While there remain some uncertainties in how the technology will roll out, investors are seeking good opportunities. Choosing the best of them, however, requires deep analysis of a number of critical issues.
In considering investment candidates in this space, the following characteristics are particularly important:
• Innovative expertise (the ability to attract and retain the very best talent in electronic engineering);
• Computing capacity (a proven track record of developing industry-leading capacity and capabilities, including developing supercomputers);
• Data quantity (companies with ownership of large data banks on which studies and analyses can be made have a strategic competitive edge);
• High data quality (the value of output is a direct function of the quality of the data on which conclusions are made).
• Lastly, we want to see leadership on regulation and security. Some companies have been at the forefront in these areas, and we would be wary of those more hesitant around governance and security.
AI is truly a revolution in data analysis and there are many investment opportunities that now present investors with a wide, but also potentially confusing, array of options.
We think they can be broadly grouped into three different categories, which investors can consider for a spread of exposures.
The Critical Enablers
These companies have been instrumental in developing leading AI technology, enabling the computing capacity and supercomputer manufacturing. They include Alphabet and Microsoft, both of which have been at the forefront of developing leading AI technology. Microsoft is already reaping the rewards of its partnership with Open AI, and it has large scope to upsell its AI into its technology stack.
A very important contributor to this group is the semiconductor industry and its supply chain. Among the main players here are semiconductor design companies such as Nvidia and AMD. Companies involved in semiconductor manufacturing include TSMC and their equipment suppliers such as ASML, which has an unrivalled position in specialist EUV lithography technology.
Also well placed to benefit are companies developing the software to design chips, including Synopsys and Cadence Design Systems, whose specialised software should allow it to capitalise on a surge in datacentre and AI chip and system design activity.
The Cloud Service Providers and Data Centres
AI-related software will predominantly be run in the cloud, and the handling and storage of data in the cloud will hugely be accelerated by AI. This should benefit the likes of Alphabet, Amazon and Microsoft. In China, the main listed beneficiaries should be Alibaba and Tencent, which own the largest cloud businesses in that part of the world.
We have a large position in Alphabet and believe AI has scope to scale its cloud business so it is a much more significant profit driver. Amazon AWS, the largest cloud business globally, should see a reacceleration of growth due to AI after a recent period of deceleration.
Importantly, there is expected to be large capital spending related to AI by cloud companies, which should benefit some of the firms involved in building out the data centre infrastructure, including networking companies such as Arista Networks and Cisco Systems.
The Adopters
AI is expected to penetrate multiple industries and there are many types of usage of the technology. Our focus is to identify entrepreneurial companies that hasten themselves to adopt AI quickly and use it to enhance their competitive strengths. We have already seen the likes of Adobe, Oracle and Salesforce on the front foot with their AI deployments.
Through applications like Photoshop, Adobe has been deploying AI tools to its customers for several years, without them really being aware of it. It has now developed a very sophisticated tool for images and video called Adobe Firefly, which it plans to integrate across its full suite of products.
Not only will this significantly increase its addressable market, but it also will provide tremendous upselling and pricing power opportunities, which should support its strong growth trajectory and reinforce its strategic competitive edge.
Finally, Accenture is probably the lowest risk way to invest in AI. It advises many businesses on their technological needs and developments, and now also specifically on their AI strategy, implementation, and maintenance. More than three quarters of its consulting work is on new technologies and on a recent earnings call it confirmed work on 100 generative AI projects already, providing a sense of the scale and speed of the adoption opportunities in this revolution in data analysis.
Gerrit Smit manages Stonehage Fleming’s Global Best Ideas Equity fund
