By Timothy Greaton, Senior Portfolio Manager at Nikko Asset Management
AI is now near the exponential growth area of the s-curve, and it is surprising people in terms of the speed of its evolution. Given our focus on fundamental change, we are excited about the opportunities that have emerged with the recent advancement of AI.
In a recent report, market intelligence firm IDC estimates that worldwide spending on AI, including hardware, software and services for AI-centric systems, will hit $154bn in 2023, up 27% from 2022. According to IDC, the global AI spending will surpass $300bn in 2026, and the current integration of AI into numerous products will result in a compound annual growth rate (CAGR) of 27% from 2022 to 2026.
Hardware producers and chipmakers riding the AI growth
The rapid advancement of AI technology has brought about a surge in the production of AI-microprocessors, AI accelerators and many other hardware that enables high performance computing, which is the ability to process data and perform complex calculations at high speed. This trend is likely to gather pace, benefiting many high-end chipmakers and AI-focused hardware manufacturers.
For the high-end hardware and AI-centric microchip markets, American GPU manufacturer Nvidia Corporation and Taiwanese chip manufacturing giant Taiwan Semiconductor Manufacturing Company (TSMC) are best positioned to ride the AI boom, as the go-to suppliers for AI-focused tech companies, in our view.
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In the high-end semiconductor market, TSMC, with a near monopoly on the production of three-nanometre cutting-edge chips, appears well poised for growth as AI takes off. To begin with, Nvidia uses TSMC as the main foundry for the production of GPUs and all of its high-end processors. The Taiwanese chipmaking titan also leads as the main foundry for ASIC chips for tech hyperscalers, such as Google, Intel/Havana, Amazon and others. Chips for high-performance computing (HPC) now accounts for over 40% of TSMC’s sales and that trend will most likely continue in 2024 and 2025, in our view.
Logic chips, which are generally considered the “brains” of tech equipment and devices, process information to complete tasks. Central processing units (CPUs), GPUs and neural processing units (designed for machine learning applications) are examples of logic chips.
A decade ago, Intel was the dominant producer of logic chips. Since then, TSMC, which is the largest foundry company in the world with over 45% of market share in logic chip production, has taken the market away from Intel, and that trend is accelerating today, given the strong demand for high-end logic chips.
Geopolitical risks
Investing in the AI segment of Asia, while rewarding, does have its fair share of risks, particularly with escalating geopolitical risks from US regulation. An example is the CHIPS Act that was passed by Washington in 2022 to bring semiconductor manufacturing back to the US by way of legislation.
In October 2022, the US barred its domestic firms—including major chipmakers—from supplying semiconductor chips and processor-making equipment to Chinese companies. In late 2022, the US government broadened its crackdown on Chinese technology companies by adding over 20 Chinese firms in the AI chip sector to the US Commerce Department’s restricted entity list.
The US has shown that it will continue to aggressively legislate in the AI and chip segments and may add more companies (particularly those from China) to the US Entity List, which adds another layer of risk for the Asian semiconductor and hardware sectors. At the moment, Chinese technology platform companies have limited access to high-end microchips manufactured by US chipmakers, and as chip upgrades continue to progress, the Chinese players could find themselves further behind the technology curve.
ESG considerations
While we see many opportunities in the world’s second largest economy, Asia is more than just China, especially in the technology space. Indeed, South Korea and Taiwan are amongst the most innovative economies in the world with innovation leadership in the realms of hardware and semiconductor technology.
We are just beginning to understand the impact of AI on other industries outside of technology and its implications on data ownership, utilisation of information and human rights. AI technology, for instance, is likely to have huge effects on labour forces, with the potential to displace many white-collar jobs. At the same time, widespread adoption of AI can have an impact on the environment as AI models and algorithms require substantial computing power, which in turn consumes considerable amounts of energy.
All in all, there are AI-related ESG risks as well as legislation threats to consider when investing in AI companies, which could potentially be subject to increasing restrictions in the future.
