Source: Bloomberg Finance L.P, J.P. Morgan Private Bank. Data as of March 2024.

The valuation difference between the 2000s and today’s leaders does not guarantee that AI-themed stocks will continue to outperform the rest of the market. But in our view, it's clear that 2024 is not 2000, either.

Source: FactSet. Data as of March 2024. EPS: earnings-per-share. PE: price-to-earnings.

Transitioning to AI 2.0

Investing in the AI theme may have felt simple so far, as the biggest tech stocks have delivered very strong returns. We think something broader and more balanced will work better from here.

We see potential opportunities in two areas that we refer to as AI 1.0 and AI 2.0.

AI 1.0 is the infrastructure that underpins AI. As the demand for sophisticated AI capabilities grows, so does demand for a scalable and powerful infrastructure. The technology is built on the foundation of data centers and because most AI workloads live on the cloud, AI is fueling further cloud growth.

Leading cloud computing companies, including Amazon, Microsoft, Alphabet and Meta, have all rapidly rolled out multi-year investment plans to support the greater cloud capacity they will need in the AI era.

Demand from AI is rapidly consuming existing data center capacity, pushing companies to build new facilities. That, too, presents potential investment opportunities. Utilities may have to add coal- or gas-fired power and rising demand will undoubtedly spark infrastructure investments and efforts to develop a more energy efficient network, better cooling systems and new solutions to integrate renewable energy.

Another crucial layer in the AI infrastructure and the advancement of large language models (LLMs) such as ChatGPT is the computational power required to rapidly process the vast amounts of data. LLMs are computer programs that learn and generate human-like language using an architecture trained on large pools of data. These computations are processed by semiconductors known as graphics processing units (GPUs). A decade of significant GPU advancements means much quicker and more efficient performance today. The GPU advancement has rendered obsolete most computational electronics from before 2020 obsolete.

Nvidia, maker of industry-leading GPUs, recently estimated that total demand for GPUs might reach $2 trillion.² This includes $1 trillion from data centers and $1 trillion from work connected to AI such as training new LLMs, machine learning and scientific simulations.

Source: Bloomberg Finance L.P, J.P. Morgan Private Bank. Data as of March 2024.

There are many beneficiaries in the AI 1.0 environment, a theme that could continue to work as demand for new computing infrastructure and AI-enabled services grows, costs drop and consumers make greater use of the technology.

The AI journey is in its early stages, and past performance is no guarantee of future returns, but we think today’s leading AI infrastructure companies, such as the data center and cloud providers and the semiconductor manufacturers, should continue to grow as the market develops.

However, most of the unrecognized value in AI is in areas such as software and applications. We call this the AI 2.0 theme, which focuses on “adopters”. Industries such as customer service, health care, finance and logistics are poised for significant transformation through AI.

For example, the buy now pay later company Klarna recently began using an AI assistant powered by OpenAI. In the first month, it had 2.3 million conversations, or two-thirds of Klarna’s customer service chats, doing the equivalent work of 700 full-time agents.³

We believe maintaining a balanced portfolio exposure between AI 1.0 and AI 2.0 could be an effective way to potentially capitalize on the promise of this space.

Go global

U.S. tech giants have received much of the attention in the AI era dating back to the release of ChatGPT in November 2022, which drew new attention to the AI field and supercharged adoption of the technology. Investors may be missing the potential of AI leaders elsewhere.

China closely rivals the United States in the AI leadership race. In December, Chinese tech company Baidu said its generative AI chatbot had surpassed 100 million users, rivalling the 180 million users of ChatGPT.⁴

There is also considerable potential for AI adoption in India, a data-rich nation with widespread mobile device use. In time, this could translate into significant investment opportunities. South Korea, Japan and Singapore remain innovative hubs.

There are leading companies across Europe that could become major beneficiaries of AI as well, as the technology may help them become more efficient and profitable. These include Germany’s robust industrial sectors, France’s aerospace, automotive and chemicals firms and the Netherlands’ high-end tech manufacturing firms. The latter is also a primary hub in global logistics.⁵

Governments are beginning to understand the national security implications that surround access and control of their data.⁶ They are also strategically positioning themselves to harness the potential of AI. Competition is likely to intensify and new rules similar to the U.S. policy limiting the sale of some advanced AI chips to China may become more common.⁷

For all these reasons, investors who fail to approach AI through a global lens could miss out on true ground-breaking innovation.

The evolution of AI is only just beginning, and we expect that opportunities throughout the ecosystem will continue to emerge over the next few years in the form of countries, companies, and startups. In the coming years, we believe AI will rapidly change the way we think, work and solve problems, opening the path to ground-breaking innovation and change.