For the better part of the last three decades, investors have had a next-big-thing technology, innovation, or trend to captivate their attention.
Since the internet completely changed the growth trajectory for businesses in the mid-1990s, we've witnessed massive addressable markets be assigned to genome decoding, business-to-business commerce, China stocks, U.S. housing, nanotechnology, 3D printing, cryptocurrency, blockchain technology, cannabis, augmented/virtual reality, and the metaverse. However, it's artificial intelligence (AI) that might be the cream of the crop among next-big-thing trends.
According to Sizing the Prize , which is an in-depth report released by the analysts at PwC, AI has the potential to add $15.7 trillion to the global economy by the end of the decade. These gains are expected to come in the form of increased productivity and various consumption-side benefits.
A $15.7 trillion opportunity leaves plenty of wiggle room for multiple businesses to come out as winners -- perhaps none more so than semiconductor colossus Nvidia (NASDAQ: NVDA) .
![https://img.particlenews.com/image.php?url=1siGXU_0vTbiSVE00](https://img.particlenews.com/image.php?type=thumbnail_580x000&url=1siGXU_0vTbiSVE00)
Image source: Getty Images.
The AI revolution has driven Nvidia's historic ascent
When 2022 came to a close, Nvidia was a $360 billion company that had fringe importance within the tech sector. Less than 18 months later, shortly after completing a historic 10-for-1 stock split , its valuation would tip the scales at a peak of $3.46 trillion, making it (briefly) the world's most-valuable publicly traded company.
At no point in history have we witnessed a market-leading business add more than $3 trillion in value in less than 18 months. The catalyst behind this never-before-seen move has undeniably been the AI revolution.
It took almost no time for Nvidia's AI-graphics processing units (GPUs) to become the top choice for businesses running generative AI solutions and wanting to build/train large language models (LLMs). Orders for the company's H100 GPU and next-generation Blackwell chip, which is slated for its debut in the first quarter of 2025, are backlogged.
To add to this point, Nvidia's CUDA platform is playing a key role in keeping enterprise clients loyal to its ecosystem . CUDA is the toolkit developers are using to build LLMs and get the most out of their Nvidia GPUs.
Controlling an estimated 98% of the GPU market for AI-accelerated data centers in each of the previous two years has afforded Nvidia a stunning degree of pricing power. Whereas businesses are paying between $10,000 and $15,000 for the MI300X AI-GPU from Advanced Micro Devices , they're forking over $30,000 to $40,000 for Nvidia's H100. A 100% to 300% premium to competing chips has translated into a better than 10-percentage-point increase in the company's gross margin over the last six quarters.
Despite this seemingly ideal execution, Nvidia's share price has fallen by 27% from its all-time high set in June, and may be primed for an even steeper decline.
Nvidia may eventually shed three-quarters of its value
Considering the lofty growth and profit projections Wall Street is forecasting Nvidia will hit in the years to come, an eventual 75% decline from its $140.76 all-time high probably sounds absurd. However, history has yet to be defeated when it comes to next-big-thing innovations .
Though quite a few game-changing technologies and trends went on to become quite successful for patient investors (e.g., the internet and businesses-to-business commerce), one thing all new technologies, innovations, and trends share is early stage bubbles.
While it's impossible to pinpoint when the euphoria surrounding a potentially game-changing innovation will fade, one consistency with the "next big thing" on Wall Street is that investors always overestimate how quickly a technology or trend will become mainstream.
Based on the amount of money businesses are spending on their AI data centers, you'd probably think artificial intelligence is on a path for rapid adoption. But dig deeper and you'll find that most businesses lack a clear game plan for how they're going to deploy AI or monetize the technology for their benefit. It's a telltale sign that we're witnessing the next bubble take shape. Market leaders of next-big-thing bubbles have a history of losing 75% to 99% of their value on a peak-to-trough basis.
The one saving grace for Nvidia is that it had other foundational operating segments in place prior to AI euphoria taking shape. Even if the technology needs multiple years to mature and sales slow dramatically, Nvidia will be able to lean on GPU sales for gaming and cryptocurrency mining , as well as revenue from its virtualization software segment, to somewhat cushion its top- and bottom-line results.
![https://img.particlenews.com/image.php?url=4Lxp4R_0vTbiSVE00](https://img.particlenews.com/image.php?type=thumbnail_580x000&url=4Lxp4R_0vTbiSVE00)
Image source: Getty Images.
Nvidia is set to face fundamental pressures, too
Beyond historic precedent, there are also fundamental reasons to believe Nvidia's sheen is going to wear off as external and internal competitive pressures build .
As I alluded earlier, AMD's MI300X is priced at a notable discount of 50% to 75% below the selling price of the H100. Between Nvidia's extensive backlog and the lure of considerably less-expensive AI-GPUs, AMD and other Nvidia rivals should have no trouble locating demand for their data-center hardware.
What seems to be flying under the radar for most investors is the potential for internal competition.
Four members of the "Magnificent Seven" account for in the neighborhood of 40% of Nvidia's net sales. While, on one hand, it's fantastic that Nvidia is the go-to hardware supplier for America's most-influential businesses, investors should also understand that all four of these companies are internally developing AI-GPUs to deploy in their data centers. Even if Nvidia's H100 and Blackwell chips retain their computing advantage, these Magnificent Seven companies are incented to use these cheaper and more available internally developed chips in a complementary fashion in their data centers.
The real issue with an uptick in internal competition is that it reduces the AI-GPU scarcity that's driven Nvidia's exceptional pricing power. With less pricing power over time, the expectation would be for the company's gross margin to decline .
Moreover, internal competition is going to reduce opportunities for Nvidia to secure valuable data center real estate from America's leading businesses. This suggests we've likely witnessed a peak in orders from the Magnificent Seven.
Nvidia is historically pricey, too. There have only been a handful of instances in the last 30 years where a business on the cutting edge of a next-big-thing innovation had a trailing-12-month price-to-sales (P/S) ratio near 40. Prior instances have resulted in these stocks shedding around 90% of their value on a peak-to-trough basis.
Whether it's historic precedent or its fundamental roadmap. Nvidia appears likely to eventually shed much of its gains since the start of 2023.
Should you invest $1,000 in Nvidia right now?
Before you buy stock in Nvidia, consider this:
The Motley Fool Stock Advisor analyst team just identified what they believe are the 10 best stocks for investors to buy now… and Nvidia wasn’t one of them. The 10 stocks that made the cut could produce monster returns in the coming years.
Consider when Nvidia made this list on April 15, 2005... if you invested $1,000 at the time of our recommendation, you’d have $716,375 !*
Stock Advisor provides investors with an easy-to-follow blueprint for success, including guidance on building a portfolio, regular updates from analysts, and two new stock picks each month. The Stock Advisor service has more than quadrupled the return of S&P 500 since 2002*.
See the 10 stocks »
*Stock Advisor returns as of September 9, 2024
Sean Williams has no position in any of the stocks mentioned. The Motley Fool has positions in and recommends Advanced Micro Devices and Nvidia. The Motley Fool has a disclosure policy .
Comments / 0