While the ideas behind artificial intelligence (AI) have been around longer than most investors have been alive, an area which had previously been regarded as the preserve of computer science departments has gone mainstream. Even so, the AI revolution is still in its infancy.
The key foundation models – the neural networks of AI trained on huge data sets – are rapidly increasing in size, delivering major gains in capability with each iteration. It will be interesting to see to what extent Google’s new Gemini model, which is due to be released this autumn, is an improvement on the large language models (LLMs) currently in use.
The wave of interest in generative AI is testament to the core attractions of the technology sector and its ability to find new growth.
Where are the opportunities?
When Microsoft founder Bill Gates said of LLMs: “I knew I had just seen the most important advance in technology since the graphical user interface", he wasn't exaggerating. Such technology will create numerous business and investment opportunities in the years to come.
To see how these might emerge, it is useful to compare the burst of innovation taking place today with the rise of the Internet in the 1990s. The Internet proved relatively slow to take off as it took time to build up connectivity around the globe; in 1990 only half a percent of the global population was online. Similar observations can be made of AI.
At present, most of what is being invested into AI is flowing to infrastructure. Companies like Google, Microsoft, Amazon, Meta and Tesla are still constrained by the availability of high-performance graphics processing units (GPUs) that are needed for both model training and inference. But once the infrastructure is built, the next wave of investment will see AI models rolled out into applications.
The potential breadth of these applications looks almost limitless. Healthcare drug discovery and diagnosis, education, art, finance will each be transformed by AI in time. And that, in turn, will fuel demand for new software, hardware and semiconductors.
Microsoft’s GitHub Copilot (for code generation) is one of the most successful scaled AI-based applications today. Globally, companies report a 20-40 per cent increase in developer efficiency from using Copilot, at a cost of around USD230 a year for enterprise users. Soon there will be Copilots for everything.
One development that distinguishes this tech investment cycle from its predecessors is that it favours incumbent technology companies over new entrants.
Today, established firms are frequently the ones leading in AI. There are several reasons why. To begin with, AI requires large amounts of data and training AI models is extremely expensive - making it easier for large, scaled companies to develop than for start-ups. Similarly, almost every firm can integrate with the LLMs - there is no natural advantage for start-ups here. Finally, AI favours companies with large existing user bases, since new AI product capabilities will be easier to roll out across well-established products. For investors, that means there are many attractive opportunities to gain exposure to the AI theme via larger, established listed technology companies.
Bumps in the road
While the long-term promise is there, caution is always warranted. Tech consultancy Gartner recently summarised the feeling of a number of commentators (and investors) when it said AI was currently at the “peak of inflated expectations”.
That means investors seeking AI opportunities will need to become more selective. It will become increasingly important to understand the nature of individual products and the competitive positioning of the different companies operating within the industry. We also think that time to revenue is an important issue. This is the kind of work we in the Pictet Digital investment team are focusing on, identifying the companies for which the investment case has firm foundations.
We are clearly at the beginning of another major technology shift, one that will transform most technology (and non-technology) markets over time. It is inspiring to see how quickly companies are adapting to take advantage of AI. We look forward to seeing the break-out products that start to define this new AI era.
John Gladwyn is a senior investment manager within the Thematic Technology team at Pictet Asset Management. To learn more about the team’s capabilities please click here.
