Capitalise on AI growth beyond the headliners

In a previous edition of Global Equity Edge, we assessed the structural and cyclical implications of AI for the global economy. While it is clear from our long-term forecasting that AI is likely to have a profound impact on many industries, so far the market impact has mostly been dominated by the Magnificent Seven group of US mega-cap technology-related stocks.

The strong performance of the Magnificent Seven has been supported by equally strong earnings growth, and these stocks are also underpinned by solid balance sheets. But much of the future earnings potential now appears to be discounted in valuations.

To demonstrate, let’s take a look at two high profile AI companies: Nvidia, the US-listed designer of specialist graphics processing units, or GPUs, that are widely used in AI and machine learning; and OpenAI, the developer of the generative AI large language model, ChatGPT. Both companies are at the heart of the AI revolution, but present challenges for global equity investors looking to gain exposure: Nvidia, which is a Magnificent Seven stock, was recently traded around 45 times forward earnings (compared to an average of around 23 times for the S&P 500), and doesn’t pay a dividend for income investors; and OpenAI is privately owned, so is not accessible via public markets (source for data: Bloomberg, as of 19 July 2024).

However, Nvidia and OpenAI don’t exist in a vacuum. They have suppliers and customers that can help investors gain access to their growth, from companies providing the hardware, software and AI infrastructure that allow Nvidia and OpenAI to operate, to the host of companies further downstream that are using AI to drive down costs and boost revenues through the development of new, or enhanced products and services.

AI beneficiaries come in many shapes and sizes

Stocks further upstream in the AI value chain include providers of AI infrastructure, such as French electrical engineering group, Legrand, which provides components for AI data centres that help power OpenAI’s servers; and chipmakers, such as Taiwan’s TSMC, which makes Nvidia’s GPUs.

Other upstream AI suppliers include Dutch microchip equipment company, ASML, which makes the machines that TSMC uses to make Nvidia’s AI chips, and Shin Etsu, a Japanese company that produces the silicon wafers onto which these chips are printed. Training AI models also requires massive amounts of computer memory, which is helping drive demand for DRAM (dynamic random access memory) from memory chip makers, such as South Korea’s Samsung.

Further downstream, the focus is on finding stocks that are actually able to make money from the application of AI technologies. While many companies may talk about the potential benefits of AI, there is much uncertainty in earnings forecasts regarding AI’s future impact across industries. Some companies are already seeing a big productivity uplift from using AI to run customer service operations, for example. For investors, the important thing is to cut through the noise to identify quality companies that are actually able to generate tangible revenues from AI today.

The opportunities here are incredibly diverse, ranging from Deere & Co., a 100-year old US-based tractor maker that is benefiting from strong demand for its AI-enabled sensors that can help farmers reduce fertiliser use, through to Keyence, a Japanese maker of automation sensors and machine vision systems, which is using AI to analyse vast amounts of vision data to improve the accuracy of its products and drive efficiency savings.

And in the UK, a market that is trading at a historically-large discount to the US, there is RELX, a data analytics company, which is using AI to monetise its vast databases. RELX is already generating new revenues from the legal industry by integrating large language models into its proprietary case law database, allowing law firms to search historical case data accurately and at speed.