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AirJoule Has Big Partners—So What's Still Holding the Stock Back?
Author: Thomas Hughes. Posted: 2/23/2026.
Key Points
- AirJoule is a pre-revenue company, making AIRJ stock speculative and highly sensitive to execution and commercialization timing.
- Multiple partnerships support the commercialization narrative, especially around data center cooling and water generation use cases.
- Analyst targets and buying activity suggest upside potential, but the setup depends heavily on validation news and upcoming milestones.
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AirJoule Technologies (NASDAQ: AIRJ) is a risky play: a pre-revenue company that expects to begin sales in 2026. The key questions are whether the company matters, whether its product has utility, and whether the stock is a buy. Based on the technology, applications, partnerships, analyst sentiment, and the charts, AIRJ is a buy — primarily as a speculative investment.
What is AirJoule? It develops materials-based cooling and water-harvesting technology that uses chemical processes rather than pressurized refrigerants.
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AirJoule's technology is claimed to be more efficient and less expensive than traditional cooling and water-harvesting methods, making it applicable across a wide range of use cases.
Key drivers in 2026 include AI and data centers, which demand advanced, efficient cooling and substantial water resources.
The company's partnerships are notable and help position it for commercialization.
AirJoule has a 50/50 joint venture with GE Vernova (NYSE: GEV) to advance manufacturing capabilities, is collaborating with Carrier Global to integrate the technology into next‑generation HVAC systems, is working with BASF on framework systems for the absorption technology, and is a member of the Net Zero Innovation Hub for Data Centers. (The Net Zero Innovation Hub is a collaborative effort to advance data center technology and support net‑zero operations.)
Catalysts for AirJoule in 2026 include product validation and securing inclusion in future data center solutions. The company already works with Google (NASDAQ: GOOGL) and Microsoft (NASDAQ: MSFT) on cooling and water generation capabilities for their properties.
Bullish Analyst Coverage Points to 100% Upside
MarketBeat tracks five analysts covering AirJoule. Four of the five rate the stock a Buy; the lone Sell comes from Weiss Ratings, which is reputable but better known for rating banks, insurers, and cryptocurrencies.
The consensus price target implies nearly 200% upside, with recent revisions generally in the 100%–150% range. Validation from commercial wins or pilot results could attract further coverage, upgrades, and higher price targets.
Institutional and insider buying are also significant. Insiders — who have the closest view of operations — own more than 40% of the stock and bought heavily in Q4 2025 and early Q1 2026. Institutions, which own virtually all remaining shares, have been net buyers since the IPO and increased purchases to record levels in early Q1 2026.
AirJoule Price Action Reflects Robust Support
AirJoule's price action shows a measured decline since the IPO, but the drop has been gradual and accompanied by rising volume — a pattern consistent with accumulation. That suggests buying from analysts, insiders, and institutions has helped establish a firm floor. The stock may trade sideways at current levels until a meaningful catalyst appears; lower lows are not expected. Key support is near the record low of $2.61.
Short interest spiked in February but remains low — under 5% — indicating only mildly bearish sentiment and supporting the constructive outlook.
Risks include execution or technology delays, which could be reflected in the stock price. So long as short sellers don't start piling in, pullbacks could represent entry opportunities. Technical resistance levels to watch are $4.06, $5.70, and $8.50; any of these could trigger volatility or cap near-term gains. The next visible catalyst is the fiscal Q4 2025 earnings report, scheduled for release in late March.
These 5 Stocks Are at the Center of the AI Supply Squeeze
Author: Ryan Hasson. Posted: 2/23/2026.
Key Points
- AI adoption is accelerating globally, but infrastructure buildout is lagging, creating bottlenecks across various industries.
- Companies like SanDisk and Micron are benefiting from supply constraints, which are strengthening pricing power and earnings momentum.
- ASML and GE Vernova sit at critical chokepoints in chip manufacturing and power generation, positioning them to gain as AI demand continues to scale.
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Artificial intelligence continues to dominate headlines, boardrooms, and capital markets. It is not just a buzzword but a structural technological shift reshaping industries in real time. Nevertheless, adoption remains relatively early: research published by Microsoft (NASDAQ: MSFT) finds that only about one in six people currently use generative AI tools. Even so, global AI adoption surged 20% in 2025 to nearly 400 million users worldwide.
That figure highlights two realities: demand is accelerating rapidly, and the runway for further adoption is enormous. While usage is concentrated in developed markets, emerging economies present a major long-term expansion opportunity. As models improve and real-world use cases multiply, AI will likely become more embedded in daily workflows, enterprise systems, and consumer applications.
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With that surge in adoption comes a second-order effect: infrastructure strain. AI models require enormous compute power, memory bandwidth, data storage, specialized chips, and electricity. In several parts of the supply chain, demand is already outpacing supply. When bottlenecks emerge, pricing power often follows.
Here are five stocks positioned at critical pressure points in the AI ecosystem that could benefit from sustained demand and potential supply constraints.
SanDisk: Storage at the Core of AI
SanDisk (NASDAQ: SNDK) has been one of the market's strongest performers this year, after finishing 2025 as the S&P 500's top performer. The company develops NAND flash memory solutions used across data centers, enterprise systems, mobile devices, and edge platforms.
AI workloads are storage-intensive. Training and running large language models requires rapid access to massive datasets, so as hyperscalers and enterprises scale AI deployments, demand for high-performance storage rises in tandem.
Over the past year, a global shortage of NAND flash memory collided with accelerating AI-driven demand, pushing prices sharply higher — NAND prices nearly doubled during the second half of last year. That dynamic created a powerful earnings tailwind.
In its latest quarterly report, released Jan. 29, 2026, SanDisk posted EPS of $6.20, well above analyst expectations of $3.31. Revenue rose 61% year over year to $3.03 billion, beating consensus. Guidance for the following quarter called for revenue of $4.4 billion to $4.8 billion, with gross margins projected at 65%–67%.
With supply still tight and AI-related storage demand growing, SanDisk remains directly exposed to one of the most important infrastructure layers in the AI stack.
Micron Technology: High-Bandwidth Memory Powerhouse
Micron Technology (NASDAQ: MU) is another memory-focused beneficiary of AI-driven bottlenecks. The company is a leading supplier of high-bandwidth memory, a critical component in advanced AI accelerators and GPUs.
High-bandwidth memory enables processors to move vast amounts of data quickly — a necessity for training and inference at scale. Micron is one of only a handful of global suppliers in this segment, giving it meaningful leverage when supply tightens.
Shares have climbed sharply, up roughly 50% this year. In its fiscal first-quarter 2026 results, Micron reported EPS of $4.78, beating expectations of $3.77. Revenue surged nearly 57% year over year to $13.64 billion, topping forecasts.
Analysts expect continued strength, with upcoming estimates forecasting significant year-over-year growth. Institutional ownership remains high, and the stock has attracted substantial net inflows over the past 12 months.
As AI models grow larger and more complex, memory intensity per chip increases, reinforcing Micron's position in a market where supply constraints can translate directly into pricing power.
Nebius: Scaling AI-Native Infrastructure
Nebius Group (NASDAQ: NBIS) provides exposure to another segment of the AI ecosystem: full-stack AI infrastructure. The company offers AI-native cloud services, developer tools, and large-scale data center capacity tailored for training and running models. As enterprises increasingly seek purpose-built infrastructure rather than generic cloud compute, Nebius is expanding aggressively.
The company is targeting 800 megawatts to 1 gigawatt of connected capacity by the end of 2026, with contracted power guidance recently raised to more than 3 gigawatts. That scale matters in an environment where AI data center capacity is increasingly scarce.
In its latest quarterly report, Nebius delivered year-over-year revenue growth of more than 500%, although quarterly revenue slightly missed expectations due to timing-related capacity. Management reiterated its ambitious 2026 annual recurring revenue target of $7 billion to $9 billion and emphasized that demand continues to outpace supply.
Longer-duration contracts, improved pricing, and strong enterprise demand suggest capacity constraints could continue to support favorable economics. Shares have surged more than 100% over the past year, reflecting growing investor recognition.
ASML Holding: The Gatekeeper of Advanced Chips
ASML Holding (NASDAQ: ASML) sits at perhaps the most critical chokepoint in the semiconductor supply chain. The Dutch company manufactures advanced photolithography systems, including extreme ultraviolet (EUV) lithography machines required to produce leading-edge chips. Without ASML's equipment, advanced AI processors cannot be manufactured at scale.
Chip designers may capture headlines, but they rely on ASML's machines to fabricate cutting-edge semiconductors. The company's near monopoly in EUV lithography gives it unique pricing power and strategic importance.
As global demand for AI chips surges, semiconductor foundries must invest heavily in new fabrication capacity, which in turn drives sustained demand for ASML's systems. Shares have rallied strongly over the past year, and analysts remain broadly constructive on the long-term outlook.
GE Vernova: Powering the AI Revolution
GE Vernova (NYSE: GEV) may not design chips or build servers, but it addresses another emerging bottleneck: electricity. AI data centers consume enormous amounts of power. As hyperscalers race to expand capacity, reliable and scalable power generation becomes essential — and in several regions, grid infrastructure is already strained.
GE Vernova designs and services equipment across the power generation and grid value chain, including gas turbines, renewable platforms, and grid modernization technologies. Its positioning makes it a pick-and-shovel play on the physical infrastructure required to sustain AI growth.
The stock has surged more than 130% over the past year and continues to trade with growth-like characteristics. In its most recent quarterly report, GE Vernova significantly exceeded earnings expectations, in part due to a one-off tax benefit, and raised its multi-year outlook. Management projects 2026 revenue between $44 billion and $45 billion, with longer-term expansion targets beyond $56 billion by 2028.
As AI-driven electricity demand accelerates, companies enabling generation and transmission capacity could remain in focus.
Where Demand Meets Constraint
AI adoption is expanding rapidly, but infrastructure buildout is struggling to keep pace. Memory, advanced chips, data center capacity, and power generation are all under pressure.
When demand outstrips supply, pricing power often strengthens. SanDisk and Micron sit at the heart of memory bottlenecks. Nebius is scaling AI-specific capacity in a constrained market. ASML controls essential chip-manufacturing technology. GE Vernova provides the energy backbone that enables AI.
If AI demand remains durable and adoption continues climbing globally, these companies are positioned not just to participate, but potentially to thrive amid the bottlenecks shaping the next phase of the AI revolution.
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