Polar Capital Technology: the AI stocks I’m excited about in cognitive era

Ben Rogoff, lead fund manager on the Polar Capital Technology Ord (LSE:PCT) Investment Trust, explains what makes his fund stand out in a period experiencing a giant technological leap forward.

He also discusses the speed of change in AI, memory bottlenecks, the trust’s exposure to semiconductor shares, and his views on individual Magnificent Seven companies.

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Dave Baxter, senior fund content specialist at interactive investor: Hello and a very warm welcome back to our Insider Interviews series. I’m Dave Baxter here at ii, and today I’m joined by Ben Rogoff, lead fund manager on the Polar Capital Technology Investment Trust. Ben, many thanks for joining today. 

Ben Rogoff, lead fund manager on the Polar Capital Technology Investment Trust: Thank you.

Dave Baxter: So, there are many ways that investors can access the technology theme, different stocks, different funds. What makes your fund stand out? How are you different? 

Ben Rogoff: Well, it’s been around for a long time and it’s very carefully managed. It’s a flagship fund or company that we look after at Polar Capital, and I’ve been managing it now for what feels like a very long time, but 20-plus years. 

What distinguishes it? I guess, in the end, beauty is in the eye of the beholder, but what we love about it and how we’ve positioned it is as a very broad-church product.It’s a technology fund that’s really focused on all the themes that happen within the technology sector, and it has done that for a very long time. 

There are always very fascinating sub things happening at any given moment in the tech sector, let’s say robotics, or earlier it might have been the cloud or software as a service, and we’ve tried to capture those smaller themes within a broad-church technology product. That’s certainly been the history of the trust since I’ve been managing it. 

Having said that, what’s unique about it today is actually quite different in that we made a very bold or big decision in May 2023 to pivot very hard into the artificial intelligence (AI) theme. We were extremely excited about the AI story. We were waiting for that moment where it would really...be adopted or really happen. We launched a fund outside the trust to focus on AI earlier. 

So, ChatGPT arrives and we decided at that point that this was one of those rare moments of general purpose technology that was about to take off. We actually collapsed the way that we’d been thinking about the trust in six to eight core themes and focused very heavily on the AI story, [and] so far, so good, we’ve really seen very rapid adoption of the AI story. 

So, right now, it’s an actively managed trust, with 90 stocks or thereabouts, so it’s well diversified, but it’s very focused on the AI theme and trying very hard to avoid the other side of the trade, the disrupted companies that we believe could fall into the shadows, if you like, as AI continues to evolve. 

Dave Baxter: In the last few years, you have sought to quantify how much of the fund is focused on AI. Where does that figure stand now? And which sectors do you view as beneficiaries and victims of AI advances?

Ben Rogoff: The numbers are a moveable feast. I would say the vast majority of the trust is directly exposed to the continued progress of the AI story. When I say progress, I mean models continuing to improve, capital spending, capex, continuing to be revised higher. I mean we’re at $1 trillion or thereabouts now from zero four years ago, and continued adoption of the technology in various different forms. So, the vast majority. It could be two-thirds, it could be 80%, depending on how the portfolio is positioned. 

On the other side of that, I think it’s worth just pointing out that, yes, the disruption story has also continued to evolve, because if you go back just three years, the technology, the transformer model that underpins the architectural underpinning of large language models, the transformer, was producing a sort of probabilistic and error-laden output. So at that point, it was very easy to dismiss it as interesting, but ultimately not going to disrupt anybody. All technologies begin as complements and end as substitutes, or at least the important ones. And we believed, and continue to believe, that that’s still true. 

As the technology’s got better, as the output’s got better, as the models have got bigger, more capable, and when you see the error rates of these models collapsing, so the scope of disruption has increased. 

I think it’s a really important point to make, if I may, which is that like this idea that you can co-exist for a while means that you could be, as an investor, lulled into thinking that a company is not on the wrong side of something because at a lower level of capability, it’s been fine. But as the AI models have continued to move - and now we are at points where most of the frontier models are already well beyond human capability, which means that, in our opinion, what started with weaker application software companies that have effectively been sold-for just by using a large language model - it has crept into other parts of the market, like information services businesses that we’ve been actively avoiding now for a while. Companies in the software space have also become embroiled in a debate, at least, about what their long-term value proposition is because, in the end, a large language model is already looking capable of doing a lot of what software does today. 

Then, longer term, you have to start thinking about, and this is where we believe the current debate is now moving, what do businesses look like in a world where the incremental interaction with a business isn’t by a human, but by a machine, by an agent?

And in that world, what does advertising mean in that world? Who are you advertising to? For example, if you’re aggregating traffic because you’re in the hotel business, and you’ve been sitting between consumers that have been overwhelmed with choice, and hotel companies are looking for customers or an audience. Those businesses have been fabulous in a world where humans have been ultimately booking hotels. But what if the incremental hotel booking is a machine that doesn’t respond to advertising and isn’t attention-scarce? 

So, sorry for a long-winded answer, but I think it’s really important to understand that this is a moveable feast, that as model capability continues to improve, so we expect the shadow formed by AI to continue to broaden. I think you have to be absolutely alive to that risk within a technology portfolio, but also in a broader equity investment portfolio. 

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Dave Baxter: So, on the software front, you believe those fears are founded? 

Ben Rogoff: Yeah, we’re actively avoiding the software space. That’s not to say that there aren’t pockets of interest. Of course, ever more capable AI models in the wrong hands can be ever more capable sources of cyber attacks, for example. So, we have exposure in the portfolio to the cyber theme, as you would imagine. 

Longer term, there are some question marks even there. If the large language models are so capable, why couldn’t they at some point be productised to perhaps compete with some of the cyber companies? But right now, the attack surface and the capabilities in the wrong hands mean that companies will invariably be spending more on cyber going forwards.

The same thing applies to companies like Snowflake Inc Ordinary Shares (NYSE:SNOW), for example. Again, it’s not an individual recommendation of a stock, it is one of our 90 names, but that company seems to be benefiting very well from the idea that companies are needing to get their data in order. And with that data, data plus large language models, [produce] credible outcomes, and so Snowflakes benefits. 

So, there will be pockets in the software space that we’re excited by. Software is ultimately a tool for humans to be more productive, but AI is becoming a substitute for human cognition. I think that’s a big statement to make, but that is how we see it. That’s why we believe this is one of those key moments, really, in life or in history, where non-human scaling takes place. We saw it in agriculture, and we’ve seen it in the Industrial Revolution, and I think we’re seeing it now in this cognitive era. 

Dave Baxter: A big chunk of the fund, around 40% or so, is in semiconductor shares, related companies. That clearly has performed very well in the last year or so. What’s your outlook now? What do you expect to happen? 

Ben Rogoff: There’s lots of risk to the AI story and I think that, if I may, it’s worth just highlighting that a new cycle is always characterised by volatility. 

Just recently we’ve heard about companies at the frontier talking about wanting to slow down potentially the pace of development. Before that, we’ve had plenty of other headwinds to the AI story in the form of scepticism around revenues or what returns people are going to get for this capex. 

So, if you’re involved in the story or if you are as excited as I am about it, you should still be guarded against the prospect of volatility. There’s going to be buffeting. In fact, the summer has been a pretty tricky time for a number of the sectors. The semiconductors are really among some of the heaviest hit. 

The memory stocks that have been a focal point for investors because memory being kind of a commodity product that in the smartphone or in the cloud world, there was plenty of it. So, essentially the industry was a price taker. We’ve moved into a world now where memory, particularly high bandwidth memory, is a critical component in the training or building of compute clusters that train AI models.

Going forward, as we do more stuff with AI, so inference workloads, the memory that your AI agent has of prior information that you’ve shared with it may be stored in something like NAND flash. 

So, the products that were really commodity components in a previous world seem to have taken on a completely different level of importance today. As a result of that, the prices have moved meaningfully higher for those products. The industry is a price giver, not a price taker, and the stocks have responded. Since the summer, a number of those companies, particularly ones in South Korea, where there’s been lots of retail involvement in the stock, have been under quite sustained pressure. 

So, how are we thinking about it now? I think that market investors generally haven’t seen anything like this before.

We were chatting before we started recording just about the idea of historical parallels helping to perhaps illuminate where we are, because it is an unusual moment. I really do believe that. 

If we look at the forward price/earnings (PE) that people are putting on stocks like NVIDIA Corp (NASDAQ:NVDA), let alone companies in the memory area like I’ve referenced, they’re very modest forward PEs. And that speaks to the idea that the market is very sceptical that the growth that we’ve seen so far can persist. There’s a real question mark about the duration of this trade because it’s very unusual for an industry to go from spending nothing to $1 trillion. 

We believe that the cycle will persist and therefore we’ve been holding and adding to some of our semiconductor holdings. 

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Dave Baxter: On the memory topic, you talk about names like SK hynix Inc ADR (NASDAQ:SKHY) and Samsung Electronics Co Ltd DR (LSE:SMSN) so far. There’s been this debate about whether those memory bottlenecks are temporary, because in the past they have tended to be so. Do you not believe that’s the case? 

Ben Rogoff: Well, you know, everything ends. So, bottlenecks are ultimately resolved. I’m a huge believer in that. Capitalism has a phenomenal habit of being able to take advantage of bottlenecks but then ultimately resolve them with very clever solutions. 

If you went back to World War II, I’m sure nobody wanted to, but people ate cakes made of potatoes because eggs were scarce. Right now, it’s tricky to bring power, for example, to data centres. It’s one of the real-world bottlenecks that I think everyone’s very focused on. 

Beyond the semiconductor sector, we’ve got lots of other AI infrastructure exposure, some of which is exposed to the power trade. What we’ve seen in that world is actually some incredibly innovative solutions that are imperfect, much like a potato cake. So, Elon Musk buying turbines from Caterpillar Inc (NYSE:CAT) in order to power Colossus, his data centre that they’ve built in a record period of time. 

So, right now, the bottleneck in memory, will it ultimately resolve? I imagine it will. But I think normal psychoanalysis says that when stocks look too cheap to be true, when it’s too good to be true, i.e.forward PE is very low, I think, understandably, people have been taught, and rightly so, to fade those stocks, to derate them. And that’s what’s happened. 

Again, we can’t be sure. I think at the margin, we’ve also been reducing our overall exposure to the memory trade, but in favour of other areas. So, for example, as agentic AI takes off, you’ve seen an incredible increase in demand for CPUs, traditional compute, because those agents are making moves like humans make when they call tools, when they complete bookings, when they find you the right flight. That requires a lot more CPU compute power than we’ve seen in the past. 

So, we’re moving around the portfolio to where we see the best bottlenecks. Bottlenecks, ultimately, are an incredible opportunity as an active investor. You have to have fairly loose hands though, these aren’t necessarily stocks that you would want to own for five years, but they can be incredibly good places to be for a short period of time and then you’re, of course, always on the lookout for the next bottleneck. 

Dave Baxter: What have you been up to in the fund so far in 2026? 

Ben Rogoff: Well, we’ve been busy, and we’ve been busy for a while. Our investment approach is what we call ‘active-active’, which may sound terribly low quality. But what that means is because we compete with, obviously, other active managers, and we compete with passive portfolios or exchange-traded funds (ETFs), and again, it’s for the customer, for the shareholders, to decide what the best approach is for them, but our investing approach has always been relatively active, because we observed many, many years ago, that in the end, the returns to the tech sector depend very heavily on not missing the big winners. 

I know there are other investment houses out there that have quite rightly also made those claims. We don’t have a concentrated portfolio. The reason that we have had 90 to 100 stocks in the trust is really that tacit acceptance that you’re going to get some wrong, but you can’t miss the big winners. 

We have a team of 12 people, we do 1,000 company meetings a year, we work as hard as just about anybody in the market to try and improve our hit rate, of course we do. But with the best will in the world, things change very rapidly. The way that compute racks are being assembled is changing weekly, monthly, and we are trying to adjust our portfolios. We aren’t hedge funds, these are all fundamentally driven investment decisions, but perhaps where the investment window is shorter than others, and once we see that that company isn’t going to be one of those core drivers of performance, we’ll exit it and try and recycle the capital into another company that might be. 

As a result of that, we’ve very rarely missed the very big winners, and again, past performance is no guide to future performance, but in the portfolios, we’re active. 

I suppose at the margin, we’re looking at the narrative shifts around the Magnificent Seven. As a group, we are less positive on them than we were perhaps, say, 18 months ago. Look at Meta Platforms Inc Class A (NASDAQ:META) very recently, a re-rating process has begun now that the company has delivered a very good model that it’s been able to package as an agent, Muse, and it’s really got traction. 

So, we need to be alive to the bear and the bull case on all the Mag 7, and a lot of the activity in the portfolio is around those big stocks. 

Dave Baxter: Let’s talk more about the Mag 7. Which names there are you bearish on and which names are you more excited about? 

Ben Rogoff: I was about to say it depends on when you’re about to put the video out, but things are changing very fast. Just a few weeks ago, Google [Alphabet Inc Class A (NASDAQ:GOOGL)] was...I should step back from this and say that we’ve owned Meta since IPO, we’ve owned Google since IPO and I bought Apple Inc (NASDAQ:AAPL) for the trust on the 1 May 2003 and I’ve owned ever since. So, please, the comments I’m about to make about which we like and which we don’t like are all really relative to themselves and to each other. We own all the big names. It’s one of the ways that we manage risk.

The industry has been talking much about active share for many, many years and how, I suppose, the higher, the better. From our perspective, we want to have the very best ideas in the trust, but we also want to have the best that the index has to offer. And in our index, the index is full of Nvidia, a great business. The same for all the Metas, the Googles, the Apples. These are dominant, I suppose, natural monopoly companies in huge profit pools. So, we own them all. 

Right now, I would say at the margin, we’ve been adding back to Meta because of the reasons I’ve already mentioned. At the margin, we’re taking money off Google, where you can see the beginnings of a narrative around the advertising industry, or at least the online advertising world, being potentially impacted by agents. We’ve been worried about that for a while and it looks like Muse might...this is the second coming of the agentic story. So, at the margin we’re reducing Google. 

Apple is an interesting one because it’s been meaningfully re-rated. I don’t remember the last time it was quite as expensive as it is, but it’s an incredible business, got a new business leader there. 

Some people like the stock because it stands aside from the AI story. It’s not trying to be a model provider, but at the same time, we’re beginning to sense that, again, I think it’s too early to say, but we might be at least beginning to think about a world post the smartphone where an agentic AI agent could potentially abstract the user from the operating system, which of course in the form of Apple and iOS has been really the crown jewel of the Apple business. So, at the margin we’ve been reducing.

Dave Baxter: The fund is very focused on large-cap shares, it is almost entirely invested in large caps, which is a contrast to some of the competition, some of them focus on mid-caps, and look to find some of those unknown success stories. What would tempt you to focus more on the likes of mid-caps? 

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Ben Rogoff: Honestly, we’re relatively agnostic to market cap. I know it doesn’t look that way. But, again, like we’ve said already, we’re certainly aware of the index. The index has been a phenomenal place to have been. Again, past performance is no guide to future performance, but thank goodness that we’ve built portfolios this way. 

Because when you think about how large the Apples, Googles, Metas, Microsoft Corp (NASDAQ:MSFT)s and Nvidias have become, it’s very hard. There’s an incredible crowding out that has occurred in the market. I know that if you’ve not been involved in the Mag 7 stocks, it’s been a deeply frustrating time. But this isn’t a business about fairness. This is about where profits are ultimately created and retained, and those companies, for lots of different reasons, have ended up dominating their respective profit boards. 

Now, the good news about that is that they’re non-fungible assets, we want them in the portfolio. But the bad news about that is that most of those profit pools, in fact, all of them bar Nvidia, were created before AI. So, if you are a market historian or if you’re as passionate about tech investing as our team is, you’ll know that at this point in a cycle, those profit pools are at risk in a way that they weren’t before. 

That doesn’t mean that they are going to ultimately be competed away or be redistributed, it just means that there’s risk now that didn’t exist in a pre-AI world to those market dominants. So, are we looking actively at alternative places? We are. And where we can find ideas is really where the money in the portfolio is allocated. 

So, we have an overweight position in Taiwan, in Japan, until recently in Korea. We will go where we find the ideas. And if we find the most compelling ideas, let’s say, in the semiconductor supply chain in Taiwan, that’s where we’ll invest. And if they’re mid-cap names, so be it. The beauty of having a closed-end fund is that in the end, we don’t have some of the same liquidity concerns even though the portfolio is incredibly liquid. 

So, the punch line is, we go to where the best ideas are, we’ll go to the geographies where we can best express our excitement and our focus in this AI cycle. What we have done already in the portfolio is de-emphasise software and, at the margin, reducing our overall internet exposure does put a downward pressure on our US exposure. These are industries, of course, that have been dominated by US companies. 

Dave Baxter: Ben, many thanks for your time.

Ben Rogoff: Thanks for having me.

Dave Baxter: And thank you for watching. I hope you found it useful and interesting. As always, let us know what you think in the comments. And if you’re a fan, hit the like button and the subscribe button too. Thanks and take care.