24 AI Stocks Explained in Plain English
Updated July 29, 2026 using data from Koyfin. This is an educational overview, not a big list of stocks to buy right now. Always do your own research or talk to a financial advisor before buying anything.
People talk about AI stocks all the time, and the media's obsessed. So it's easy to want to start buying these wild stocks, even if you don't know what they actually do.
That's why we're breaking down 24 key AI stocks in plain English. Take your time reading this. There's a lot of ground to cover since the AI supply chain is absurdly complex.
Building and running applications like ChatGPT, Claude, Gemini, and Grok takes a massive supply chain: chips, cloud computing, software, networking, cooling, and of course, electricity. That's why everything from GPU makers to memory producers to nuclear power companies gets lumped into the “AI stocks” category.
Below are 24 companies across that entire chain, grouped by what they actually do, explained without the jargon (or at least minimizing it). We've also included some helpful stats for each one like the current stock price, market cap, recent performance, distance from its 52-week high, the average Wall Street price target, and short interest.
These numbers were last updated on July 29, 2026, so keep that in mind.
🧠 Part 1: The Chipmakers (the “brains” of AI)
These companies make the physical processors that train and run AI models. Without them, there's no AI boom.
1. Nvidia (NVDA)
Nvidia is pretty much THE flagship AI name. This Mag 7 name makes the GPUs (graphics processing units) that have become the industry standard for training and running AI models like ChatGPT. Originally built to power graphics in high-powered gaming PCs, these chips turned out to be awesome at AI math. Nvidia is the single most important hardware company in the AI world right now, and most of the biggest AI buildouts run on its chips.
📊 Stock Price: $194.13 | Market Cap: $4.70T | 1-Mo performance: -0.4% | YTD Performance: +4.2% | Below 52-Wk High: -17.9% | Analyst Target: $302.83 (+56% implied return) | Short Interest: 1.3%
2. Advanced Micro Devices (AMD)
AMD is Nvidia's main rival in AI chips, just as it is in PC GPUs. AMD makes its own line of AI accelerators (called Instinct) and has landed major deals, including a huge multi-year agreement to supply GPUs to Meta (META). AMD isn't likely to dethrone Nvidia anytime soon, but it gives big tech companies a second supplier so they're not fully dependent on one vendor.
📊 Stock Price: $444.05 | Market Cap: $724.1B | 1-Mo performance: -17.7% | YTD Performance: +107.3% | Below 52-Wk High: -24.1% | Analyst Target: $575.49 (+30% implied return) | Short Interest: 2.6%
3. Broadcom (AVGO)
Broadcom doesn't sell off-the-shelf chips. It's best known for making Google's TPU processors, and also co-designs custom AI chips for other customers like Meta, and OpenAI. This lets those companies get chips tailor-made for their own AI workloads instead of using general-purpose GPUs. Broadcom's AI chip and networking business has grown explosively, and management has talked about reaching $100 billion in annual AI-related revenue.
📊 Stock Price: $380.02 | Market Cap: $1.81T | 1-Mo performance: +2.0% | YTD Performance: +10.2% | Below 52-Wk High: -23.2% | Analyst Target: $527.00 (+39% implied return) | Short Interest: 1.5%
4. Taiwan Semiconductor Manufacturing Company (TSM)
TSMC doesn't design chips. It manufactures them for everyone else, including Nvidia, AMD, Apple, and Broadcom. If you own an AI chip, there's a good chance TSMC physically made it. That makes TSMC one of the most important, and most geographically concentrated, companies in the entire AI supply chain, since nearly all of its advanced manufacturing happens in Taiwan. However, TSMC is looking to make inroads in the US.
📊 Stock Price: $385.75 | Market Cap: $1.79T | 1-Mo performance: -15.2% | YTD Performance: +27.5% | Below 52-Wk High: -19.5% | Analyst Target: N/A | Short Interest: N/A
5. ASML Holding (ASML)
ASML makes the extraordinarily complex (and pricey!) machines that TSMC and other chipmakers need to actually print circuits onto silicon (called EUV lithography). Nobody else on Earth makes machines capable of this at scale, which gives ASML a near-monopoly on the equipment behind the most advanced chips. News reports indicate China is entering the same market, but is way behind ASML in terms of technology.
📊 Stock Price: $1,583.21 | Market Cap: $607.5B | 1-Mo performance: -15.8% | YTD Performance: +48.6% | Below 52-Wk High: -20.8% | Analyst Target: N/A | Short Interest: N/A
6. Micron Technology (MU)
Micron makes memory chips (DRAM and, increasingly, high-bandwidth memory or “HBM”) that sit right next to AI processors and feed them data fast enough to keep up. Demand for its newest memory has been so strong that Micron has reportedly sold out its 2026 HBM supply through long-term contracts. Memory used to be thought of as a boring, cyclical business, like potatoes or soybeans. Now it's a high-growth piece of the AI puzzle. And the debate is raging over whether AI has turned memory into a secular growth sector.
📊 Stock Price: $772.02 | Market Cap: $871.9B | 1-Mo performance: -32.6% | YTD Performance: +170.6% | Below 52-Wk High: -38.5% | Analyst Target: $1,507.38 (+95% implied return) | Short Interest: 2.8%
7. Marvell Technology (MRVL)
Like Broadcom, Marvell designs custom AI chips for big cloud companies (its biggest customer is reportedly Amazon) and makes chips that help data move between AI processors. It's grown fast and joined the S&P 500 in 2026, but it also trades at a very high valuation relative to its earnings, meaning investors are pricing in a lot of future growth.
📊 Stock Price: $171.02 | Market Cap: $149.8B | 1-Mo performance: -38.4% | YTD Performance: +101.5% | Below 52-Wk High: -48.2% | Analyst Target: $256.91 (+50% implied return) | Short Interest: 3.9%
💾 Part 2: The Storage Makers (where all this AI data actually lives)
Training and running AI takes a ridiculous amount of data, and that info has to be stored somewhere. So it goes into hard drives and flash memory. This used to be a sleepy, commodity business, and it's now one of the hottest trades in AI.
8. SanDisk (SNDK)
SanDisk makes NAND flash memory. Those are the fast storage chips used in enterprise SSDs (solid-state drives) that sit between a data center's ultra-fast memory (like Micron's HBM) and its slower, cheaper hard drives. It became an independent, publicly traded company again in 2025 after splitting off from Western Digital. As a pure-play flash memory supplier, it's been one of the single best-performing AI-adjacent stocks of 2026, with shares up several hundred percent as AI data centers snap up its enterprise SSDs. In fact, after its recent decline, it's still the #1 stock in the S&P 500 index.
📊 Stock Price: $1,069.37 | Market Cap: $158.4B | 1-Mo performance: -47.9% | YTD Performance: +350.5% | Below 52-Wk High: -54.6% | Analyst Target: $2,217.77 (+107% implied return) | Short Interest: 4.9%
9. Western Digital (WDC)
Western Digital makes hard disk drives (HDDs), especially high-capacity “nearline” drives used to store the massive datasets AI systems are trained on. Traditional spinning hard drives turn out to still be the cheapest way to store enormous volumes of data, and that's kept demand and pricing power unusually strong. That's why PC hard drives have gotten so expensive.
📊 Stock Price: $482.87 | Market Cap: $166.4B | 1-Mo performance: -25.9% | YTD Performance: +180.5% | Below 52-Wk High: -39.6% | Analyst Target: $655.50 (+36% implied return) | Short Interest: N/A
10. Seagate Technology (STX)
Seagate is Western Digital's main rival in hard drives, and it's leaning on a new recording technology called HAMR (heat-assisted magnetic recording) to pack more data onto each drive. Seagate has reportedly sold out its high-capacity hard drive supply for the year, with hyperscale customers locking in allocations years in advance. That's another sign of just how much storage AI demands.
📊 Stock Price: $792.89 | Market Cap: $179.4B | 1-Mo performance: -18.1% | YTD Performance: +188.6% | Below 52-Wk High: -30.8% | Analyst Target: $1,059.13 (+34% implied return) | Short Interest: 2.9%
☁️ Part 3: The Cloud Giants (where AI actually runs)
Most companies don't buy their own AI chips — they rent computing power from these giants instead.
11. Microsoft (MSFT)
Microsoft has woven AI (“Copilot”) into nearly everything it sells, like Azure cloud, Office, GitHub, and Windows. Its early, deep investment in OpenAI gave it a head start in offering AI tools to businesses, and its Azure cloud division is one of the main places companies go to rent AI computing power.
📊 Stock Price: $399.01 | Market Cap: $2.96T | 1-Mo performance: +8.3% | YTD Performance: -17.1% | Below 52-Wk High: -28.2% | Analyst Target: $555.77 (+39% implied return) | Short Interest: 1.2%
12. Alphabet / Google (GOOGL)
Alphabet builds its own AI chips (called TPUs), runs one of the leading AI labs (Google DeepMind, maker of the Gemini models), and sells AI-powered cloud services through Google Cloud. It's one of the few companies that plays at every layer of the AI universe, including chips, models, and applications. Alphabet also owns a massive stake in Anthropic, the maker of Claude.
📊 Stock Price: $340.27 | Market Cap: $4.16T | 1-Mo performance: -3.8% | YTD Performance: +8.9% | Below 52-Wk High: -16.7% | Analyst Target: $427.59 (+26% implied return) | Short Interest: 0.7%
13. Amazon (AMZN)
Amazon Web Services (AWS) is the largest cloud computing provider in the world, and a growing share of its growth is coming from AI: renting out GPU computing power, its own custom AI chips (Trainium and Graviton), and AI tools built on top of its cloud. Amazon is also a major backer of Anthropic, the AI lab. And like Alphabet / Google, it owns a huge stake in Anthropic.
📊 Stock Price: $231.67 | Market Cap: $2.49T | 1-Mo performance: -3.5% | YTD Performance: +0.4% | Below 52-Wk High: -16.8% | Analyst Target: $313.07 (+35% implied return) | Short Interest: 0.9%
14. Meta Platforms (META)
Meta uses AI to power its ad business and recommendation algorithms across Facebook and Instagram, and it's spending tens of billions building out its own data centers and AI infrastructure to develop its Llama family of AI models. Unlike some peers, Meta doesn't sell cloud computing to others. Its AI spending is aimed at improving its own products, like its ad platforms. However, news reports indicate Meta may in fact enter the AI compute business soon.
📊 Stock Price: $595.20 | Market Cap: $1.51T | 1-Mo performance: +5.8% | YTD Performance: -9.7% | Below 52-Wk High: -25.2% | Analyst Target: $824.68 (+39% implied return) | Short Interest: 1.4%
💻 Part 4: The Software Layer (AI you actually click on)
These companies build the tools and platforms that businesses use to actually put AI to work.
15. Palantir Technologies (PLTR)
Palantir builds software that helps governments and large companies make sense of messy, scattered data and use AI to act on it. It started out focused on defense and intelligence work. But it's expanded fast into commercial AI contracts. Its revenue growth has been among the fastest of any large software company, though its stock trades at a very high valuation relative to earnings.
📊 Stock Price: $126.05 | Market Cap: $302.2B | 1-Mo performance: +8.9% | YTD Performance: -29.1% | Below 52-Wk High: -39.3% | Analyst Target: $182.20 (+45% implied return) | Short Interest: 3.6%
16. Oracle (ORCL)
Oracle, long known for database software, has repositioned itself as a cloud and AI infrastructure company. It rents out computing power to AI labs and companies training large models, and its cloud revenue growth has accelerated sharply as a result. However, it's also taken on significant debt to fund the data centers behind that growth, which has many investors and traders worried about credit quality. This has resulted in Oracle stock sagging pretty badly.
📊 Stock Price: $120.07 | Market Cap: $345.8B | 1-Mo performance: -18.5% | YTD Performance: -37.8% | Below 52-Wk High: -65.3% | Analyst Target: $248.15 (+107% implied return) | Short Interest: 1.5%
17. Snowflake (SNOW)
Snowflake stores and organizes company data so it can be searched and analyzed, like a big warehouse for a company's information. It's now layering AI tools (called Cortex) on top, letting businesses build AI agents that work directly with their own data. A strong earnings report from Snowflake in 2026 helped calm broader fears that AI might make it obsolete.
📊 Stock Price: $290.74 | Market Cap: $100.8B | 1-Mo performance: +15.5% | YTD Performance: +32.5% | Below 52-Wk High: -0.2% | Analyst Target: $298.23 (+3% implied return) | Short Interest: 6.6%
18. ServiceNow (NOW)
ServiceNow's software helps large companies manage internal workflows, like IT tickets, HR requests, approvals. Now it is positioning itself as an “AI control tower” that lets businesses deploy AI agents across all those different workflows. The vast majority of Fortune 500 companies already use its platform, which gives it a big built-in customer base to sell AI features into.
📊 Stock Price: $117.65 | Market Cap: $121.6B | 1-Mo performance: +17.7% | YTD Performance: -23.2% | Below 52-Wk High: -41.5% | Analyst Target: $140.25 (+19% implied return) | Short Interest: 6.0%
🏗️ Part 5: The Infrastructure Builders (the plumbing behind AI)
AI doesn't just need chips — it needs entire buildings full of servers, wiring, and cooling systems to run them.
19. CoreWeave (CRWV)
CoreWeave rents out AI computing power the way a hotel rents rooms. Except the “suites” are jammed full of Nvidia GPUs. Instead of building their own data centers, AI labs and companies can rent CoreWeave's capacity instead. It has grown explosively (its order backlog reportedly jumped toward $100 billion), but that growth is fueled by heavy borrowing to build data centers fast enough to keep up with demand. As with Oracle, this has many investors and traders worried.
📊 Stock Price: $63.40 | Market Cap: $34.6B | 1-Mo performance: -33.6% | YTD Performance: -11.5% | Below 52-Wk High: -58.6% | Analyst Target: $138.03 (+118% implied return) | Short Interest: 14.8%
20. Arista Networks (ANET)
Arista makes high-speed networking switches that connect thousands of AI chips together inside a data center so they can work as one all-powerful system. As AI clusters get bigger, the networking connecting them becomes just as important as the chips themselves, and Arista has become a leading supplier of that networking gear to the largest cloud companies.
📊 Stock Price: $161.39 | Market Cap: $203.2B | 1-Mo performance: -1.7% | YTD Performance: +23.2% | Below 52-Wk High: -15.0% | Analyst Target: $192.31 (+19% implied return) | Short Interest: 1.7%
21. Vertiv Holdings (VRT)
Vertiv makes the power and cooling systems that keep AI data centers from overheating. Modern AI chips generate staggering amounts of heat, especially as they're packed more densely into racks. Vertiv's liquid cooling and power management systems (co-developed with Nvidia) have become essential “plumbing” for AI infrastructure buildouts.
📊 Stock Price: $222.60 | Market Cap: $85.5B | 1-Mo performance: -27.5% | YTD Performance: +37.5% | Below 52-Wk High: -41.4% | Analyst Target: $376.15 (+69% implied return) | Short Interest: N/A
22. Constellation Energy (CEG)
Constellation is the largest operator of nuclear power plants in the U.S. AI data centers need enormous, reliable, round-the-clock electricity. And Constellation has signed long-term power contracts with major tech companies looking to lock in access to power. It's also investing in restarting old nuclear plants and building new small reactors to meet demand.
📊 Stock Price: $258.76 | Market Cap: $92.4B | 1-Mo performance: -0.2% | YTD Performance: -26.5% | Below 52-Wk High: -37.3% | Analyst Target: $352.91 (+36% implied return) | Short Interest: 3.4%
🚀 Part 6: The Emerging & Higher-Risk Names
These companies are more speculative — smaller, more volatile, and more directly tied to a single piece of the AI story.
23. Cerebras Systems (CBRS)
Cerebras takes a completely different approach to AI chips than companies like Nvidia and AMD. Instead of connecting thousands of small processors together, it builds one giant chip out of an entire silicon wafer (about the size of a dinner plate) so an AI model can run on a single piece of silicon instead of being split across a cluster. The true believers believe Cerebras is a genuine challenger to Nvidia's approach. Cerebras has a massive compute deal with OpenAI, and it went public in a blockbuster May 2026 IPO where shares nearly doubled on their first day of trading… before dropping like a rock. As a newly public, single-product company, it's also one of the more volatile and higher-risk names on this list.
📊 Stock Price: $179.50 | Market Cap: $40.7B | 1-Mo performance: -17.0% | YTD Performance: N/A (IPO'd 2026) | Below 52-Wk High: -53.5% | Analyst Target: $292.00 (+63% implied return) | Short Interest: 6.0%
24. Super Micro Computer (SMCI)
Super Micro builds and assembles the physical servers that go inside AI data centers, packing together chips from Nvidia and AMD with the cooling and power systems needed to run them. It's a faster-growing but also more volatile way to invest in AI hardware demand, since it operates on thinner profit margins than the chipmakers themselves and has faced past accounting-related scrutiny.
📊 Stock Price: $26.90 | Market Cap: $17.4B | 1-Mo performance: -4.5% | YTD Performance: -8.1% | Below 52-Wk High: -56.9% | Analyst Target: $37.81 (+41% implied return) | Short Interest: 16.0%
Remember, this is not a buy list. This guide was written to help you understand how these 24 companies are connected to the AI universe. Always do your own research!
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