Keep an eye on machine learning stocks. Companies are tripping over each other for the technology, which involves feeding data to a machine so it can learn and even make human-like decisions. It could be a $503.4 billion market by 2030. Two years later, it could be worth $771.38 billion, according to Precedence Research
Even better, we’re seeing substantial machine learning demand from just about every major industry. That includes healthcare, finance, retail, entertainment and manufacturing just as they are adopting the technology to boost revenue, cut costs and automate operations, as noted by Learn.G2.com. Even more impressive, about 48% of global businesses are already using machine learning with 44% of them seeing lower business costs.
While we can always jump into Nvidia (NASDAQ:NVDA), it’s now an $880 stock that’s already made quite a few investors very wealthy. In fact, the last time I mentioned NVDA in a machine learning article, it was only a $700 stock. If you missed its run, don’t worry. There are plenty of other machine learning stocks with similar potential.
Lantern Pharma (LTRN)
Let’s start with Lantern Pharma (NASDAQ:LTRN), a $52.95 million company trading at less than $5.
An artificial intelligence company, it’s helping to transform the cost and speed to oncology drug discovery and development with its AI and machine learning platform, RADR. With the help of machine learning, AI and advanced genomics, its platform can scan billions of data points to help identity compounds that could help cancer patients.
Typically, with early-stage discovery and development, the traditional approach can take three to five years. However, with companies like Lantern, the process can be as low as two years.
Most recently, the company announced, “Multiple clinical trials across three AI-guided drug candidates are active with first expected data and readouts for LP-184 (for use across multiple cancer indications) in the second half of 2024; with additional next-generation drug development programs approaching IND studies.”
Rekor Systems (REKR)
There’s also Rekor Systems (NASDAQ:REKR), a $156.57 million company that’s leveraging AI and machine learning to identity infrastructure concerns for transportation, public safety and urban mobility. One of its key solutions is Rekor One — an AI-powered roadway intelligence platform.
Most recently, the company announced substantial growth throughout 2023. Gross 2023 revenues of $34.9 million, for example, was 75% better than year ago numbers. Fourth quarter gross revenue jumped 71% year over year.
The total value of its contract values jumped 124% year over year to $49.1 million. And it narrowed its adjusted EBITDA loss from $37.4 million to $28.7 million for 2023.
Even better, as noted by Invetorplace contributor Josh Enomoto, “For the current fiscal year, experts are calling for revenue of $66.07 million. That’s up a staggering 89.1% from last year’s tally of $34.93 million. In the following year, sales could jump to $88.74 million, implying a 34.3% gain over projected 2024 revenue.”
Invesco AI and Next Gen Software ETF (IGPT)
Or, we can diversify at a lower cost with an exchange-traded fund such as the Invesco AI and Next Gen Software ETF (NYSEARCA:IGPT). With an expense ratio of 0.61%, the ETF holds some of the top AI and machine learning stocks on the market, including Nvidia, Alphabet (NASDAQ:GOOG), Meta Platforms (NASDAQ:META), Adobe (NASDAQ:ADBE), Advanced Micro Devices (NASDAQ:AMD) and Qualcomm (NASDAQ:QCOM) to name a few.
What’s nice about this ETF is that we can buy 100 shares of it for just under $4,300, which allows us to diversify with its 98 holdings. Or, we can just buy NVDA and not have the same diversification, and pay about $87,700 for 100 shares.
Since bottoming out at around $30.27 in October, the IGPT ETF hit a high of $47.03 in March. Now back to $42.78, I’d like to see it initially retest its prior high. Even better, the ETF is technically oversold on RSI, MACD, and Williams’ %R — all of which are pivoting higher.
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Read More: Penny Stocks — How to Profit Without Getting Scammed
On the date of publication, Ian Cooper did not have (either directly or indirectly) any positions in the securities mentioned. The opinions expressed in this article are those of the writer, subject to the InvestorPlace.com Publishing Guidelines.
