When it comes to investing in stocks markets, one must consider a wide range of factors. For starters, you should diligently study the books, including key metrics such as dividends, debt-to-equity ratio, price-to-equity ratio, earnings growth, etc. It’s also essential to put your money in future-ready companies.
These days, artificial intelligence companies are all the rage in the stock market. However, investing in such companies can get a little tricky, given the warp speed at which the AI tech is evolving. For that reason, picking an AI stock calls for an indepth look at various factors beyond just financials.
Here we list the top factors to look at before investing in an AI company.
Many companies leverage AI for problem-solving. As a result, the quality of solutions an AI company has to offer becomes a key performance indicator. Many players are working on the same problems in the AI field. Complacency is a cardinal crime for AI companies as there is always the risk of hungrier companies — with better solutions– eating into your market share.
For instance, C3.ai, an AI-based cloud company, had one of the hottest IPOs in 2020 at $42 a share. The stock hit $100 a share the next day, and the company had raised a total of $651 million.
However, C3.ai runs on top of Amazon’s AWS and Microsoft’s AI, which are both suppliers and competitors. While C3.ai claims its services are cheaper, more efficient, and customisable, AWS and Amazon have their own platforms for integration. So unless C3.ai is able to innovate aggressively, people will move away from the platform. The net losses of the company have gone up in the past three years. Snowflake is another AI-based cloud company that faces a similar threat.
AI has applications across industries. It is critical to have adequate background knowledge of the industry before you invest. The risks associated with the industry can have a spillover effect on the industry’s investment in AI. Imagine you have invested in an app-based cab hiring company that uses AI for price optimisation. In this case, you should consider all the factors that could affect the ride-sharing industry, like a pandemic.
For instance, the pandemic took a big toll on Uber, an AI-based ride-hailing app. Uber’s services had to be shut down after the US declared lockdown in February. The stock fell from $42 on February 21, to $15 in a month’s time. Thus, while Uber’s AI technology might be the best in the business, the stock is on a free fall due to disruption of the industry.
AI relies heavily on other emerging technologies and also huge sets of quality data. For instance, advances in cloud computing can facilitate quicker access to data to train AI models. At the same time, AI applications can complement cloud services. As the network effects kick in, the technologies become cheaper.
For example, NVIDIA was investing heavily on making custom hardware for deep learning applications, whereas ARM was involved in custom chips that accelerated the smartphone innovation. Last year, NVIDIA’s announcement on acquiring ARM sent its stock soaring. Overall, NVIDIA’s share doubled through the past year, until September, compared to a mere 3% increase in S&P500 shares. The rallying of stock was attributed to strategic moves by NVIDIA that also included the acquisition of Mellanox, a leading supplier of intelligent interconnect solutions.
AI is powered by a bundle of cutting-edge technologies. It pays to wise up to concepts like machine learning, deep learning, and neural networks if you are going to invest in an AI company. You should be able to place an informed bet based on how a company deploys its AI.
The market for Natural Language Processing in healthcare is predicted to grow from $1.5 billion in 2020 to $3.7 billion by 2025, at a CAGR of 20.5%. Companies like Google and IBM are investing heavily in this area.
Recently, many companies have come under fire for deploying biased algorithms. Courting controversies can have adverse effects on the company’s goodwill and, by extension, on its stock. From an investor’s perspective, it’s crucial to ensure the companies they are getting behind use AI fairly and ethically. Investors should also see if the company is using AI to misappropriate personal or biometric data of users.
Palantir, a big-data analytics company, has focused on developing surveillance tools, after 9/11, designed to sift entire populations to identify ‘terrorists’ and ‘miscreants’. The company has worked for the US Army and also helped the notorious Immigration and Customs Enforcement (ICE) in the US, to identify illegal immigrants. The company was heavily criticised for being given access to citizens’ personal data by the UK government to track COVID-19 patients.
Companies that build technologies using personal data risk running into data privacy issues and an image problem. After 17 years, Palantir still has only 125 customers and remains a heavy loss-making company with a highly volatile stock.
Being a relatively new field, most AI companies are startups and hence not publicly listed. However, the risk/reward ratio of these startups are on the higher side. Platforms like SeedInvest and WeFunder let you use cryptocurrencies to invest in such firms.
When it comes to investing in small startups, it’s a good idea to look at their funding history. At the end of the day, AI is a high capital play, and it’s safer to invest in companies backed by respectable venture capitalists and angel investors.
Data is at the heart of every AI company. Just as oil prices affect car companies or land prices influence the semiconductor industry, the availability of data impacts AI. Companies with access to the best or unique datasets have a sizable advantage.
For instance, search engines like Google can leverage its access to large swathes of diverse datasets to build innovative AI solutions. Before investing in a company, it’s essential to ensure the company will have continued access to useful data.
Investors should get their fundamentals right before putting the money in an AI company. You should look at trading charts to understand the stock’s movement and the overall market and study the balance sheet before investing. In sum, make sure you dot the i’s and cross the t’s while developing a strategy to invest in an AI stock.