Artificial intelligence (AI) has polarised views, especially after the launch of Chinese chatbot DeepSeek in January, forcing fund managers to reconsider their positions in the tech sector.
Some have jumped fully on board and think AI will be the greatest money-making opportunity of the near future, while others are more sceptical and aren’t prepared to take on the risks that come with mega-cap tech stocks.
Jasmine Yeo, manager of the Ruffer Investment Company, is part of the latter cohort (in line with the more defensive stance traditionally taken by the fund management house) and said that AI is a promise, but not yet a reality. Stephen Yiu, manager of the high-growth and tech-heavy Blue Whale Growth fund, couldn’t disagree more.
Below, they share their take on the most controversial topic in financial markets today.
The bear case
“The promise of AI is the fairy dust encouraging investors to engage in magical thinking”, Yeo said, referring to the way it was able to attract investors and drive momentum in the past couple of years, keeping the global economy afloat despite weak fundamentals.
She didn’t negate AI’s “transformational potential” for productivity or the “tantalising” opportunities from a corporate perspective to expand margins and save on labour costs.
“However, markets have a wonderful way of bringing the hopes of the future into the prices of the present. Just like internet-related benefits pre-2000, [the fruits of this new technology] will not arrive quickly enough to support current enthusiasm.”
This is a familiar argument for fund managers, who have often drawn parallels between today’s situation and the dot-com bubble of the early 2000s. In conversation with Trustnet at the end of last year, Julian Bishop, co-manager of the Brunner investment trust, said that while Nvidia is “incredibly profitable” and far from being a “dot-com bubble-type, nonsense stock”, there is no way of telling whether it will end up being the next Cisco – a company that played a fundamental role in building out the internet, but ended up fading to nothing.
Yeo quoted recent research from Goldman Sachs, which showed that only 5.9% of US companies are using AI at present, up from just 4% a year ago.
“Cumulatively, AI is not expected to have a noticeable aggregate impact on the economy until 2028 at the earliest. In today’s myopic markets, that is a lifetime away. Also, it is easy to forget that much of what AI adds will be lost on a net basis. If AI does something better, that will cause displacement, disruption and job losses,” she said.
“Despite all the society-changing innovations of the past two decades – PCs, the internet, mobile phones, social media – real GDP growth has averaged around 2% annually, which is significantly lower than in any of the five decades before that. The lesson from history is that technological advances have provided durable benefits to consumers, not durable periods of extreme profitability.”
The bull case
On the opposite side of the spectrum, Yiu said most people have yet to grasp the full potential of AI, starting with all the fund managers who haven't invested in Nvidia.
“You can call it luck, but we have made over $100m in our investment in Nvidia in the past two years,” he said. “We have gone through the full journey with Nvidia until today and because of that, we have a unique perspective that other managers don’t have.”
Yiu strongly opposed the concept of AI being a bubble. The first, considerable difference between today and the dot-com euphoria is that today, everything is done in the digital world, throwing fewer hurdles in the way of AI companies, he said.
“If you want to start another delivery or a smartphone company like Amazon and Apple, it's going to be very expensive in terms of logistics. This was also the case in the tech bubble, when companies needed to tackle several frictional forces before they could deliver their end products,” he explained.
“In the context of AI, there's almost zero friction. All the data you need is already available in the cloud, where us, the users, are storing it. The only hurdle is the money.”
Money – or rather, revenue – was his next point. Until 2022, Nvidia’s revenue was about $30bn. Today (only three years later), that number is more than $200bn. This growth is equivalent to the UK’s entire NHS budget, Yiu noted.
“That money is coming from the biggest companies in the world, which have decided to spend $300bn on AI this year. Within that, $170bn is going to Nvidia,” he said.
Finally, Yiu pushed back on valuation concerns, arguing that Nvidia isn’t expensive.
The biggest company during the tech bubble, Cisco, was trading on 130x earnings in March 2000. In comparison, Nvidia is trading at 25x today.
“Microsoft, MasterCard, Amazon and Apple are trading at 30x earnings. The US stock market is trading just about 20x earnings. [So] 25x to me is within a reasonable range. When people say that today’s valuations remind them of the tech bubble and Nvidia of Cisco, I'm not sure what that their context is,” he concluded.