AI spending continues to reshape markets, but after several years of extraordinary growth, are the most obvious opportunities becoming harder to find? FundCalibre discusses signs of bubble-like behaviour, with Mikhail Zverec and Graeme Bencke, co-managers of the WS Amati Global Innovation fund.
In this latest FundClaibre podcast episode, the team elaborate on the slowing growth in AI capital expenditure and why the next phase could favour less obvious beneficiaries.
The interview explores physical AI, robotics, industrial automation and the specialist companies providing the infrastructure, sensors and software behind them.
Also examined – why parts of the software market may have been written off too quickly, before moving beyond AI to uncover innovation across drug discovery, laboratory automation, radiopharmaceuticals, defence, drones, cyber and space.
Why you should listen to the interview: If you’re wondering whether the AI boom still has room to run, this interview offers a more nuanced perspective.
It looks beyond the biggest names to explore where innovation could create opportunities next, from the infrastructure behind physical AI to overlooked software businesses, healthcare breakthroughs and specialist areas of defence.
This interview was recorded on 16 September 2026. Please note, answers are edited and condensed for clarity. To gain a fuller understanding and clearer context, please listen to the full interview.
Interview highlights:
“It does definitely seem like we’re in a bit of a bubble”
“It does definitely seem like we’re in a bit of a bubble. There are certain behaviours that are definitely reminiscent of that sort of typical bubble stage of the investment cycle. And Mikhail and I have lived through a couple of these before.
“If you look at AI CapEx as a percentage of GDP, it is pretty comparable to kind of the dot-com period or the telecom bubble at the time. And the trends we’re seeing in circular financing and the kind of high retail participation across the market in AI-related stocks, all these things kind of lead you to think that we’re getting towards that point of bubble territory.
“There’s a lot of AI plays in everyone’s portfolios. From our perspective, we consider ourselves to be kind of pragmatic optimists, but we do feel that it’s time to have a bit of extra care in this space.
“So we focus on companies that are likely to see continued growth, even if the spending by the frontiers does begin to slow from here, or AI capability doesn’t improve. So we’re not betting on things continuing to get better. We think of these as being somewhat asymmetric bets.
“These are areas like memory. I mean, memory will continue to be in high demand even if the capabilities don’t improve, just because there’s going to be more and more use of AI across data networks and companies just using AI more and more in their day-to-day business. So memory will grow regardless.”
The less obvious beneficiaries of physical AI
“We go wherever innovation takes us. The way we think about this is, when we find an area of innovation frontier, and let’s pick physical AI as an example, it’s kind of a collection of several things in there.
“We see this as a sort of real, very interesting technological change which touches very large markets. It is happening, industry is adopting it. So we want to investigate who are the players in that space? What is the cluster of companies that stands to benefit from that?
“And we have this framework of pioneers, enablers and adopters. The leading-edge inventors that come up with the kind of frontier technology that makes it happen, the picks-and-shovel suppliers, the enablers, and the lateral beneficiaries, the adopters.
“And they can be, you know, anything. We owned NVIDIA in our time, we owned SK Hynix, we still own Samsung, but we also own companies which had kind of mid-to-high single-digit hundreds of millions of market capitalisation.
“So right down the spectrum, wherever we see the best business. And we’re looking for real businesses, profitable, capital generative, but also kind of the best exposure at the best price.
“To pick physical AI as an example, we did indeed find a mid-cap company, a company called Belden, which we think is a pretty undiscovered but potentially crucial fabric that kind of underpins physical AI.
“So the way we think about it is, just like AI in data centres needed networks to make it work and people investing in networking equipment players like Arista Networks, which we have done, or Lomentum, or connectors like Amphenol, has been a very lucrative way to benefit from the data-centre AI growth.
“We think the same playbook will be repeated in physical AI, except the industrial networks are very complex beasts. They are, you know, pretty exotic specialist protocols. They’re not your usual kind of office Ethernet. They have completely different tolerances in terms of ability to cope with harsh environments, latency, error correction. It’s just, you know, those are very mission-critical networks.”
Innovation beyond AI
“There’s more to innovation than AI. And this is how we run our portfolio. We benefited from AI. It contributed very strongly to the fund’s performance, but it’s never been more than kind of 15–20% of our exposure, all things considered, because there’s just so much more interesting stuff going on in the world which arguably the market is paying less attention to.
“Healthcare is an interesting one. Some of them are AI-adjacent because one of the things that AI is doing is accelerating the cadence of, let’s call it, drug discovery.
“The initial glimpse of the opportunity – this molecule might do that good thing in a human body – which once relied purely on human ingenuity can now be accelerated or simplified using AI. And so the number of plausible candidates for new medicines is exploding. We’re hearing that from the industry.
“But if you imagine the framework for drug discovery, yes, you come up with an idea first, then you test it maybe in a digital model to make sure you haven’t missed some obvious pitfalls.
“But then eventually you have to test it in what’s called a wet lab. You need to put it in a Petri dish, see if it actually does something to the cell that you think it does.
“And so we see this kind of wet lab in the loop, in vitro validation, as a really interesting stage. And this avalanche of new ideas is coming towards that part of the chain of drug discovery.
“Both the capacity of wet-lab drug discovery research, the number of tools that do this job, but also the automation that enables this much larger number of candidates to be explored efficiently, will increase.
“So we have quite a substantial position in life sciences tools generally, in anticipation of that growth. But we also have a Swiss company in our portfolio that is the global leader in laboratory automation, effectively robotics for labs.”
Conclusion: AI may dominate the headlines, but innovation is happening far beyond the biggest technology companies.
As the investment cycle matures, identifying the less obvious beneficiaries could become increasingly important.
Past performance is not a reliable guide to future returns. You may not get back the amount originally invested, and tax rules can change over time. The writer’s views are their own and do not constitute financial advice.
This information should not be relied upon by retail clients or investment professionals. Reference to any particular investment does not constitute a recommendation to buy or sell the investment.
Main image: robotics, lab, louis-reed-wSTCaQpiLtc-unsplash
