The double-edged sword of AI investment
The flaws in artificial intelligence are well-documented, and in many cases, like Google’s recent failures, they are downright embarrassing.
As David Moadel of ValueWalk explains in detail in his recent piece, Eating a Stone and Making Excuses: Google’s Latest Gen-AI Failure, alphabet (NASDAQ:GOOG) (NASDAQ:GOOGL) has been doing damage control for a series of high-profile generative AI mistakes. Most recently, it included an overview of Google’s AI that provides bizarre answers to search queries.
For example, the AI model suggested that it was okay to eat one rock a day. Apparently, the geology website that the AI was providing when it wrote its response included a satirical article from The Onion about eating rocks.
This is just one of many examples of gen-AI failures, many of which are foolish and outrageous, while others are quite damaging. For example, in February, Air Canada was sued by a passenger who got false information about a flight from the airline’s virtual assistant.
Flaws like these confirm how many Americans feel about AI: they don’t trust it. Herein lies the challenge of AI-related business.
AI is revolutionizing computing, driving revenue for many companies, and gaining investor attention, but it’s a double-edged sword. If AI fails in a very public way, trust can be damaged, company brand damaged, and profits negatively impacted.
In many ways, AI is still the Wild West, like the early days of the internet. Therefore, investors should be wary of companies chasing the AI rainbow with low-quality or unsustainable products that lead to bad outcomes.
Most Americans Don’t Trust AI
A survey conducted by Bentley University and Gallup last November found that 79% of Americans do not trust companies to use AI responsibly, with 38% saying “not at all” and 41% saying “not very much.” .
“More and more experts are sounding the alarm about how dangerous these AI tools can be, and these findings show that the message is reaching a wider public,” said Noah Giansiracusa, associate professor of mathematics and data science at Bentley. . “This is a real opportunity for companies to compete for customers by associating their brands with more responsible use of AI.”
Alphabet’s Vint Cerf, an Internet pioneer known as Google’s chief Internet evangelist and one of the “fathers of the Internet,” echoes this sentiment. At the February 2023 conference, Cerf warned against companies piling money and resources into AI chatbots just because they are a hot commodity.
“If you’re thinking, ‘This is a hot topic and I can sell it to investors because everyone is going to throw money at me,’ don’t do that,” Cerf said at the conference, according to CNBC. “Be thoughtful.”
That means that in the rush to win the AI arms race, a series of wrong moves could further damage consumer trust, which could be difficult to regain in a crowded marketplace.
AI Stocks: The Good and the Not-So-Good
By far the most successful company in the burgeoning AI era has been NVIDIA (NASDAQ:NVDA), which makes graphics processing units (GPUs) that support and facilitate AI computing. Nvidia has been the best-performing AI stock, with its price skyrocketing, up 239% in 2023 and 150% so far this year.
But for every NVIDIA, there’s a Lemonade (NASDAQ:LMND) or Upstart (NASDAQ:UPST). Both AI fintechs generated a lot of interest when they listed, but have since stagnated.
Lemonade, which uses AI chatbots and algorithms to underwrite insurance policies and resolve claims, was an AI favorite when it hit the market in July 2020. The IPO price was $29 per share, and in February 2021, the company is trading at $168 per share.
Lemonade is currently trading at around $16 per share after plummeting 90% from its highs.
It’s a similar story at Upstart, which uses AI to process loan requests. The company went public in December 2020 at $20 per share and soared to more than $400 per share in 2021 before plummeting. It’s currently trading at $25 per share.
This is not to say that these companies will not ultimately succeed. In fact, both companies have consistently grown their profits. The problems were high costs, competition from larger companies with their own AI technology, and the irrational enthusiasm of investors who drove up stock prices based on sentiment rather than profits.
These examples highlight the risks of investors chasing the latest shiny object. That said, there is no doubt that AI is the future of computing and will transform businesses and industries in the process.
There is little doubt that this is just the early stages of AI, and not even experts can predict where the technology will go from here.
Consider, for example, the Gen-AI chip market. According to consulting firm Deloitte, it will increase from almost zero in 2022 to $50 billion in 2024. Deloitte predicts that the market will reach $110 billion to $400 billion by 2027. This shows the uncertainty even experts have about the growth trajectory.
Investors must be diligent
For companies like Alphabet, which are investing billions of dollars in AI infrastructure, these AI failures may be easier to manage due to the sheer amount of resources they have. Google is by far the dominant player in search and is gaining market share in the cloud business. However, it ranks third with a market share of about 11%.
Alphabet’s stock price took a big hit recently following news of the glitch, but has since regained all the value it lost. The stock is now trading again at around $178 per share, up about 28% year to date.
Although this episode wasn’t helpful to your brand, we have the resources to make it right. Clearly, the company has a lot of leeway from investors given its market strength.
But that doesn’t mean investors aren’t watching, and the next wave of AI failures could have a cumulative effect that erodes trust. The same margin for error may not be available to less dominant players in their industry.
Therefore, investors in AI stocks should carefully look at mistakes and flaws and companies’ responses to them, and carefully monitor how much they are spending on AI and whether they are taking responsibility for it. Investors should also make sure the company is profitable, or at least moving toward profitability, and try to avoid AI stocks with ridiculously high multiples.
