Shawn Kim: The Double-Edged Sword of AI Technologies

The market for artificial intelligence technologies could reach $275 billion by 2027, but not all companies will be able to generate revenue. Here’s what investors should watch.

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Welcome to Thoughts on the Market. I'm Shawn Kim, Head of Morgan Stanley's Asia Technology Research Team. Along with my colleagues bringing you a variety of perspectives, today I'll discuss why A.I matters for investors and our outlook for the next 5 to 10 years in the evolution of A.I. It's Tuesday, July 11th, at 9 a.m. in New York.

In the span of just six months, open A.I has moved from being a niche IT research and development, to a key driver of what is set to become a $3 trillion IT spend by 2029. Despite this rapid progress, we're still in the early stages of A.I technologies. We believe today's machine learning stage of A.I adoption precedes a much larger future market when we reach the inference phase, which is where A.I would be able to make predictions based on novel data. And that, in turn, would eventually expand to an even bigger potential market in endpoint or edge A.I inference.

The A.I technology total addressable market or the TAM, which includes semiconductors, hardware and networking, is at $90 billion today and we estimate it will grow to 275 billion by 2027. That's more than half the size of the semiconductor market today.

This remarketable growth is actually led by semiconductors, where we see the A.I semiconductor market TAM tripling over the next three years from 43 billion to 125 billion, and signifying our growing the overall A.I market. Companies that we consider A.I leaders are generally showing high growth and returns, consensus shows a three year average EPS growth of 24%, which is more than twice the earnings growth of global stocks on average.

Our investment framework addresses three key criteria. One, which parts of the tech supply chain are the biggest beneficiaries of A.I, in terms of revenue exposure and how that exposure is growing relative to their traditional businesses. Two, the quality of those earnings and whether they are based on volume or pricing. And three, whether stock valuations reflect that upside potential.

We believe we are far from bubble metrics, although the market will inevitably compare A.I. to the dot.com boom. However, today's leading A.I companies are well-established with good cash flow characteristics, for the most part, unlike many companies that became casualties of dot.com collapse.

As we embark on what we view as a new, decade-long paradigm shift, we expect outperformance to come in waves and think we are currently very early in the enabling technology stage. And like so many technologies, A.I is also a double edged sword. There are companies that are in the right place at the right time now, but also have what it takes to fully commercialize the A.I opportunity over the long term. The flip side is companies that are less relevant to A.I products or services but will infuse optimism in their forward guidance via mentions of A.I.

While we expect A.I will be a growth driver for most, it will not generate revenue growth for everyone. Other potential risks include the fact that the chip cycle is not just depending on the A.I, but also on the wider global economic cycle. And furthermore, we believe any big visions of A.I's transforming the world as we know it must rest on a solid foundation of physics, ethics and the law, a big topic we will continue to follow closely and bring you updates.

Thank you for listening. If you enjoy the show, please leave us a review on Apple Podcasts and share Thoughts on the Market with a friend or colleague today.