The rapidly evolving generative AI technology — the technology powering applications such as Chat GPT — presents compelling opportunities for investors across a range of industries.
Today we are in the infrastructure investment phase of generative AI, so we are seeing the biggest impact on the infrastructure-exposed sectors such as semiconductors. Over time we expect this to broaden to software, internet, and beyond.
We also recognize there is much uncertainty — and sometimes unsettling speculation — about the longer-term consequences of AI. Investors must be flexible and open-minded, with the knowledge that implications for specific businesses will shift — positively or negatively, and sometimes significantly — over time.
While ChatGPT dramatically raised awareness of generative AI, the technology has been in development for years by many businesses. However, as ChatGPT demonstrated, the underlying technology has taken a huge step forward. Businesses now have the computing horsepower to enable these large language models to be trained with relative ease and provide users with extremely powerful productivity tools.
Time it took for selected online services to reach one million users
Source: Statista using company announcements via Business Insider/LinkedIn, 2023.
1 One million backers.
2 One million nights booked.
3 One million downloads.
Among the first to potentially benefit: Semiconductors
The semiconductor industry has seen the earliest upward shift in fundamentals from generative AI. We expect the industry may continue to benefit, as semiconductors power the underlying servers that enable AI. Semiconductor content in AI servers today represents only about 3% of the total semiconductor market. However, this is increasing quickly as companies eager to participate in the generative AI opportunity are investing in servers to ensure they have the required computing capacity.
AI servers require 10 times the semiconductor content of traditional servers. A vital component of AI servers are GPUs — graphics processing units. Based on our analysis of GPUs required for initial ChatGPT training, we expect the total addressable market for GPUs — already large at an estimated $40 billion — to more than double in the next three years as generative AI is adopted across search, productivity tools, and creative workflows.
Hyperscalers: A potentially dominant force as AI demand grows
The rapid pace of change in generative AI technology makes it challenging to identify possible winners, but one area of our focus is hyperscalers — large cloud service providers such as Microsoft, Amazon, and Google. These hyperscalers are spending aggressively now to ensure they are well positioned for a future led by generative AI.
Based on the cost and infrastructure required to develop large language models, hyperscalers have the potential to dominate this market and may benefit from a growing wave of demand for generative AI tools and services.
In other areas, we believe the near-term effects of generative AI are more limited. For e-commerce, we’re seeing early examples of plug-in software that enables consumers to interact with retailers in a more conversational way, like a concierge or personal assistant.
Eventually, this technology could be built into consumer-facing websites. For e-commerce payments, AI could play a role as a fraud detection tool. For telecommunication companies, we see limited disruption, although they could benefit as bandwidth-intensive AI applications drive growth in data usage.
Areas of focus today
The potential investment opportunities from generative AI span multiple sectors and industries, but hyperscalers and semiconductors are key areas of focus.
In our view, MSFT is a dominant hyperscaler at the forefront of generative AI, from both a technology and a brand awareness standpoint.
- Azure, MSFT’s cloud computing platform, has seen a wave of new customers as well as growing demand from existing customers due to MSFT’s leadership in generative AI technology.
- Microsoft 365 Copilot is a soon-to-be-launched digital assistant powered by AI that will be an embedded feature in many of Microsoft’s existing applications, such as Office. We believe it could offer significant value for customers in terms of productivity gains, and it is likely to provide MSFT with increased pricing power across its products.
This semiconductor company is a leading supplier of GPUs, the accelerators needed to power generative AI. In our view, it has the right “mousetrap” at the right time. Investors have already recognized NVDA’s potential, as it is trading at one of the highest multiples in the semiconductor industry. However, we cannot overlook the enormous opportunity generative AI brings to NVDA.
- NVDA was already generating $15 billion — about 50% of its total revenues — from AI demand, and we believe generative AI will act as an additional leg of the growth stool.
- One key advantage is the strength of NVDA’s parallel processors, which will be used for both model training and inference.
Advanced Micro Devices (AMD).
A key competitor of NVDA, this company may be underappreciated as a strong alternative provider of the GPUs that power AI.
- We see potential in AMD’s MI300X AI accelerator chip. It could allow the company to participate in the full breadth of the GPU market, which has the potential to exceed the CPU market in size over the next 4 to 5 years. Only a small market share gain could be meaningful to AMD’s bottom line.
- We believe AMD is currently attractive from a valuation perspective, trading at just 20x fiscal year 2024 earnings per share.
Many open questions for investors
We believe generative AI is an unprecedented technology breakthrough, and many investors are rushing to identify potential winners and losers. In our view, this new AI landscape requires significant fundamental research and analysis and the flexibility to adjust to rapidly evolving new offerings and yet-to-emerge challenges.
About the authors
Robert Gray is an analyst in Putnam’s Equity Research group, focusing on the technology sector. He conducts fundamental analysis of companies in the media, telecommunications, internet, and information services industries.
Andrew O’Brien, CFA, is Assistant Director of Equity Research, providing oversight and strategic direction to Putnam’s team of equity analysts. In addition, he is a portfolio manager of Putnam Research Fund and is an analyst in Putnam’s Equity Research group, focusing on the U.S. technology sector.
Di Yao is a Portfolio Manager of Putnam Global Technology Fund. In addition, he is an analyst in Putnam’s Equity Research group, focusing on the non-U.S. technology sector assessing valuation of companies in the semiconductor and hardware industries.
The inclusion of specific securities information in this commentary should not be interpreted as a recommendation to buy or sell or hold any security. It should not be assumed that an investment in the securities mentioned was or will be profitable.
Putnam Research Fund holdings as of 6/30/23: Advanced Micro Devices: 1.10%, Alphabet: 3.79%, Amazon: 3.38%, Microsoft: 7.20%, NVIDIA: 2.64%.
Putnam Global Technology Fund holdings as of 6/30/23: Advanced Micro Devices: 3.90%, Microsoft: 19.21%, NVIDIA: 7.41%. Alphabet and Amazon were not held as of 6/30/23.
The views and opinions expressed are those of the authors, are subject to change with market conditions, and are not meant as investment advice.
Our investment techniques, analyses, and judgments may not produce the outcome we intend. The investments we select for the fund may not perform as well as other securities that we do not select for the fund. We, or the fund’s other service providers, may experience disruptions or operating errors that could have a negative effect on the fund. You can lose money by investing in the fund.
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