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Trust Issues: The Double-Edged Sword of AI Investing

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The glitches with artificial intelligence have been well documented, and many are just downright embarrassing — as was the latest fail by Google.

As ValueWalk’s David Moadel detailed in his recent piece, Eating Rocks and Making Excuses: Google’s Latest Gen-AI Fail, Alphabet (NASDAQ:GOOG) (NASDAQ:GOOGL) has been doing damage control over a series of high-profile generative-AI blunders. The most recent involved Google’s AI Overview, which gave bizarre answers to search queries.

For example, the AI model suggested that it’s OK to eat one rock a day. Apparently, a geology website the AI sourced when creating its answer included a satirical article from The Onion on eating rocks.

This is just one of many cases of gen-AI fails, and while many are just silly and absurd, others have been quite damaging. For example, in February, Air Canada was sued by a passenger who got bad information on a flight from the airline’s virtual assistant.  

Glitches like these confirm what many Americans feel about AI: they don’t trust it. Herein lies the conundrum for AI-related businesses.

While AI is revolutionizing computing, driving returns for many companies and attracting the attention of investors, it is a double-edge sword. When AI fails in a very public way, it damages trust, hurts the company’s brand, and can negatively impact its bottom line.

In many ways, AI is still the Wild West — like the early days of the internet. Thus, investors must be wary of companies chasing the AI rainbow with subpar or unsustainable products that lead to bad results.

Most Americans don’t trust AI

In November, a survey by Bentley University and Gallup found that 79% of Americans don’t trust companies to use AI responsibly, with 38% saying “not at all” and 41% saying “not much.”

“A growing chorus of experts has been sounding the alarm on how risky these AI tools are, and this survey finding shows that message is reaching the wider public,” said Noah Giansiracusa, associate professor of mathematics and data science at Bentley. “This is a real opportunity for businesses to compete for customers by associating their brand with a more responsible use of AI.”

Alphabet’s own Vint Cerf, Google’s chief internet evangelist and an internet pioneer known as one of the “fathers of the internet,” echoes these sentiments. At a conference in February 2023, Cerf warned about businesses piling money and resources into AI chatbots — just because they are a hot commodity.

“If you think, ‘Man, I can sell this to investors because it’s a hot topic and everyone will throw money at me,’ don’t do that,” Cerf said at the conference, according to CNBC. “Be thoughtful.”

In other words, in the rush to win the AI arms race, a series of false moves can further damage consumer trust, and that can be hard to win back in a crowded marketplace.

AI stocks: The good and the not-so-good

So far, the most successful company in this burgeoning age of AI has been NVIDIA (NASDAQ:NVDA), which makes graphics processing units (GPUs) that power and facilitate AI computing. NVIDIA has been the best-performing AI stock as its price has gone through the roof, rising 239% in 2023 and another 150% so far this year.

However, for every NVIDIA, there is a Lemonade (NASDAQ:LMND) or Upstart (NASDAQ:UPST): both AI fintechs that sparked a lot of interest when they went public but have fallen flat since.

Lemonade, which uses AI chatbots and algorithms to underwrite insurance policies and settle claims, was an AI darling when it hit the market in July 2020. Its initial public offering (IPO) was priced at $29 per share, and by February 2021, it was trading at $168 per share.

Today, Lemonade is trading at around $16 per share after plunging 90% from its highs.

It is a similar story with Upstart, which uses AI to handle loan requests. The company went public in December 2020 at $20 per share and surged to over $400 per share in 2021 before crashing. It is now trading at $25 per share.

This is not to say these companies won’t ultimately be successful; in fact, both have had consistently increased revenue. The problem has been high costs, competition from bigger companies crowding them out with their own AI tech, and irrational exuberance of investors sending their stock prices higher based on sentiment and not earnings.

These examples illuminate the hazards of investors chasing the latest shiny object. That said, there is little doubt that AI is the future of computing and that it will transform companies and industries along the way.

There is also little doubt that this is just the early days of AI, and even the experts can’t wrap their arms around where this technology will go from here.

Take the gen-AI chip market, for example. It has grown to $50 billion in 2024, up from virtually nothing in 2022, according to consulting firm Deloitte. By 2027, Deloitte predicts the market could be worth anywhere from $110 billion to $400 billion — showing the uncertainty even experts have on its growth trajectory.

Investors should be diligent

For a company like Alphabet, which is investing billions of dollars in its AI infrastructure, these AI fails may be more manageable because of their massive amount of resources. Google is far and away the dominant player in search and has been gaining market share in the cloud business, although it is a distant third with about an 11% market share.

Alphabet’s stock price took a hit on the recent news of the glitch, but it has since regained all the value it had lost. The stock is now back to trading at around $178 per share, up some 28% year to date.

While this episode has not helped its brand, Google has the resources to get it right. Apparently, the company also has plenty of leeway from investors given its market strength.

However, that’s not to say investors aren’t watching, and the next gen-AI fail could have a cumulative effect on eroding trust. Less-dominant players in their industries may not be afforded the same margin for error.

Thus, investors in AI stocks should be diligent, taking note of the gaffes and glitches and the company’s response to them and watching how much they spend on AI and if they are being responsible. Investors should also try to make sure the company is profitable or at least moving toward profitability and avoid AI stocks with ridiculously high multiples.