September 24, 2024
What Do Lower Interest Rates Mean for Your Portfolio?
September 24, 2024
Investors are entering a new market as the US economy continues towards a soft landing and the Federal Reserve aims to cut interest rates.
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It can make your computer faster, give you more accurate search results on Google, speed up payments, write novels, direct video games, make investments, and even support military campaigns. But are these claims realistic?
Artificial intelligence does offer many benefits. However, when it comes to selecting investments, it’s healthy to be critical of anyone claiming “world-changing” technology. Otherwise, we could end up with another Dot Com bubble.
Let’s remember back to early 2000. The first quarter saw over 140 IPOs in the US alone, with share prices tripling. But by March, it was already in decline. Even “safer” technology stocks like Intel or Oracle lost up to 80% of their value after the bubble burst.
But that doesn’t mean that the technology isn’t revolutionary.
Let’s consider an example of AI usage in payments. Artificial intelligence enables accounting teams to rapidly process invoices, reducing time and money spent on data-entry, error corrections, and follow-ups. It opens time for these finance professionals to focus on higher-level, more interesting tasks. The cost of processing a single invoice, according to the 2024 State of ePayables report, dropped by 79%.
At the same time, it isn’t a “hands-off” technology. The amount of invoices that make it through the process without needing human intervention is only 48.9% for the best-in-class software. In other words, even the best solutions only process half of the invoices without any kind of human interference.
This element matters when we look at AI claims at scale. Much of invoice-processing is repetitive, specific information. It’s matching invoices to purchase orders, ensuring numbers and set names align.
Can you imagine the discrepancies possible with generative AI, the tools believed to be writing novels and creating art?
For the investor, risk is everything. It’s why advisors put so much emphasis on risk tolerance levels and questionnaires. It helps us to determine strategy.
Reviewing risk can also help you better make investment decisions. But we seldom look at the drawbacks of technology, especially if they appear to be earning high returns.
However, if we look at value-investing, reviewing a company, its industry, and associated risks are essential.
I’ve identified three major risk areas for AI-related businesses below.
With new technology comes new questions of legality. Remember when the internet first began to pick up steam? There were early discussions about anonymity, what’s acceptable to place online, what data businesses can collect, and other concerns.
AI is going through the same process.
In fact, there are over 20 lawsuits over the use of AI technology, most of them relating to copyright. These cases even involve established businesses, such as Microsoft, OpenAI, Getty Images, Meta (formerly Facebook), and Thomson Reuters.
You see, AI “creates” writing or art by pulling information from its database. A significant problem for these companies is that many of these databases are built off of the work of others, such as books, newspapers, photography, and art. The original creators of these items are not compensated, even as the AI companies earn revenue from using their work.
Artificial intelligence tools, especially generative AI software, carry a considerable risk of copyright infringement and plagiarism, which can cost a company legal fees.
Another critical risk is supply chain management. Delays in design, manufacturing, testing, and distribution can result in significant sales delays and revenue bottlenecks for these companies.
According to NVIDIA (NVDA)’s 10-Q, a document filed to the SEC, stated that industry risks, such as export controls on semiconductors and other parts, are significant problems. Geopolitical tensions, such as the war in Ukraine or rising tensions with China, and conflict minerals create an unstable environment for the creation and management of AI technologies.
Another significant concern regarding AI is its immense use of energy. For example, if NVIDIA’s AI adoption continues on the same trend, which would be 1.5 million AI server units per year shipped until 2027, it would consume more energy than what small countries use in a year.
This problem isn’t limited to one company. One study found that AI training doubled computing power every 3.4 months on average. Another report found that a single ChatGPT query can generate 100 times more carbon than a Google search. Training chatbot models, like ChatGPT, release even more carbon—the equivalent of 1 million miles driven by a gasoline-powered vehicle.
In other words, generative AI products often negatively impact the environment.
Another clear cause for concern is the magnitude of returns. In NVIDIA’s 10-Q quoted above, filed in May 2024, their Data Center revenue alone was up by 427%. This part of their business encompasses its AI and cloud technology. The total return since 2022 is 629.15%.
Such high revenue increases aren’t sustainable. And it’s possible the leadership knows it.
At the same time, the CEO and founder Jen-Hsun Huang, has been selling off millions of NVIDIA stock since June of this year. Since that time, he has sold shares worth $365,104,470.
NVIDIA, represented by the stock ticker NVDA, is the golden child of AI companies. Founded in 1993 by Taiwanese-American engineer Jensen Huang, NVIDIA became known for its software and hardware enhancements to computing. One such example is its graphic processing units (GPUs), also known as graphics cards, used to vastly improve video game graphics. Over the past 30 years, the NVIDIA team has scaled operations across the globe, increasing their reach and expanding into new product markets—including AI.
But how did a company known for pro-video game graphics turn into an AI powerhouse?
GPUs can do more than make videos and images look better on the computer. These chips can also rapidly process complex complications—making them ideal for other functions, like blockchain transactions, smart car driver assistance programs, or artificial intelligence modeling. These new capabilities dramatically increased the demand for NVIDIA’s GPUs, raising prices and increasing the company’s value.
And, for an investor, the company looks solid on the surface. Last year, its Data Center revenue skyrocketed by 427% within the last year, its gross profit margin was 76.3%, and it owns approximately 80% of the GPU market share.
That said, it’s easy to get carried away by the upsides. Let’s look at the risk factors. After all, there must be a reason that the founder is consistently selling off stock. And past performance, as we all know, isn’t indicative of future success.
Today’s world is very different for this tech giant—and those in a similar position. Here is the breakdown of risks and considerations:
In 2022, the Federal Trade Commission (FTC), as well as regulatory bodies in Asia and Europe, were concerned about NVIDIA’s proposed acquisition of Arm Holdings PLC for $40 billion. Regulators were concerned that the merger would have given NVIDIA an unfair advantage and reduced innovation. When the acquisition was successfully blocked, both companies recovered quickly, but Ndviai took a loss. The company’s year-on-year operating loss for 2023 was attributed to the blocked merger. And while revenue increased by 214.6%, operating losses accounted for 529.86% compared to the previous year. With few companies in the GPU space, there is little ability to grow in the long term from acquisitions or mergers.
A significant risk listed in the Specialized Disclosure section of NVIDIA’s 110-k from February 2024 highlighted the impact of conflict minerals on reporting. GPUs and similar chips are made with rare minerals from regions like the Democratic Republic of Congo, and establishing a transparent supply chain is essential to maintain regulatory compliance across multiple regions. As a global company, it is required to invest heavily in due diligence—any slip up can cause significant brand reputation damage and negatively impact the company’s value.
According to Lucidworks, only 63% of global companies plan to increase AI spending over the next year—a 47.7% decrease from the year before. Why? Companies cite concerns over implementation costs and lack of ROI from previous investments in generative AI. Furthermore, 93% of all consumers believe it’s important to regulate AI—which may increase expenses and slow down innovation in the industry overall.
Generative AI companies are facing significant legal pushback, and NVIDIA is no different. In Nazemian and Dubus v. NVIDIA, two class actions are alleging that NVIDIA is violating their copyright by using their work to train its AI model, Nemo Megatron-GPT. And the case involves big-name screenwriters, novelists, and journalists. Plaintiffs include Abdi Nazemian, Andre Dubus III, Brian Keene, Stewart O’Nan, and Susan Orlean.
Then there’s just pure math. Using institutional investor tools, I can easily review stock predictions. While no forecast is set in stone, it can help determine how much a stock can affect a portfolio.
I looked at the Upside/Downside ratio for NVIDIA and similar companies investing in AI. The Upside/Downside ratio works like this:
Ideally, your downside should be low and the upside high. This is not the case for many AI-based stocks currently. Let’s take a look at what they and the S&P 500 look like right now:
As we can see, most of the companies investing heavily in AI have significantly higher downsides than upsides. Only Tesla and Apple have more positive upsides than downsides, and the S&P 500 is largely balanced in comparison.
This doesn’t mean the stocks are necessarily good or bad — only that it’s important to pay attention to volatility and take caution when investing in new technologies.
You don’t need to be an expert in every industry you invest in. But once everyone is talking about a specific industry or stock buy, taking a moment to pause is essential. Review an asset’s prospectus, ask your friends, discuss it with your advisor, or speak with professionals from that industry.
That said, AI is a new technology. A new development can rapidly change the landscape and major players. That’s where the excitement—and volatility—come from. You don’t need to shy away from AI stock but rather know the risks involved to avoid the hype.
Because when we focus on solid data and company fundamentals, we can make better-informed investing decisions.
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