AI: Investment Opportunities and Strategies

AI: Investment Opportunities and Strategies

An exploration into the transformative power of Artificial Intelligence (AI) technologies, focusing on the predicted market growth, investment prospects, potential winners, and strategies to leverage in the fast-growing sector

Image source: Morgan Stanley research

Artificial Intelligence, once an area of interest confined within the bounds of IT Research and Development, is now rapidly emerging as a giant in the tech industry. Its predicted market value, a staggering US$3 trillion by 2029, according to research from Morgan Stanley, emphasises its potential and the opportunities it brings. This phenomenal growth isn’t mere conjecture; we’re already witnessing the rise of AI, albeit in its nascent stages.

At the heart of AI development, we have machine learning, which constitutes the initial phase of AI adoption. However, the scope extends far beyond this, ultimately leading to a much larger AI market focusing on model deployment and endpoint or edge AI inference. The potential market value for AI technology, covering areas like semiconductors, hardware, and networking, which currently stands at around US$98 billion, is projected to reach US$275 billion by 2027, offering a lucrative arena for investors.

Identifying AI Leaders

The influence of AI extends globally, with 37 identified frontrunners commanding a combined market capitalisation of around US$2.8 trillion. These leaders are distributed across various regions, with the United States housing 50%, followed by Taiwan at 21%, Korea with 14%, Europe at 10%, and Japan and China trailing with 2-3%.

Morgan Stanley wrote in a recent research note: “Most are well positioned to thrive in our forecast scenario of the AI technology market TAM (Total Addressable Market) nearly tripling over the next four years from US$90bn to US$275bn – significantly outgrowing the overall AI market. AI leaders are generally showing high growth and returns; consensus shows three-year average earnings-per-share growth of 24%, which is more than twice the earnings growth of global stocks on average, and revenue growth of 22%.”

In terms of growth, the AI semiconductor market, currently valued at US$43 billion, is expected to almost triple to US$125 billion in the next three years. This growth rate surpasses that of the overall AI market. However, it’s not just about market expansion. AI leaders show impressive performance, with an average three-year EPS growth of 24%–over twice the global average – and revenue growth at 22%.

How can investors determine the best companies leading the AI transition? A simple way to make this assessment is to examine the tech supply chain to understand which sections benefit the most from AI – not just in terms of revenue exposure but also in relation to how this exposure changes over time versus traditional business. Understanding the quality of earnings derived from AI–is it a volume or pricing story–and comparing the ‘price’ relative to future growth and upside potential is crucial. This approach helped identify the aforementioned AI leaders.

AI: Early Stages and Future Projections

Despite the rapid advancements in AI, we’re still far from peak metrics. It would be premature to base valuation decisions on past peak multiples for AI. Unlike the dot-com boom, where many companies without a solid business case crashed, today’s AI front-runners are mostly well-established organisations with good cash flow characteristics.

The AI investment playbook presents four key strategies. First, identify companies best positioned to maximise technology adoption globally. Second, select stock picks that are not just in the right place at the right time, but also have the internal knowledge and strength to fully commercialise the AI opportunity in the long run. Third, be prepared for possible tactical pullbacks and consider any dip as a buying opportunity. Lastly, utilise periods of market weakness to build and invest time in the market to reap benefits.

However, it’s essential to exercise caution. AI, like any technology, has its pros and cons. While it brings immense opportunities, there’s also the risk of overhyping AI in corporate forward guidance. It’s vital to differentiate between companies with the potential to outperform and those merely using AI as a buzzword.

Potential risks ahead also include the dependence of the chip cycle not just on the AI side but on the wider global cycle. Moreover, any overarching visions regarding how AI might transform the world must be tempered by physics, ethics, and law. Morgan Stanley remains ‘constructive’ on AI stocks based on the following criteria:

  • Which elements of the technological supply chain are poised to reap the most significant benefits from AI? They’re analysing the extent of revenue exposure and how this exposure is transforming when juxtaposed with their conventional business operations. Given AI’s status as a necessity to maintain relevance and a powerful agent for future relative growth, this evaluation is imperative.

Current discussions about technology shares revolve largely around their AI offerings. Although, as it stands, they account for only 3-15% of hardware or semiconductor sales, a marked increase is anticipated due to the significant and growing incremental AI Total Addressable Market (TAM).

  • How about the quality of earnings? They identify narratives of volume and pricing to discern the qualitative traits of incremental AI revenues.
  • How does the ‘price’ fare when compared with the prospective growth? They juxtapose current market-implied Return on Equity (ROE) values with standard historical returns among the entities they cover. A majority of investors expect the next decade to mirror the previous one.

In broad strokes, the valuations in the tech sector may appear somewhat inflated, but they don’t seem substantially misaligned from fundamentals. The relative valuations, however, call for closer scrutiny, which is believed to partially reflect the generally bearish sentiment in the market this year. The prevailing opinion is often influenced more by recent happenings than by likely future outcomes, leading to an assumption that shares are overpriced based on short-term surges.

“We believe this group is poised to recover faster in 2024 with a more strategic runway thereafter. We believe we are still early and far from bubble metrics; for the most part, the multiples for AI stocks have not expanded beyond earnings or expected future cash flows.”

AI promises to be a game-changer in the tech industry. As the market continues to expand, it presents a wealth of opportunities for investors. By understanding the landscape, being savvy about potential pitfalls, and implementing effective strategies, one can harness the benefits of this AI revolution.

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