AI stocks under $20 for 2025: What to watch
You see ‘AI’ in every headline and hear about stocks like NVIDIA soaring, making you feel like you’ve missed the boat. But the AI revolution is just getting started, and you don’t need thousands of dollars to own a piece of it. What if you could invest in the AI future for less than the cost of a movie ticket?
Before you start searching for how to find undervalued AI companies, there’s one critical idea we must cover. A low stock price, like $10 or $20, doesn’t automatically mean a company is “cheap” or a good value. In practice, the price of a single share is often one of the most misleading numbers for a new investor.
Think of it like this: a stock’s price is the cost of a single brick, but what you really want to know is the price of the entire house. That total price tag for a company is called its market capitalization (or “market cap”). It’s calculated by multiplying the stock price by the total number of shares, and it’s a far better way to judge a company’s true size.
For example, a company with a $2 stock might have one billion shares, giving it a huge $2 billion market cap. Meanwhile, another company with a $50 stock could have just 10 million shares, for a much smaller $500 million market cap. These smaller, or “small-cap,” AI stocks often have more room to grow but also carry more risk. Grasping this difference is the key to looking beyond the price tag.
What Kind of AI Companies Actually Trade Under $20?
When you’re looking for stocks under $20, what kind of AI companies should you expect to find? You won’t discover the next NVIDIA or Google in this price range. Instead, these are typically smaller, more focused companies that fall into two main buckets, representing exciting emerging AI stock opportunities.
Recognizing these categories is the key to spotting potential. Most of these affordable stocks are either:
- AI-Powered Businesses: These companies have a primary business—like healthcare or finance—and use artificial intelligence as a powerful tool to do it better. Think of a company whose main service is helping doctors, but uses AI to analyze medical scans faster than the human eye.
- Emerging AI-Tech Companies: Often AI software stocks, these companies are building new, specialized tools. Instead of creating a giant, all-knowing AI, they might build a best-in-class voice assistant for restaurant drive-thrus or a tool that helps online stores fight fraud.
The common thread is focus. These companies aren’t trying to build everything; they’re trying to solve one problem exceptionally well in sectors poised for growth. They aim to become a crucial component for other, larger businesses. Our first example, a company putting its unique stamp on voice AI, shows this concept in action.
Real-World Example #1: How SoundHound AI Is Putting Voice AI Everywhere
Have you ever gotten frustrated talking to a voice assistant that just doesn’t understand you? SoundHound AI (Ticker: SOUN) is a company betting it can do better. Instead of creating a consumer gadget, however, it offers its advanced voice AI as a service to other businesses. Think of it like a “plug-and-play” brain that allows cars, restaurants, and smart devices to understand complex, natural human speech without their developers having to become AI experts themselves.
This business model is powerful. A restaurant chain like Jersey Mike’s can use SoundHound’s technology to take drive-thru orders, and car makers like Mercedes-Benz can embed it to create a world-class conversational assistant right in the dashboard. These companies pay SoundHound for access to its technology, creating a stream of revenue. This approach makes it one of the more interesting potential machine learning companies under $20 because its success is tied to the success of its many partners.
For investors, a key thing to watch is who SoundHound partners with. When a major brand trusts a smaller company’s technology, it’s a powerful vote of confidence. A recent investment from NVIDIA, the company that builds the chips powering the AI revolution, further signals that SoundHound is a serious player in the field. These relationships are often a more telling sign of potential than a daily stock price swing for emerging AI stocks under $20.
SoundHound’s entire business revolves around what an AI can hear. But AI is also changing what we can see. Our next example, Rekor Systems, applies this same focused strategy to the world of computer vision, showing just how different the opportunities in this space can be.
Real-World Example #2: How Rekor Systems Uses AI to Make Our Roads Smarter
While SoundHound teaches machines to listen, Rekor Systems (Ticker: REKR) teaches them to see. Imagine if our roadways could spot a traffic jam forming before it becomes a standstill or instantly alert emergency services to an accident. That’s the future Rekor is building by applying artificial intelligence to the cameras that already watch over our public spaces.
The company’s technology transforms ordinary traffic cameras into smart devices. Instead of a person having to watch dozens of video feeds, Rekor’s AI analyzes the footage in real time to understand traffic flow, identify vehicle types, and even read license plates. This provides a wealth of information that was previously impossible to gather at scale, making it one of the more interesting predictive analytics stocks for future growth focused on physical infrastructure.
Unlike companies that sell to other businesses, Rekor primarily operates on a Business-to-Government (B2G) model. Its main customers are city, state, and federal agencies responsible for transportation and public safety. For investors performing a Rekor Systems stock analysis, this is a key detail. Government contracts can be large and long-lasting, potentially offering more stable revenue than chasing individual consumer trends.
From voice assistants in restaurants to smart cameras on highways, these examples show there isn’t just one way to be an “AI company.” This variety is exciting, but it also makes it tricky to sort through the hype and evaluate these unique companies for yourself.
Your 3-Point Checklist for Evaluating Any Low-Priced AI Stock
It’s easy to get lost in the buzzwords. With so many companies claiming to use “revolutionary AI,” how do you begin to separate the contenders from the pretenders? Instead of needing a computer science degree, you just need a simple framework. This short checklist is a powerful starting point in your own personal guide to emerging AI stock opportunities.
Before you ever consider investing, run the company through these three simple tests. If you can’t find clear and simple answers, it’s a major red flag.
- The One-Sentence Test: Can you explain what problem the company solves in a single, simple sentence? (e.g., “They help restaurants take drive-thru orders with an AI voice.”) If the explanation is confusing, the business model might be, too.
- The Customer Test: Who pays their bills? Is it regular people, other businesses, or the government? A company with a clear and growing customer base has a much stronger foundation.
- The Profit Test: Are they making money yet, or are they burning cash to grow?
This framework helps you look at a company the way a business owner would. The first two questions confirm there is a real, understandable business here. The third question, however, is where the risk comes into focus. Many small, fast-growing companies aren’t profitable yet because they are spending heavily to build their technology and attract customers.
A company’s profitability is a crucial clue in finding potentially undervalued AI companies, separating those with a future from those just burning cash. While a lack of profit isn’t an immediate deal-breaker, it dramatically raises the stakes.
A Crucial Warning: The High-Wire Act of Small AI Stocks
That last point from our checklist—the Profit Test—is where the excitement meets the danger. Many of these promising, low-priced AI companies are spending far more than they make. This creates a high-stakes environment full of what investors call volatility, and it’s one of the biggest risks of investing in low-priced AI companies.
Think of volatility as the stock’s temperament. A massive company like Apple is a cruise ship, moving slowly and steadily. These smaller AI stocks are more like speedboats in a choppy ocean. Their price can rocket upward on good news but can plunge just as fast on a setback. This means the value of your investment can swing wildly from one day to the next.
This is the world of speculative investing. You aren’t buying a piece of a stable, profitable machine; you’re betting on a blueprint. It’s like planting a rare seed in the wild. It might grow into something massive, or it could be washed away in the first storm. Even what look like the top AI penny stocks with strong fundamentals can, and often do, fail.
Because of this, the single most important rule is to never invest money you can’t afford to lose. The long-term growth potential of cheap AI stocks is the prize, but the risk of losing your entire investment is very real. Think of these stocks as a small, high-wire act within a larger, more stable financial portfolio.
Your Next Step: From Reader to Researcher
Before reading this, the world of AI stocks might have felt like a members-only club, with entry fees in the hundreds of dollars. The idea of investing in artificial intelligence for under $20 likely seemed like either a secret trick or a total gamble. But you now possess a different lens, one that can look past a simple price tag to see the bigger picture.
You’ve learned that a company’s total value (its market cap) tells a more complete story than its share price. You know to look for companies solving real-world problems for actual customers, a core lesson in any guide to emerging AI stock opportunities. Most importantly, you understand that with high potential comes very real risk, especially with smaller, unproven companies.
This article was the map, not the destination. Your first step isn’t to open your brokerage app. Instead, pick one company you learned about today. Find its official “Investor Relations” website and see if you can answer three simple questions: What problem do they solve? Who are their customers? What are their biggest risks? Don’t worry about buying or selling—just practice telling their story.
This simple exercise is how you move from searching for the “best affordable AI stocks to buy now” to building the skills to find them yourself. It is the first, most crucial step in transforming from a passive spectator into a confident, informed investor. You’ve already taken the biggest leap: choosing to learn before you leap.
