Machine learning stocks are rising in popularity. The interest in AI and machine learning has surged this year thanks to OpenAI’s release of ChatGPT. We’ve tasted what these technologies are capable of and are already thinking about what the future could hold.
Machine learning stocks, therefore, have much room to run and the ability to mint tomorrow’s millionaires.
These companies have applications ranging from helping doctors diagnose life-threatening diseases to stopping credit card fraud, chatbots, and prognosticated tech utilization like artificial general intelligence.
So, if you want to add three new machine learning stocks with tremendous upside potential, continue reading.
C3.ai (AI)
C3.ai (NYSE:AI) provides AI software for enterprises, but it’s most well-known for its advancements in machine learning capabilities. It allows companies to launch and manage their own AI applications that are stored in the cloud.
There are a few reasons to believe that C3.ai could be one of those machine learning stocks that will deliver multi-bagger returns. Although the company is currently unprofitable with a negative net income, this is par the course for tech startups, as their focus is on scaling revenue and reaching those important network effects first.
C3.ai has launched pilots with numerous marquee brands such as GSK (LON:GSK), Indorama (NSE:INDORAMA), First Business Bank (NASDAQ:FBIZ), and others. It also closed 62 agreements in total with various companies, which signals that its revenues could be scaling quickly.
Then there’s also the company’s valuation, which remains attractive. On a forward price-to-sales basis, it trades at just 11.17 times sales. Therefore, the company seems cheap relative to its progress in onboarding numerous blue-chip clients, making it one of those machine learning stocks with massive potential.
Appen (APXYY)
Appen (OTCMKTS:APXYY) An Australian company, Appen focuses on developing high-quality training data for machine learning and artificial intelligence. This is my ultra high-risk, high-reward play for one of those machine learning stocks to consider.
The company is a penny stock, trading around AUD 0.60 at the time of writing. This is an enormous decline from its AUD 35.43 peak share price recorded in August 2020. It also recently reported a massive 30% drop in revenue amid a reduction in spending by a few of Appen’s major tech customers and a capital raise that saw its shares diluted.
However, despite these problems, some brokers believe that Appen’s business remains structurally sound despite facing a downturn. The company is predicted to realize a small EBITDA profit next year, and thanks to being down 94.82% over the past five years, its share could very nearly be at the absolute bottom.
DataRobot (DR)
DataRobot (NASDAQ:DR) offers an enterprise AI platform that enables organizations to build and deploy machine learning models. Like the other machine learning stocks on this list, DR also has some powerful catalysts ahead of it.
For example, the company recently enhanced its partnership with SBI Holdings, a Japanese internet financial services leader, to advance generative AI in Japan. The partnership will see them develop chatbots for financial products and create summarization services for certain legal and financial documents. The big picture is that the initiative could deliver revenue within the next three years.
Also, on the enterprise front, DR launched a new console for clients to get a bird’s eye view of the health and performance of their enterprise models. Specifically, this console allows organizations to help monitor if their models generate toxic or misleading content and to take steps to correct it.
In summary, DR stock addresses the core risk of generative AI models for large enterprises, namely the problem of hallucinating and creating dubious content. If DR can successfully handle this issue, then one of the key issues that stop organizations from adopting the technology will be overcome, and its privacy and governance features are planned to keep the AI assets in a secure environment.
On the date of publication, Matthew Farley did not have (either directly or indirectly) any positions in the securities mentioned in this article. The opinions expressed are those of the writer, subject to the InvestorPlace.com Publishing Guidelines.
