AI revolution: who’s profiting now from generative AI?

What is AI and why has interest in it taken off now?

Jonathan McMullan, Global Sector Specialist, Public Equities: “Artificial intelligence (AI) essentially means any technique that enables computers to complete tasks that typically require human intelligence. The concept of AI has been around for a long time and we already encounter AI a lot in our daily lives, often without knowing it.

“What really distinguishes generative AI from other hyped technologies of recent years, like cryptocurrency or the metaverse, is its tangible, practical nature. It's not just an abstract idea. Generative AI is already finding its way into everyday workflows, and we don't need to stretch our imaginations too far to see its transformative potential.”

Michael White, Global Sector Specialist, Public Equities: “The success of ChatGPT has been astonishing. It was the fastest platform in history to reach 100 million users, and is now at around 170 million. The speed with which this milestone has been reached suggests that societal habits are forming around the use of text-based generative AI, and that this practise is here to stay.”

What’s behind the new wave of generative AI apps?

Paddy Flood, Global Sector Specialist, Public Equities: “There are multiple factors contributing to the emergence of generative AI, including new(ish) architecture, enhanced computer power, increased availability and usability of data, and techniques which allow for the deployment of AI ‘at the edge’ – this means that computations are done on the device where the data is created, rather than on a distant data centre.”

What kinds of companies operate in the generative AI segment?

Ankur Dubey, Investment Director, Private Equity: “We need to understand the ‘technology stack’, i.e. the set of technologies needed to build a generative AI application. There are four layers to the stack:

1. The compute layer is the base of the stack. Generative AI systems require large amounts of computing power and storage capacity to train and run the models. Hardware (semiconductor chips) provides the computing power and cloud platforms like Amazon Web Services, Microsoft Azure or Google Cloud Platform provide services like virtual machines and storage.
2. Next comes the foundational model layer. Foundation models are systems with broad capabilities that can then be adapted to a range of different, more specific purposes. Arguably this is the most important layer of the generative AI stack.
3. Infrastructure layer. These are the tooling/infrastructure companies for apps that don’t use proprietary foundational models. Such apps need the infrastructure companies to help them fully utilise the technology available at the foundational level. Apps with proprietary models (like ChatGPT) do not need to rely on third parties in the infrastructure or foundational models layers.
4. Finally, top of the stack is the application layer, which is the software via which users interact with the underlying AI technology. This can include OpenAI’s ChatGPT product or an internally built solution like Schroders’ in-house AI product, named “Genie”.

What kinds of companies will make the most money from generative AI?

Ankur Dubey: “So far the ‘compute’ layer has emerged as a winner and the example of NVIDIA – with its share price up c.190% year-to-date (FactSet, as at 30 June) – shows the market agrees.

“That said, there is a question over whether the cutting edge technology being designed by NVIDIA today could be commoditised over time.”

Michael White: “For now, the ‘picks and shovels companies’ in the compute layer look like winners thanks to their existing dominant positions. As generative AI use cases grow, the demand for chips will grow too and NVIDIA is an expert with a dominant market share in the GPUs (graphic processing units) that are essential for AI processing.

“The cloud computing market is an oligopoly. At least for now, the big players like Amazon Web Services, Microsoft Azure and Google Cloud Platform will likely retain their advantage.

“But, we must remember that new tech enables new ways of doing things and creating entirely new businesses. It certainly seems as though this exciting new technology will provide new ways of doing things, but it is perhaps too early for those businesses to have emerged yet – this is what we are looking for”.

Mike McLean, Senior Investment Director, Private Equity: “Looking outside the tech industry itself, one possibility is that companies that are data-rich, for example those that own a large amount of proprietary user-generated content, could become valuable simply because of the value of that data in training AI models. AI is an increasingly important element of the types of companies being created in the market today”.

Jonathan McMullan, Paddy Flood, Michael White, Ankur Dubey, Mike McLean

Any reference to sectors/countries/stocks/securities are for illustrative purposes only and not a recommendation to buy or sell any financial instrument/securities or adopt any investment strategy.

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