The glitches with artificial intelligence have been well documented, and plenty of are only downright embarrassing — as was the most recent 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. Probably the most recent involved Google’s AI Overview, which gave bizarre answers to look queries.
For instance, 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.
That is just certainly one of many cases of gen-AI fails, and while many are only silly and absurd, others have been quite damaging. For instance, 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 a lot of corporations and attracting the eye of investors, it’s a double-edge sword. When AI fails in a really public way, it damages trust, hurts the corporate’s brand, and might negatively impact its bottom line.
In some ways, AI remains to be the Wild West — just like the early days of the web. Thus, investors have to be wary of corporations chasing the AI rainbow with subpar or unsustainable products that result in 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 corporations to make use of AI responsibly, with 38% saying “by no means” and 41% saying “not much.”
“A growing chorus of experts has been sounding the alarm on how dangerous these AI tools are, and this survey finding shows that message is reaching the broader public,” said Noah Giansiracusa, associate professor of mathematics and data science at Bentley. “This can be 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 web evangelist and an online pioneer generally known as certainly one of the “fathers of the web,” echoes these sentiments. At a conference in February 2023, Cerf warned about businesses piling money and resources into AI chatbots — simply because they’re a hot commodity.
“For those who think, ‘Man, I can sell this to investors since it’s a hot topic and everybody will throw money at me,’ don’t try this,” Cerf said on the conference, based on CNBC. “Be thoughtful.”
In other words, in the frenzy to win the AI arms race, a series of false moves can further damage consumer trust, and that could be hard to win back in a crowded marketplace.
AI stocks: The nice and the not-so-good
Up to now, essentially the most successful company on 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 undergone the roof, rising 239% in 2023 and one other 150% to date this 12 months.
Nevertheless, for each NVIDIA, there’s a Lemonade (NASDAQ:LMND) or Upstart (NASDAQ:UPST): each AI fintechs that sparked loads of interest after 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.
NVIDIA $NVDA JUST REPORTED EARNINGS
EPS of $6.12 beating expectations of $5.58
Revenue of $26B beating expectations of $24.59B
NVIDIA ALSO JUST ANNOUNCED A NEW 10:1 STOCK SPLIT
pic.twitter.com/6v2yJNa3dM
— Evan (@StockMKTNewz) May 22, 2024
It’s an identical story with Upstart, which uses AI to handle loan requests. The corporate went public in December 2020 at $20 per share and surged to over $400 per share in 2021 before crashing. It’s now trading at $25 per share.
This will not be to say these corporations won’t ultimately achieve success; in reality, each have had consistently increased revenue. The issue has been high costs, competition from greater corporations crowding them out with their very own AI tech, and irrational exuberance of investors sending their stock prices higher based on sentiment and never earnings.
These examples illuminate the hazards of investors chasing the most recent shiny object. That said, there’s little doubt that AI is the long run of computing and that it would transform corporations and industries along the best way.
There’s also little doubt that that 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 instance. It has grown to $50 billion in 2024, up from virtually nothing in 2022, based on consulting firm Deloitte. By 2027, Deloitte predicts the market might be price anywhere from $110 billion to $400 billion — showing the uncertainty even experts have on its growth trajectory.
Investors ought to be diligent
For a corporation like Alphabet, which is investing billions of dollars in its AI infrastructure, these AI fails could also be more manageable due to their massive amount of resources. Google is way and away the dominant player in search and has been gaining market share within the cloud business, even though it is a distant third with about an 11% market share.
Alphabet’s stock price took a success on the recent news of the glitch, nevertheless it has since regained all the worth it had lost. The stock is now back to trading at around $178 per share, up some 28% 12 months so far.
While this episode has not helped its brand, Google has the resources to get it right. Apparently, the corporate also has loads of leeway from investors given its market strength.
Nevertheless, that’s to not say investors aren’t watching, and the following gen-AI fail could have a cumulative effect on eroding trust. Less-dominant players of their industries is probably not afforded the identical margin for error.
Thus, investors in AI stocks ought to be diligent, being attentive to the gaffes and glitches and the corporate’s response to them and watching how much they spend on AI and in the event that they are being responsible. Investors must also attempt to be sure that the corporate is profitable or at the very least moving toward profitability and avoid AI stocks with ridiculously high multiples.