For the past 30 years, Wall Street and the investment community have been waiting for a game-changing innovation or technology to come along that can rival or surpass what the internet did for corporate America. The rise of artificial intelligence (AI) just might fit the bill.
When discussing AI, I’m loosely talking about using software and systems to handle tasks that humans would normally be responsible for. What makes AI such a potential cornerstone innovation is the ability for software and systems to learn without human oversight. This ability to become more efficient at tasks over time, as well as learn new tasks, gives this technology utility in pretty much all facets of the U.S. and global economy.
Just how big the AI revolution could be is left up to interpretation and the imagination. But according to the lofty estimates provided by analysts at PwC, artificial intelligence has the capacity to add $15.7 trillion to the global economy by 2030. PwC came to this conclusion by deducing that $6.6 trillion would be added by increases in productivity, with the remaining $9.1 trillion aided by consumption-side benefits.
Dollar figures this large aren’t lost on Wall Street’s brightest minds. Most Wall Street institutions and analysts have set lofty growth expectations and sky-high price targets on market-leading AI stocks.
But there are exceptions.
Based on the low-water price targets from select Wall Street analysts, the following three leading artificial intelligence stocks can plunge by up to 91%.
Palantir Technologies: Implied downside of 65%
The first top-tier AI stock that might get taken to the woodshed, based on the prognostication of one Wall Street analyst, is data-mining specialist Palantir Technologies (NYSE: PLTR).
Whereas one analyst believes Palantir still offers 35% upside from where it closed on July 3, Rishi Jaluria of RBC Capital believes it’s worth $9 per share. If this forecast proves accurate, one of the hottest AI stocks would plummet by 65%!
Although longtime Palantir bear Jaluria recognizes that its operating results have been solid, a May 2024 note implies concern about the company’s commercial segment. Specifically, Jaluria points to revenue that’s been pulled forward from special purpose acquisition companies (SPACs) that had signed deals with Palantir. There’s no telling how sustainable or recurring this revenue will be.
While Jaluria’s concern is valid — most SPACs have been disasters for investors — Palantir does bring identifiable competitive advantages to the table that clearly do deserve some premium. For instance, the scope of services provided by Palantir can’t be duplicated at scale by any other business.
Palantir’s bread-and-butter operating segment has long been Gotham. This is the AI-driven platform that helps governments gather data and plan missions, among other tasks. The company typically secures multiyear contracts from governments using Gotham, which leads to sustained double-digit sales growth and predictable cash flow.
However, the company’s future likely rests with the success of its Foundry platform, the aforementioned “commercial” segment. Foundry is tasked with helping businesses understand their data so they can streamline their operations. Commercial customer count has surged 53% over the last year (as of March 31, 2024), albeit this segment is still in its very early stages of growth.
Although Palantir can deliver sustained double-digit sales growth and is irreplaceable at scale, a forward price-to-earnings (P/E) ratio of 65 and a price-to-sales ratio of 25 (based on trailing-12-month sales), are tough pills to swallow in an already pricey stock market.
Nvidia: Implied downside of 22%
A second artificial intelligence stock that might face a coming beatdown is the company that’s benefited most from the AI revolution: semiconductor titan Nvidia (NASDAQ: NVDA).
While most Wall Street analysts can’t set their price targets high enough for this leading AI stock, Deutsche Bank‘s Ross Seymour set a $100 price target ($1,000 prior to Nvidia’s 10-for-1 stock split) in May. If Nvidia were to hit $100 per share, it would shed 22% of its current value, which translates to almost $700 billion in lost market cap.
In many ways, Nvidia’s expansion has been flawless. The company’s H100 graphics processing unit (GPU) has quickly become the must-have chip for AI-accelerated data centers. Last year, Nvidia’s GPUs accounted for 98% of the 3.85 million AI-GPUs shipped, according to TechInsights. With its next-generation Blackwell GPU architecture set to make its debut in the latter half of this year, Nvidia shouldn’t have any trouble maintaining its compute advantage in enterprise data centers.
However, history has consistently been a thorn in the side of businesses leading next-big-thing revolutions. Since the advent of the internet, there hasn’t been a buzzy innovation, technology, or trend that’s avoided a bubble in its early innings. Investors habitually overestimate the uptake and growth potential of new innovations and technologies while giving them no time to mature. Artificial intelligence seems unlikely to be the exception to this unwritten rule.
Nvidia’s fiscal second-quarter adjusted gross margin forecast of 75.5% (+/- 50 basis points) may also be an ominous warning. While an adjusted gross margin of 75.5% is still well above its historic norm, it represents a decline of 235 to 335 basis points from the sequential quarter. Putting two and two together, it suggests that competitive pressures have entered the picture.
External competitors are releasing or ramping up production of their respective AI-GPUs in the second half of the year, while Nvidia’s top four customers by net sales are all developing AI-accelerating chips of their own for their data centers. The GPU scarcity responsible for fueling Nvidia’s scorching-hot adjusted gross margin looks set to wane — and that’s potentially bad news for investors.
Tesla: Implied downside of 91%
However, the potential disaster du jour among AI stocks is the world’s most-valuable electric-vehicle (EV) maker Tesla (NASDAQ: TSLA). The company’s full self-driving (FSD) software, which uses a network of cameras and ultrasonic sensors to avoid obstacles, is a perfect example of how Tesla incorporates AI into its EVs.
In mid-April, longtime Tesla bear Gordon Johnson of GLJ Research lowered his uber-specific price target on Tesla to $22.86 per share. Historically, Johnson has arrived at his price targets by placing a multiple of 15 on his forward-year earnings estimate for the company and applying a 9% discount rate at the current price.
There’s no denying that Tesla has done what had been impossible in the auto industry for more than a half-century. CEO Elon Musk successfully built the company from the ground up to mass production, and has delivered four consecutive years of generally accepted accounting principles (GAAP) profit. But the praise ends here.
Over the last 18 months, Tesla has slashed the selling price for its fleet of EVs on more than a half-dozen occasions. With its first-mover advantages waning and competition picking up, Musk has had no choice but to become more price-competitive. The end result has been a steep reduction in the company’s operating margin, a reversal to a free cash outflow during the first quarter, and a big increase in the company’s EV inventory.
Furthermore, Tesla’s efforts to become more than a car company have largely fallen flat. Though it does have a handful of small victories under its belt, the growth rate for Tesla’s Energy Generation and Storage segment has tapered significantly, while gross margin for Services is in the low single digits. As much as investors want to pretend that Tesla is an energy or tech company, the bulk of its sales and profits still come from its now-struggling and cyclical EV operations.
The other damning factor for Tesla is the laundry list of promises and innovations from Musk that have failed to take shape. After a full decade of promising Level 5 autonomy for his company’s EVs, Tesla’s FSD hasn’t budged from Level 2 autonomy. What’s more, the Cybertruck has been an early stage flop, with multiple recalls and subpar deliveries.
Tesla is an auto stock with contracting margins and declining EV deliveries that’s trading at a premium to even the loftiest of AI stocks. While a 91% drop might be a bit extreme, I’d have to concur with Gordon Johnson that significant downside seems likely.
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Sean Williams has no position in any of the stocks mentioned. The Motley Fool has positions in and recommends Nvidia, Palantir Technologies, and Tesla. The Motley Fool has a disclosure policy.
3 Leading Artificial Intelligence (AI) Stocks That Can Plunge Up to 91%, According to Select Wall Street Analysts was originally published by The Motley Fool
Source: finance.yahoo.com