“Themes” for Investing in Artificial Intelligence

The race to develop and deploy Artificial Intelligence (AI) tools is on.

According to JPMorgan data, US and global private investment in AI totaled $53 billion and $94 billion, respectively, in 2021. This level of investment marked a more than fivefold increase in real terms compared to the five years prior, and it also came before the release of Chat GPT.

Business investment for new AI computing data centers has soared since. By some estimates, business investment (capex) could reach $1 trillion in the space within the next 10 years. If an investment approach is ever about ‘following the money,’ AI is where it’s going.¹

The big question for investors is, where will new AI investment dollars flow? 

The future of AI should be thought of in two ways. First, what infrastructure is needed to build and power all of the AI tools? And second, what new businesses and systems will emerge because of AI, and who will lead this new future of business?

Starting with the first point, infrastructure, investors should focus on the “tech stack” needed to power AI, with a greater emphasis on specific types of semiconductors, supercomputers, data centers, and cloud computing services. Companies will also need to invest in infrastructure for AI training (teaching AI how to work for and within your business), increasingly advanced models, novel approaches for managing data, and new applications for humans to leverage AI systems.

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The New “Tech Stack” for Generative AI

Digging in more specifically to where billions of new dollars will need to be invested, we find four distinct categories:

• AI servers – demand for AI servers has been greater in 2023 than anyone expected, as there’s now an understanding of the compute intensity required by sophisticated AI models. Major stakeholders in the AI race – along with startups – need NVIDIA’s GPUs and the servers they accelerate. But servers require much more than GPUs, which means suppliers of CPUs, networking components, power supply, cooling systems, storage, and memory chips also stand to benefit from rapidly increasing demand.
• Memory – AI servers require far more memory and storage capacity than traditional servers, which implies that the proliferation of generative AI will mean exponential demand for memory. According to Blackrock, “a major memory chip producer predicted that 2025 will be a record year for sales on increased volume and recovery of prices (memory is currently in a cyclical downturn).” Since advances in processing speed have outpaced increases in memory bandwidth, there is rising market demand for ‘high-bandwidth memory,’ or HBM.
• Electronic Design Automation (EDA) – semiconductors are notoriously complex to design and make, and there is a notable shortage of skilled workers available. EDA is a new software technology that allows chip designers to simulate and design chips virtually, which not only saves on cost but also opens new doors for innovation. According to Blackrock, “a leading provider of EDA tools expressed confidence that AI will funnel new types of customers to EDA and stated that, for the first time in history, software is outpacing hardware.”
• Accelerated Computing – according to NVIDIA CEO Jensen Huang, “If you’re not using accelerated computing, you’re just burning power, wasting money.” Huang likened general-purpose computing as like having a workforce with no specialist. With accelerated computing, Huang says that over the last 10 years they have “reduced the cost of computing by nearly a million times….. the next 10 years, we’re going to be another million times.”

The second area of focus comes in two forms:

1. Productivity Enhancement, New Services, Lower Costs – enterprises are likely to use generative AI to eliminate redundancies, drive productivity higher, reduce operational expenses, grow without hiring, and deliver new services. Together, these improvements can all drive earnings higher.
2. Emergence of New Companies – there will almost certainly be the emergence of new companies that were never previously possible, much like the Ubers and TikToks of the world—which came into existence only after the iPhone did.

Bottom Line for Investors

In short, the investment opportunities with generative AI could come in the form of infrastructure, identifying companies and sectors that produce semiconductors, silicon, AI servers, memory, and all of the other infrastructure elements that are needed to power generative AI. The second opportunity is less knowable since many of the new businesses and systems that come into existence cannot be predicted. There will be winners and losers, so it will be important to approach the sector with patience and diligence.

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• 4 myths of a properly diversified portfolio
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• How to create a truly well-diversified portfolio

Get our free guide, Is Your Investment Portfolio Actually Well-Diversified?, ⁴ to learn how to create a truly diversified portfolio.

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¹ Black Rock. June 15, 2023.

² Zacks Investment Management may amend or rescind the Is Your Investment Portfolio Actually Well-Diversified? guide offer for any reason and at Zacks Investment Management’s discretion.

³ Black Rock. Expert Insight. 2023.

⁴ Zacks Investment Management may amend or rescind the Is Your Investment Portfolio Actually Well-Diversified? guide offer for any reason and at Zacks Investment Management’s discretion.

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