we shared a difficult decision with our team,” Dorsey wrote in a letter to shareholders. “We’re reducing Block by nearly half, from over 10,000 people to just under 6,000, which means that over 4,000 people are being asked to leave or entering into consultation.”

As of Dec. 31, 2025, Block employed 10,205 people worldwide, according to its annual filing.

AI as Operating Model, Not Just Tool

Block Chief Financial Officer Amrita Ahuja said the job cuts are intended to position the company “for our next phase of long term growth,” adding that the company is “choosing to shift how we operate at a time when our business is accelerating and we see an opportunity to move faster with smaller, highly talented teams using AI to automate more work.”

The framing underscores a broader recalibration underway across corporate America: artificial intelligence is no longer confined to product innovation but is reshaping organizational design. Rather than trimming around the edges, Block is resizing its workforce to align with what Dorsey called “intelligence tools” that can absorb functions previously handled by human teams.

In a post on X, Dorsey said he weighed the option of spreading layoffs over time but rejected that path.

“Repeated rounds of cuts are destructive to morale, to focus, and to the trust that customers and shareholders place in our ability to lead,” he wrote.

He went further in his shareholder letter, predicting that the shift will not be isolated. “Within the next year, I believe the majority of companies will reach the same conclusion and make similar structural changes,” Dorsey said.

Several technology firms have recently attributed job reductions directly to AI-driven efficiency gains, including Pinterest, CrowdStrike, and Chegg. Block’s move stands out for its scale and the explicit linkage between automation and headcount compression.

The restructuring comes as Block’s core business shows resilience. The company reported adjusted earnings per share of 65 cents on revenue of $6.25 billion for the fourth quarter, essentially matching analysts’ expectations for earnings and slightly surpassing revenue estimates, according to LSEG. Gross profit climbed 24% year over year to $2.87 billion.

For the full year, Block projected adjusted earnings per share of $3.66, well above the $3.22 analysts had anticipated.

The scale of the workforce reduction is particularly notable given the earnings backdrop. Rather than responding to declining revenue, Block is compressing costs during a period of gross profit growth. That approach suggests management is prioritizing operating leverage and long-term margin expansion over short-term stability in headcount.

The company expects to record $450 million to $500 million in restructuring charges, primarily tied to severance, benefits, and non-cash share-vesting expenses. Most of those charges will be incurred in the first quarter.

For investors, the calculus is straightforward: if AI-driven automation allows Block to sustain revenue growth with materially lower operating expenses, margins could widen significantly. At the same time, the cuts raise questions about execution risk. Rapid downsizing can strain product development cycles, compliance operations, and customer support — areas central to a payments platform handling billions of dollars in transactions.

Block has spent years evolving from a payments processor into a broader financial services ecosystem spanning merchant tools, consumer finance, and digital assets. A leaner organizational structure may sharpen that focus, but it also represents a decisive bet that AI systems can shoulder a meaningful share of internal workflows without undermining service quality or innovation speed.

The market’s immediate reaction signals confidence in that bet. But analysts believe the gains proving durable will depend on how effectively Block translates workforce compression into sustained margin expansion while maintaining growth momentum.