AI stocks

Wolfspeed directly reported that AI data-center revenue more than doubled in fiscal 2026.

BizLink’s Q2 growth was directly attributed to AI infrastructure and capital equipment, with HPC and SPE rising to 56% of revenue.

Coherent supplies 800G and 1.6T optical transceivers required by AI clusters.

Revenue is heavily driven by optical transceivers and components sold directly for hyperscale cloud networks and AI clusters.

Caterpillar is directly exposed through generator production, a large backlog, and a disclosed factory expansion aimed at data-center power demand.

Veeco directly captures capex as it receives orders for its advanced packaging and lithography systems from specialist foundries.

SK Hynix’s HBM and advanced-memory demand is directly linked to AI accelerators and hyperscaler infrastructure.

SCREEN's SPE business is the primary direct exposure in the event, and management cited approximately 20% WFE growth plus AI, memory, and logic demand.

AI semiconductor revenue grew 143% and now represents nearly half of total revenue.

Large AI clusters require high-speed switching, networking ASICs, and increasingly co-packaged optics. Broadcom is identified as one of the leading CPO and switch-chip vendors, creating incremental demand exposure, although adoption timing remains uncertain.

Advantest directly captures AI semiconductor capex through testers for increasingly complex AI SoCs, DRAM and HBM products.

The expansion of AI-chip packaging and testing capacity increases demand for high-throughput ATE, handlers and thermal-control systems. Advantest is identified as a leading tester and has platforms designed for large AI-oriented packages, creating indirect equipment revenue upside.

Backlog growth is explicitly driven by technology-load infrastructure and grid modernization for AI.

Samsung captures AI-capex spending through HBM, server memory, NAND, foundry, and related capacity expansion.

Amkor is also investing in advanced packaging capex and is highly aligned with AI and HPC packaging ramps.

Continued AI investment can increase outsourced assembly, advanced packaging and testing volumes for accelerators and HBM. The downside is that an AI-capex slowdown would reduce or postpone outsourced backend demand.

OpenAI's reported revenue acceleration and planned compute expansion increase demand for AI accelerators, networking, and complete systems. NVIDIA is a leading accelerator supplier, although HBM, advanced packaging, power, and custom-silicon constraints can delay shipment conversion.

NVIDIA Corporation stands as a prominent provider of advanced graphics, computational, and networking solutions, operating across the United States, Taiwan, China, and numerous international markets. Its Graphics division encompasses GeForce GPUs, central to PC gaming and personal computing experiences, along with the GeForce NOW cloud gaming service and its supporting infrastructure, as well as dedicated solutions for various gaming platforms. For professional visualization, it provides Quadro and NVIDIA RTX GPUs for enterprise workstations, further offering vGPU software designed for cloud-centric visual and virtual computing, automotive platforms for in-vehicle infotainment, and the Omniverse software suite, facilitating 3D design and virtual world creation. The Compute & Networking segment is a cornerstone for AI, high-performance computing (HPC), and accelerated data center platforms. It integrates Mellanox networking and interconnect solutions, delivers automotive AI Cockpit technologies, fosters autonomous driving development through strategic agreements, and offers comprehensive autonomous vehicle solutions. This segment also manufactures cryptocurrency mining processors, supplies Jetson platforms for robotics and other embedded applications, and offers enterprise AI software, including NVIDIA AI Enterprise. These diverse offerings find widespread application across the gaming, professional visualization, data center, and automotive sectors. NVIDIA distributes its portfolio through a broad ecosystem, engaging original equipment and device manufacturers, system integrators, add-in board makers, retail channels, software vendors, internet and cloud service providers, automotive companies (both manufacturers and tier-1 suppliers), mapping firms, nascent technology ventures, and other industry stakeholders. A notable strategic partnership exists with Kroger Co. Founded in 1993, NVIDIA Corporation maintains its corporate headquarters in Santa Clara, California.

Surging demand for AI training and inference compute drives massive record data center revenue growth for AMD's Instinct GPUs and server CPUs.

Generac has direct exposure to data-center generator production, backlog, and capacity expansion, capturing the adjacent backup-power portion of the buildout.

The plan is partly justified by AI data-center load growth, reinforcing demand for backup, prime-power, and microgrid equipment where grid connections are delayed or reliability requirements are high. Generac has a disclosed data-center generator backlog and is expanding large-generator capacity, although the Canadian plan does not specify a purchase.

Freshworks has a clear tiered monthly subscription pricing model that monetizes its Freddy AI agents.

Data center and custom AI silicon are the primary growth engines, representing over 70% of sales.

Supplies the optical networking components critical for interconnecting large-scale AI clusters.

High direct exposure as power solutions for AI data centers serve as the primary growth driver, backed by multi-year capacity reservation agreements.

Accelink is a listed optical-module supplier exposed to 800G and 1.6T AI-network deployments.

Connecting 10,000- and 100,000-card clusters requires high-speed optical transceivers, optical circuit switches, and fiber interconnects. Accelink is identified as a Chinese supplier of 800G and 1.6T transceivers and optical switching hardware, giving it direct networking-capex exposure.

Vertiv's order backlog is surging due to the specialized cooling needs of high-density AI clusters funded by Microsoft.

Several gigawatts of new AI compute require high-density power distribution, liquid cooling, racks, and thermal-management systems. Vertiv directly supplies this infrastructure, so successful financing and deployment can increase orders and backlog, subject to power availability and construction timing.

Vertiv Holdings Co, headquartered in Columbus, Ohio, is a global provider of essential digital infrastructure technologies and comprehensive lifecycle services. The company specializes in the design, manufacturing, and servicing of critical systems vital for data centers, communication networks, and diverse commercial and industrial applications. Its extensive product range encompasses AC and DC power management, thermal control solutions, integrated rack systems, modular designs, and sophisticated management platforms for monitoring and governing digital environments. These solutions are fundamental to the operation of numerous modern services, including e-commerce, online banking, file sharing, video on-demand, energy storage, wireless communications, the Internet of Things, and online gaming. In addition to its hardware offerings, Vertiv delivers a full spectrum of lifecycle management services. These include professional deployment, ongoing maintenance, and optimization, supported by predictive analytics. Specific service capabilities extend to preventative maintenance, acceptance testing, engineering and consulting, performance assessments, remote monitoring, training, spare parts, and specialized critical digital infrastructure software. Vertiv's products are marketed under prominent brands like Liebert, NetSure, Geist, E&I, Powerbar, and Avocent. The company serves a wide array of sectors such as social media, financial services, healthcare, transportation, retail, education, and government. Its global reach spans the Americas, Asia Pacific, and Europe, the Middle East, and Africa, facilitated by a robust network of direct sales professionals, independent representatives, channel partners, and original equipment manufacturers.

Tokyo Electron captures AI capex through deposition, etch, coat/develop, cleaning, and related process equipment used in memory and foundry expansion.

Tokyo Electron supplies process equipment to memory manufacturers and advanced-packaging firms. Rising AI-memory capex should support orders for etch, deposition, and related production tools.

ASE can capture AI capex through outsourced assembly, testing, and advanced-packaging overflow capacity.

More AI accelerators and HBM content increase demand for outsourced assembly, advanced packaging, and testing. ASE can benefit if captive backend capacity remains constrained.

Extremely high backlog and revenue exposure to grid power delivery, switchgear, and transformers needed to power modern AI campuses.

Eaton provides critical power distribution equipment, backup power systems, and control software necessary to manage grid-to-chip power fluctuations. Large gigawatt-scale data center facilities require extensive switchgear, transformers, and UPS systems to handle high-current demands and stabilize power surges, boosting Eaton's industrial AI backlog.

Arista is a major switch vendor directly driving and supplying AI datacenter networking demand that requires 800G and 1.6T optics.

Networking is a critical 'pick-and-shovel' for AI clusters, seeing increased revenue targets.

Ciena’s 1.6T coherent and optical transport products are directly complementary to the fiber capacity being built for AI data-center interconnection.

Ciena is the direct beneficiary of the development: its Q3 growth and raised FY26 guidance indicate stronger demand for its optical transport and high-speed connectivity systems, particularly for AI infrastructure and cloud-provider data-center interconnects.

AI accelerator and server deployment increases demand for high-bandwidth memory and other memory components.

More enterprise inference capacity requires high-bandwidth memory and server memory in accelerator systems. Micron can benefit from incremental HBM volume, product mix, and pricing if the reported Copilot spending translates into higher model-serving workloads.

Revenue is increasingly driven by advanced packaging and transistor scaling for AI chips.

The stronger AI-memory signal increases the probability that memory producers expand DRAM, HBM and advanced-packaging capacity. Applied Materials supplies deposition, etch, CMP and related tools, so it can capture delayed wafer-fab and packaging capital expenditure.

Meta's future monetization is expected to be 'agentic' and usage-based, though it currently bears the cost of the compute.

Meta's AI infrastructure buildout directly supports demand for HBM and DRAM.

Azure can monetize inference workloads, while GitHub Copilot and other developer products can capture agent usage.

The rapid shift toward agent-based development expands demand for both Azure inference capacity and integrated developer tooling. Microsoft can monetize the infrastructure layer through Azure and the workflow layer through GitHub, which is adding agentic workflows and coding-agent capabilities. The benefit is moderated by competition among Microsoft, standalone agents, and other cloud providers.

AI-compute expansion requires Schneider’s power-management, distribution, automation, and cooling products, creating second-order equipment revenue.

Schneider supplies electrical distribution, automation, power management, busway, and cooling systems for high-density AI facilities. The stronger long-term deployment outlook supports infrastructure backlog, while grid and project delays can defer revenue conversion.

ASML captures a portion of AI capex through demand for EUV lithography equipment needed to expand leading-edge logic capacity.

The AI-supported semiconductor-capex channel increases demand for advanced-node lithography as foundries and memory producers expand capacity. ASML benefits from this structurally supported investment, although extended equipment lead times and fab execution can defer revenue recognition.

ASML Holding N.V. provides lithography solutions for the development, production, marketing, sales, upgrading, and servicing of advanced semiconductor equipment systems. The company offers lithography, metrology, and inspection systems. It also provides extreme ultraviolet lithography systems; and deep ultraviolet lithography systems comprising immersion and dry lithography systems solutions to manufacture various range of semiconductor nodes and technologies. In addition, the company offers metrology and inspection systems, including YieldStar optical metrology systems, a diffraction-based wafer metrology platform to assess the quality of patterns on the wafers; and HMI electron beam solutions to locate and analyze individual chip defects. Further, it provides computational lithography solutions, and lithography systems and control software solutions; and refurbishes and upgrades lithography systems, as well as offers customer support and related services. Additionally, the company offers hardware, software, and services to chipmakers to produce the patterns of integrated circuits. It operates in Japan, South Korea, Singapore, Taiwan, China, rest of Asia, the Netherlands, rest of Europe, the Middle East, Africa, and the United States. The company was formerly known as ASM Lithography Holding N.V. and changed its name to ASML Holding N.V. in 2001. ASML Holding N.V. was founded in 1984 and is headquartered in Veldhoven, the Netherlands.

Cisco is a major networking-system vendor exposed to the AI-driven expansion of high-speed optical interconnects.

The construction surge is a leading indicator for subsequent installation of networking equipment inside new AI facilities. Cisco already recorded substantial hyperscaler AI-infrastructure orders, with a significant portion tied to optics, providing a direct equipment-demand pathway.

Fabrinet assembles optical modules whose volumes are driven by the 800G and 1.6T AI-networking ramp.

Fabrinet benefits as a contract manufacturer and optical-module assembler when AI networking vendors increase production of 800G and 1.6T systems. Arista's larger multiyear component commitments and higher shipment outlook can increase manufacturing throughput and demand for specialized optical assembly, although the company remains dependent on customer program timing.

Cummins India has direct backup-generation exposure because AI data centers require redundant power systems to maintain uptime.

BESI captures AI capex indirectly through advanced-packaging equipment used for die attach and hybrid bonding.

BESI is the direct beneficiary of the new information: Q3 orders reached €342.6 million versus a €298 million estimate, with orders up 96% year over year. Continued AI-capacity investment should support additional die-attach, thermocompression, and hybrid-bonding equipment orders.

Oracle can monetize agentic workloads through OCI and token- or outcome-oriented pricing embedded in enterprise applications.

Oracle's transition to prepaid 'token bundles' and outcome-based pricing allows the firm to monetize its massive AI infrastructure build-out more effectively, securing upfront capital and reducing friction for AI adoption across its Fusion application suite.

IBM can monetize enterprise inference deployment through watsonx, governance, and integration services, giving it meaningful but indirect sensitivity to model usage.

A revenue reset at a frontier model provider can shift enterprise demand toward governed, auditable, hybrid, and open-model deployments. IBM can capture this through watsonx, governance, integration, security, and consulting without bearing the same frontier-model infrastructure burden.

Revenue is increasingly driven by AI server assembly, and China is a significant hub for this demand.

Tower manufactures silicon-photonics PICs used in 1.6T optical transceivers, giving it direct foundry exposure to AI optical demand.

Innolight supplies optical transceivers used in high-speed AI-cluster networking and can benefit from related network-product procurement.

The target requires networked accelerator clusters rather than isolated servers, increasing demand for 800G, 1.6T, and future co-packaged optical links. Zhongji Innolight is identified as a leading optical-transceiver supplier with 1.6T production and CPO capability, providing direct exposure to AI-networking demand.