The semiconductor industry has been hamstrung by supply chain issues for the past three years, triggered by the COVID-19 pandemic in 2020. That's when the demand for electronic devices skyrocketed thanks to shelter-in-place orders, and it led to a spurt in sales of personal computers (PCs), gaming consoles, and smartphones, among other things.
While the semiconductor shortage has eased somewhat since (partly because the pent-up demand for consumer electronics devices subsided and because chipmakers brought more capacity online), there is one area where chip scarcity is rearing its head once again.
Tech-focused business publication The Information pointed out last month that there was a massive spike in demand for server chips required for training and running artificial intelligence (AI) applications. That's not surprising as the AI chip market is expected to generate over $227 billion in annual revenue by 2032, clocking yearly growth of 30% over the next decade.
One company stands to win big from this market -- Nvidia (NVDA -0.83%). And the evidence for that can be seen in the emerging shortage of AI chips. Let's take a closer look at what's going on in the chip markets and how it might benefit Nvidia stock owners.
Customers are reportedly waiting to get their hands on Nvidia's chips
According to The Information, cloud infrastructure providers such as Amazon, Microsoft, Alphabet's Google, and Oracle are running at capacity thanks to the booming demand for AI software. Training and running AI software and workload requires graphics processing units (GPUs), which are chips capable of computing massive amounts of data.
Nvidia is the leader in the GPU market. The company controls 85% of discrete graphics cards that are used by gamers in PCs, while its share of enterprise GPUs (which are deployed in data centers for AI and other workloads) reportedly stands at more than 90%. So, it is not surprising to see that there is a waiting period for Nvidia's GPUs.
The semiconductor giant is reportedly sitting on an order backlog of two to three months for its cloud server chips. It is now feared that the waiting time for Nvidia's chips will slow down the development of generative AI applications. However, there are a few reasons why Nvidia may be able to overcome this shortage and speed up customers' AI initiatives.
The tech giant is setting itself up to take advantage of this massive market
Nvidia is reportedly placing more chip orders with its foundry partner Taiwan Semiconductor Manufacturing, popularly known as TSMC. Taiwan-based newspaper DigiTimes reports that TSMC has reportedly committed to delivering 10% to 20% additional chip on wafer on substrate (CoWoS) packaging to Nvidia that is meant for deployment in high-performance computing (HPC) applications.
More importantly, Nvidia's new generation of data center GPUs could reduce the number of chips needed to train and run AI models. The company's latest generation H100 Hopper data center GPUs are reportedly up to 9 times faster in training AI models and 30 times faster during inferencing. What's more, Nvidia is providing access to a much faster AI chip at prices that are reportedly two to three times its previous generation A100 data center GPUs that are powering Microsoft and OpenAI's popular chatbot ChatGPT.
In simpler words, Nvidia customers can now tackle much larger AI workloads with the H100 GPUs at an incrementally lower price as compared to the company's prior-generation A100 GPUs. So, it won't be surprising to see the demand for Nvidia's H100 GPUs improve in the future, especially considering that customers will need fewer of those chips to meet their AI-related needs.
Given that the H100 GPUs are priced significantly higher than their predecessors, Nvidia could witness stronger margins and enjoy robust earnings growth in the long run. The good part is that Nvidia's H100 GPUs are already witnessing healthy demand as they are powering multiple generative AI applications from different customers.
All this indicates that Nvidia could continue to dominate the AI chip market. One Wall Street analyst says that the AI opportunity could lead to a 5-times jump in Nvidia's stock price over the next decade. So, investors who are still of two minds about buying Nvidia stock following its 114% gains in 2023 can still consider buying the stock.
Of course, some might argue that Nvidia trades at an expensive 173 times trailing earnings right now. However, its forward price-to-earnings (P/E) ratio of 67 points toward a solid bottom-line jump, which means that investors with the risk appetite to buy this richly valued AI stock can still buy it as it can deliver more upside even after terrific gains in 2023.
