Look beyond market darlings for AI winners

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AI has easily been the hottest topic in investing this year. While IML Portfolio Manager Daniel Moore is excited about AI’s potential, he sounds a reminder that investing in popular themes is “fraught with danger”. Instead of buying AI-themed market darlings which are now trading at heady valuations, he suggests long-term investors should look to other companies which are investing heavily in AI, and are likely to be beneficiaries of it, but haven’t yet seen their share prices appreciate significantly.

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Lightly edited transcript

Louise Watson: Hello and welcome to Navigating the Noise, a podcast by Natixis Investment Managers Australia, where we bring you insights from our global collective of experts to help you make better investment decisions.

I’m Louise Watson, Head of Country for Natixis Investment Managers in Australia and New Zealand. And today I’m joined by Daniel Moore, portfolio manager from IML’s large cap team to talk about investing in AI.

Daniel, AI has been the hottest topic in investing in 2024, without a doubt. We’ve seen AI related stocks explode in value this year and drive many global markets to all-time highs. This time last year, most people hadn’t even heard of Nvidia, and now it’s a household name. While the Australian stock market, where IML invests, hasn’t seen the same AI boost as US markets, it’s also received an AI boost this year though. Dan, how does IML view AI and investing in AI?

Daniel Moore: Thanks, Louise. It’s obviously great to be here. We’re really excited about the impact AI is going to have on our lives. It’s going to revolutionise how businesses operate, so we’re bullish from that perspective AI. However, from an investing perspective, I think we are definitely treading a little bit more cautiously. And the reason is that there’s sort of many risks, I guess, and really the risks permeate from the fact AI, as you mentioned, is a really popular theme.

And we know from history in the past, investing in popular themes is fraught with danger. And there’s two main reasons. One is, by definition, because it’s popular, lots of people are investing in the space and valuations as you mentioned are at nosebleed levels. So you’re paying very elevated prices.

And the second reason is, because it’s popular, it attracts lots of competition, lots of new entrants, which is not always conducive for good outlook for company profits. And we’ve seen this many times in the past, whether it was the internet boom, whether it was buy now, pay later. Very similar ideas, very high valuations, lots of new competition, and even lithium more recently. Again, it’ was another popular theme, which has come a bit unstuck from an investment perspective.

Louise: The dot-com boom bust happened in the early days of IML and in some ways was the making of IML, as you avoided the eye-watering valuations of tech stocks and invested in quality companies, quality companies which have earnings, which then boomed as the tech stocks plummeted. Do you see parallels between that era and now with AI?

Dan: Yeah, I think there’s enormous parallels in that, the internet changed our lives in a massive way, just like probably I think AI will. So lots of similarities. Also with the internet, there were some really big winners as well, whether it was Amazon or Meta, Google, some huge winners. However, there was thousands of failures, and that made the investing environment particularly in the boom, really tricky. I think the average investor investing in internet stocks did very poorly.

And to be fair to people, picking winners was really difficult, because if you think about those winners, Amazon, Meta and Google, they weren’t the big companies at the time as well. Because, if you go back in the 2000’s, if you think about search, the biggest company in 2000 wasn’t Google in search, it was Yahoo. And we know Yahoo today’s almost, it’s insignificant. And if we go to social media, Meta wasn’t the first social media company. The first social media company with real big scale was MySpace. And obviously, we know that went through its demise. So picking winners was really difficult and we see a lot of those risks around the AI environment today, as well.

Louise: Yeah, lots of .com names in the graveyard of investing over time and when we think about winners and losers in the space, I’d like to refer to a really well used quote within our business by one of the most well-known investors at Loomis Sayles in global equity, Aziz Hamzaogullari, the lead portfolio manager there, he says that he thinks people will underestimate the impact of AI and overestimate the number of winners in AI. Do you think that’s true? And if it’s true, what can investors learn from this?

Dan: Yeah, I couldn’t agree more. AI will impact our lives a massive way, just like the internet. I was on the train this morning and it’s a sad reality with smartphones and everyone connected to the internet, literally everybody’s head is down looking at their phones on the train, and you couldn’t imagine that back in 2000 or ’98. That’s the world we live in today. And I think AI will have a huge impact on all of us.

But I suspect, and our research shows, that there won’t be a huge number of winners. The difference with AI compared to the internet is, it looks like the larger players are in a much better position, whereas the internet, we saw a lot of startups like Amazon, and Meta, and Google eventually become the winners. With AI, what’s sort of becoming more obvious is what really matters is scale.

First of all, you need the data. To create great AI software products or decision-making tools you need lots of data. And first of all, the larger companies that have been around a long time have the data. Second of all, and we’ve just learned this recently, you need access to the data centres. And the data centres, which house all the computing power to run these models, there’s not enough of them, and there’s lots of restrictions on the capacity of growth of data centres. In America, for example, they’re running out of power generation in some states to run these data centres. So, getting access to these data centres is really tricky.

And if you’re a data centre owner, you’re going to preference the large players with lots of profits over the startup AI companies. So, the startup AI companies are struggling to get access to data centres, the Nvidia computer chips everyone wants. Again, the large players are getting the lion’s share of those. And there’s restrictions, as I mentioned, on power generation and grids.

The large companies, believe it or not, Microsoft, Amazon, they’re investing in power generation themselves, even nuclear power generation; these companies have separate arms, so they’re protected long term, which makes it hard for the smaller players. So, I agree with him completely. I think there’ll be few winners.

Louise: So, with that backdrop and those challenges in mind, we’ve seen the AI related technology stocks in the US booming. They’ve had a great run. And we’ve seen some parallels with the Australian stock market. Which Aussie stocks have really benefited from the AI theme and which have been left behind?

Dan: In Australia, there’s definitely less direct beneficiaries, or direct AI comps, I guess. So the stocks that have done really well have been Next DC which is one of the largest data centre owners in the country, Goodman Group, which is an industrial property owner. And potentially some of the industrial land they use can be used for data centres, but their share price has gone up 60% in six months, and they don’t even operate data centres. So that’s a little bit strange to us. And then there’s other companies like Wisetech in the tech space, which are a software company mainly around logistics, where they think they could be a good beneficiary of AI improving logistics through their software.

And if we look at the flip side, what we’re seeing in the market is people selling stocks to fund those purchases. So to fund the exciting AI purchases they’re selling, the less exciting companies that are not obvious AI beneficiaries, typically the more defensive companies. So companies like Telstra, or the Lottery Corp, or CSL or ironically Sonic; those companies have less excitement about them around AI and people have been selling those to fund those purchases. So yeah, they’ve definitely been left behind.
And this was exactly like the internet boom. In the internet boom we saw people sell the more, boring industrial companies to fund the internet purchases. And funnily enough, the best investments you can make in the internet boom were the non-internet companies that were very cheap, because everyone sort of left them behind, forgot about them while they were chasing all the internet stocks.

Louise: That’s a really interesting point. And so given valuations for names like NextDC, and Goodman are looking really full for investors wanting to invest in the AI thematic, but perhaps avoid some of the more obvious candidates which we’ve talked about. Do you have any advice for where people should look or companies you think that we should consider?

Dan: Look, generally we love investing in great businesses that are out of favor. So in this situation, we like to invest in companies that will benefit from AI but aren’t direct AI companies. So traditional businesses that are heavily investing in AI, out investing their competitors, where we can see that investment improving their earnings growth outlook over time.

The best example I could give is Sonic Healthcare. And Sonic Healthcare is a global leader in pathology. They’re also very big in radiology, in Australia as well. They already today have AI software products. So if you go for a chest x-ray in Australia, The software program which will analyse whether you have lung cancer or not, will be an AI software program, which Sonic owns a share in.

They’re very close to releasing a brain scan product as well. So the AI software just looks at the image and with better accuracy than a human can tell whether you have cancer or not. And Sonic’s also working on histopathology, so think skin cancers. Any specimen that can be looked at under a microscope, they’re working on AI software products that automate that process, which you can imagine would deliver massive efficiencies for themselves as a business. And the plan is they’ll sell that software products to their competitors globally as well. So pretty exciting, but , the multiples are incredibly reasonable. We’re talking 16 times earnings.

Louise: These are really great adjacency businesses that are essentially using AI to help improve their operating model. And that’s a great example of how business is using AI to improve efficiency. So that’s really where our investors should be looking in order to find well-priced companies that are taking advantage of the theme.

Dan: And there’s plenty of companies that are doing that, I could keep going on. Whether it’s Orica and explosives, they’re using AI to improve their blast designs, and they’ve got thousands and thousands of blasts they’ve done over decades. They’ve got the data on to help them improve that. Telstra is looking at splicing their 5G spectrum to create individualised mobile internet coverage. The list is endless, so there’s plenty of opportunities, but you’ve just got to be careful you’re not paying the very high prices.

Louise: Yeah. So rich pickings, but it doesn’t come without its challenges, which is probably a good place to turn our discussion.

As well as some of the benefits, there’s also some big risks for society [in AI], and I did hear a great example the other day from Holly Ransom, and she asked one of the AI models who had scored the most goals in international football. And the model answered, “Cristiano Ronaldo,” who at the time of the campaign had netted 118 goals. But the correct answer is actually Christine Sinclair, a Canadian soccer player who at the time had scored 190 international goals, so obviously way more than Ronaldo.

And while this is surprising, the most shocking bit was that even when she corrected the AI, and then repeated the question, it still answered Ronaldo. And we’ve seen many such examples of bias from AI and also wrong answers that it’s giving. Is this something you’re bearing in mind as you invest? And if you are using AI in the IML investment team, how are you making sure that AI biases don’t creep in and affect your decisions?

Dan: It’s a really good point. And we’ve come across this ourselves actually. So we’ve definitely dabbled in using Chat GPT and things for our research process. It’s not there yet. We’ve found multiple errors, pretty obvious basic ones, so we’re not using it extensively.

I think it’s definitely not a source of gospel truth, as you just mentioned a really good example. For the moment, for us, how we use AI is not really on the research side. We use it more for summarising lots of text. It’s great with language, really good. You can copy and paste a 60-page speech by an RBA governor and ask it to summarise it for you in two pages, and it’s really good at doing stuff like that. Research topics where the truth is very important as it is in investing. We’re not really there yet, in using AI tools for picking stocks, maybe in the future, but not right now.

Louise: Well, thank you Daniel for navigating the noise in AI with me today and giving us some insight [into] how IML views this transformational new technology. And thank you as well to everyone for listening in. Please tune back in to hear more podcasts from our global collective of experts to help you make better investment decisions.

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