While it’s clear that artificial intelligence (AI) will reshape our future, the challenge investors face today is identifying the AI leaders of tomorrow. The right investment into the right company today could yield spectacular long-term returns, if only you know which horse to back.
Without a lens into the future, investors may feel overwhelmed in trying to decipher a clear winner. The good news, says Sameer Singh, Research Analyst at Old Mutual Wealth Private Client Securities, is that the AI universe is far broader than merely a handful of software and systems developers.
“It is clear that while AI has seen immense growth over the past few decades, it still has a significant runway for evolution and growth. Not only are we dealing with a technology that is in a nascent stage of development and deployment, but applicability and adoption rates vary significantly across sectors.
He says despite the uneven adoption of AI across industries, Singh believes that there are ample avenues across the risk spectrum to attain exposure to this theme. “The AI value chain is as deep as it is broad, with investment opportunities spread across seven tiers.
“Top of this pile sits the semiconductor chip makers whose hardware powers the trillions of AI and machine learning calculations while working with massive datasets.
The upside potential for these producers is evident in the growth of stocks like Nvidia, which is up 1500% over the past five years. A good way to get exposure to these companies without betting on any one technology is via the iShares Semiconductor ETF, which has the added benefit of offering investors exposure to other fast-growing themes like cloud computing and online gaming. Individual companies such as Taiwan Semiconductor, Intel, Qualcomm, and Micron Technology are also well positioned to benefit.
In many respects, solution providers in the next tier are already established and have a far greater scope for growth. These are the infrastructure and cloud providers that offer the hardware infrastructure and services needed to host AI systems. Amazon, Microsoft and Google already have considerable clout, followed closely by IBM and Alibaba.
“We favour a more balanced approach to AI investing, supplementing our semiconductor exposure with meaningful positions in Accenture, Alphabet, Amazon and Microsoft, which provide exposure to the largest of the Platform and Infrastructure providers but also to the Enterprise Solutions, and Models and Algorithms markets,” Singh explains.
It’s no surprise that many of the big tech names — including Google, Amazon, Microsoft and IBM — all play in the models and algorithm tier by offering AI software services tied with their infrastructure and platform offerings. “However, there is a growing demand for cognitive algorithms that offer services such as conversational agents and bots, natural language processing, and vision,” Singh says.
“Increasingly, these services are being hosted in the cloud as AI-as-a-Service offerings. In this space, the largest companies are advantaged owing to financial resources to hire the best research and engineering talent and access to the largest datasets.
For those looking to spot the next major AI-player, keep in mind that for start-ups to be relevant, they need to be well funded, with deep research functions supported by intellectual property and access to quality datasets. Often though, start-ups with attractive intellectual property and researchers are easy targets for acquisitions by the larger firms, further favouring the most dominant companies.”
Rounding out the investment opportunities presented by AI are the providers of solutions to the market, as well as the users of AI looking to entrench or enhance their market positions. Big names like Salesforce, IBM, Oracle and SAP have benefitted from cross-industry AI adoption and dominate this space, although some start-ups are challenging for attention,
“There are many start-ups offering services that fill the gaps left by the incumbents and in some cases are even disrupting them. Companies like Farmers Edge in the precision farming space, and Affirm and Klarna in fintech are some of the names disrupting existing industries via AI.
“The key for start-ups will be their ability to solve and scale solutions to meet real-world enterprise needs. However, much like the algorithms space, the most promising applications and tools will be attractive targets for the larger players should they present a meaningful threat.”
The final link in the value chain, Singh says, is nation states and how they are responding to AI. In this respect, China is by far the leader, especially in security and facial recognition. Elsewhere, as with Europe, a focus on data privacy could hamper growth for start-ups and large companies alike..
“Even with large AI budget allocations, most nations collaborate with the largest corporates, such as Google and Microsoft, to implement their AI goals, which raises the question: Who will benefit most from the value created by these initiatives?”
He concludes that this abundance of AI investment opportunities offers a decent spread of known names and unknown possibilities in AI start-ups. And soon, rather than asking how to attain exposure to AI, we will rather be wondering which sectors have not been disrupted by this technology.
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