216. Investing in innovations that allow us to meet unmet medical needs
In this interview, Simon Clements, co-manager of the Liontrust Sustainable Future Global Growth and...
Sanlam Artificial Intelligence fund ‘eats its own cooking’ using an artificial intelligence (AI) system to help find companies whose business models are aligned to benefit from this growing theme. The fund is unconstrained in that it can invest in businesses of almost any size and in more than just technology stalwarts; around half of the portfolio can be found in the healthcare and consume and industrial-related sectors.
22 February 2022 (pre-recorded 21 February 2022)
Below is a transcript of the episode, modified for your reading pleasure. Please check the corresponding audio before quoting in print, as it may contain small errors. Please remember we’ve been discussing individual companies to bring investing to life for you. It’s not a recommendation to buy or sell. The fund may or may not still hold these companies at your time of listening. For more information on the people and ideas in the episode, see the links at the bottom of the post.
Staci West (SW): Welcome back to the Investing on the go podcast. In this episode we’re delving deeper into the investment opportunities and risks of artificial intelligence. There are four main types of artificial intelligence: reactive machines, limited memory, theory of mind and self-awareness. But for the purposes of this podcast we’ll be discussing the topic as it aligns with the Sanlam Artificial Intelligence fund and we’ll start with manager Chris Ford giving us his definition of artificial intelligence.
Ryan Lightfoot-Aminoff (RLA): I’m Ryan Lightfoot-Aminoff and today I’m joined by Chris Ford, the Elite Rated manager of the Sanlam Artificial Intelligence fund. Chris, thank you very much for your time today.
Chris Ford (CF): It’s a pleasure Ryan, thanks for having me.
RLA: Now let’s start from sort of a broad level, what is artificial intelligence and why does the world need it?
CF: Well, that’s the most difficult question you’ll ask today. So artificial intelligence, we say, looks to synthesise, automate and optimise the process of converting information into useful and actionable knowledge. And that’s a definition that we’ve used for the last six years. And it’s one that builds on the work of a gentleman called Demis Hassabis, who’s an extraordinary man, who’s done brilliant things with AI, through his leadership of a company called DeepMind, that many of listeners here will have come across.
And it’s a slightly different nuanced definition of AI when compared to others. It’s not a definition of AI that looks to define AI in terms of human intelligence, because of course there are many different types of intelligence and we think it’s important to reflect that. There are many solutions that are being delivered into the world today, which whilst not necessarily capable of a human level of cognation are still providing, you know, great insights and practical help to those who are using artificial intelligence systems that don’t necessarily approximate human levels of intelligence.
But what we also like about our definition is it’s an intensely practical definition of AI. You know, what’s really, what really matters is this ability to take that data, take that information and turn it into something that’s useful and actionable. And that’s what really is of course attractive to corporate buyers and consumers at the moment who are able to engage with artificial intelligence systems to deliver something that is beneficial to them in ways that they never previously could.
RLA: And in the fund itself, you don’t invest just in the, sort of the pure artificial AI companies themselves, but also those embracing AI in their existing businesses. Can you just maybe explain why and bring that to colour with sort of a few examples?
CF: Yeah, sure. So there are many companies that are developing artificially intelligent systems, developing the tools, if you like, and selling to third parties, but even more there are companies that are utilising artificial intelligence systems to revolutionise their own business processes internally and really kind of drive and deliver change within those organisations. And really that’s what we’re looking to invest behind.
But there are also those companies that are looking to do both of those things. And an example of that would be a United Healthcare, for example, in the United States, which very early understood the benefits that artificial intelligence systems could deliver into its business. And whilst using some of the paid solutions they also invested very heavily in their own data science capabilities to deliver what they regard to be a significant competitive advantage relative to their peers. So it’s important for companies like that, for companies like John Deere in the machinery space, for example, to invest in their own solutions because they’re recognising it very significantly enhances their competitive moat around their businesses.
For other companies that maybe don’t necessarily have as deep pockets or the innate capabilities from a skills perspective inside their organisations, the opportunity to really invest in their own AI is going to be somewhat limited, but that doesn’t mean that they can’t engage with the process. And so for those companies, we find examples that are buying artificial intelligence systems off the shelf, if you like, and doing a bit of configuration and still managing to deliver very significant benefit to their organisations. And so it’s important to us, to focus yes on the presence of AI, but it’s as important for us to understand how the AI is being delivered and the benefits that its delivering to a business model because of course what we’re ultimately concerned about is the extent to which there is a significant cash generative impact as a result of the better presence of an artificial in intelligence system, within a business.
RLA: And when you launched the fund in 2016 you had about sort of 10% of your investment universe in the Asia Pacific region. You recently said this is grown to nearly 50%, so nearly half of your investment universe, what’s been going on? What’s the reason behind this area’s been growing so significantly? I imagine it’s causing you a few sort of early mornings as well.
CF: So we have committed quite a lot of incremental resource to the Asia Pacific region to reflect that change in the shape of our opportunity set. And what we’re seeing in Asia is an extraordinary converging of opportunity from an artificially intelligent perspective. And that AI is bringing with it disruption at a rate that we simply haven’t seen previously in the Western hemisphere.
The rate of industrial disruption that we’re seeing in the Greater China space, but even more broadly across Asia, is truly extraordinary. And it makes even what goes on on the west coast of the United States seem positively tame by comparison. I think it is poorly understood by investors and we have some frameworks that help us to understand that rate of change and to model it from business perspective. But, you know, we’re seeing companies appear in timeframes and scale to significant size in timeframes that simply would be inconceivable in the Western universe.
And it’s partly a reflection of a younger workforce that is typically more digitally native in the Asian Pacific region than it is in the Western world. It’s a reflection of a corporate world, which in some cases is less aged. So you have less baggage to bring with it. And of course, you know, stepping aside from AI specifically, you know, AI brings with it the requirement to embrace change and embracing change is something which is very difficult for many corporations to undertake. And you know, the more ‘change-minded’ an organisation is, the more likely they are to successfully embed within their business processes, artificial intelligence systems. And so if we can find those companies which have less of that cultural baggage, than it’s easier for them to engage with these systems. And we are finding more of those companies in Asia.
But I think just culture more broadly is redder in tooth and claw in parts of the Asian market than it is in the Western world. You know, in Silicon valley, there is a kind of innate respect for innovation and a sense by which the innovator’s best interests should be respected and protected. And to some extent those things are less prevalent – those attitudes are less prevalent in Asia, for good and for ill. You know, we are aware in the Western world of the kind of pillaging of intellectual property, which is thought to be rife in the Asian world, particularly in the Greater China space. And that may or may not be true, but it’s certainly the case that the fast followers follow more rapidly in the Asian context than they do in the Western hemisphere. And that brings with it a requirement on the part of the innovators to move ahead themselves that much more rapidly. So we just see the whole [inaudible] moving much more quickly to the extent that you’re right to highlight our investable universe having grown significantly. But we have also seen, you know, right the way across the economies significantly higher levels of penetration of artificial intelligence systems into corporate entities in the Asia Pacific region than we have in the rest of the world.
RLA: And are there any signs of this happening or starting to change closer to home? Any sort of green shoots? We can’t make our population any younger, so that’s one of the advances gone, but are we taking sort of any theirs cues from the culture change? I know in the UK we’ve seen some commentary on the political side about getting more tech companies onto the market, supporting IPOs in that way, is this going to change the outlook for the West at all?
CF: I think AI changes the outlook for everybody, frankly. I think, to think differently, I think is to have ones head in the sand, that’s not to say you should necessarily agree with my perspective entirely, but it is to suggest that not to have a view on AI is really, I think unacceptable now it’s, you know, AI has come flying out of Pandora’s box, the lid having been lifted over the course of the last 10 years. And it isn’t going back inside.
The UK, it, you know, has a wonderful opportunity in AI. It is in many ways, a market leader in AI from an intellectual property perspective, the R&D efforts in the UK are second to none. The university output from the perspective of AI engineering talent is extraordinarily high here in the UK, and Cambridge in particular, is a real global centre for AI innovation, with many, many companies having, you know global AI innovation centres based in the Cambridge region. And also of course in London with DeepMind being the bohemoth that is one of the twin pillars of Google’s AI.
So there are signs of things going on close to home. The UK market has been a disgrace really in respect of its willingness to fund AI companies and tech more broadly for at least two or three decades now, and companies in the growthy end of the market and in the tech end of the market have very rarely if ever enjoyed the kind of support in the UK that they would get in North America and elsewhere.
And I think it’s you know, from a market perspective, it’s difficult for me to recommend that a new company looks to list in London when the opportunity to deliver in New York would be available to them. You see a company like Endava which is a UK IT services company, which has been incredibly successful in what it’s delivered over the course of the last five years or so. And has had its had that success reflected in its multiple for most of that period, you know, and you look at the success that that company has had in the reception that it’s stock has received in North America and compare it to, you know, companies like Blue Prism, like you know, even Ocado here in the UK and it’s been much, much more difficult for those companies to really be as successful as they might have been, have they been listed elsewhere. So I think, you know, we in the City need to look to ourselves really in respect of our willingness to fund innovation and find ways to invest in those companies in a market which is still incredibly focused on jam today and the requirement to provide yields to our pension funds.
RLA: And you alluded to earlier in that question that you think we’re only in the foothills of the AI adoption story, how do you see it developing over time? How far can it go?
CF: That’s a very difficult question to answer because it’s got an awful long way to travel. I think, you know, it’s always been a bit of a mugs game trying to identify an end point for human innovation. Because there’s always something that, you know, we’ll create a hole somewhere or we’ll dream up to take technology to the next level.
Look, we are incredibly early in the journey into the artificially intelligent world and something that we’ve found engaging with AI – we use an artificial intelligent system to help define our investable universe in our investment process – something we’ve found which many other people have found is as you tip toe into the world of artificially intelligent systems, the system might address the particular need that you’ve identified within your business process, but as it addresses that it then opens up myriad other opportunities for inquiry and engagement with the field, subsequently.
And I think that certainly our negating factor for our engagement with AI in our business process is really, you know, our own imagination and creativity in respect of how we think that AI might be able to help us to do things better and more efficiently in the future.
When I look around the economy at the moment, I see so many opportunities for AI, many of which are not yet addressed, you know, we are constantly told that autonomous driving for example is something which is not going to happen for the next, you know, 5, 10, 15 years, depending on who you, who you listen to. We happen to think that it will happen a little bit earlier than I think most people think. But to the extent that is all really remarkably long dated, all of that innovation is still yet to come in that part of the economy, which is very clearly identified as something, not a feature that, you know, it’s debatable whether or not it’s going to happen. It’s just a question of when, not if. And so we’re talking about timeframes and there are many, many other opportunities.
And I think to your point about the aging population, the fact of an aging population is a very powerful backdrop for the for the engagement with artificially intelligence system. We’re seeing in Japan already, you know, a country which is beset with even more demographic headwinds then we face in the UK, we’re finding that the opportunity to develop artificially intelligent systems to address shortfall in the labour market is very, very obvious. And to then provide services that simply would not be provided if human capital were to be relied upon. So for those of us who are concerned out wage inflation, concerned about labour shortages, concerned about, you know, long run inflation on the back of that. The opportunities that are provided by artificially intelligence systems to provide some solutions to those problems are readily apparent.
RLA: And beyond the demographics thing, has the adoption of AI been accelerated by the pandemic at all?
CF: I think it has you know, we’ve certainly thinking about, you know, corporate digitalisation more broadly, it’s widely understood that the pandemic certainly brought forward quite a lot of that activity and numerous research from the CEO of Microsoft quite early in the pandemic that he thought that, you know, the first couple of quarters of the pandemic, we’d seen two years’ worth of digital innovation brought forward into that time period. So we’ve seen a race to adopt these platforms, and I think as a result of companies have been forced to undertake their business differently, some of the sacred cows, some of the kind of laziness, if you like, and unwillingness to engage with change was removed of necessity. And I think that that’s been a very powerful thing and I’m not sure, you know, in the same way that it’s often said that we’re not going to go back to shopping in the same way that we did before pandemic, you know, the transition to eCommerce as a consumer is here to stay. I think in terms of corporate behaviour, corporates have had to think differently about how they do their business and they’ve had to expect different things of themselves with regards to delivering change and the timeframes within which that change needs to be delivered. And I think having seen what they’re capable of, my hope would be that the corporate world would expect more of itself as we go through the next 5, 10 years in respect to engaging with artificially intelligent systems over that period, and that’s certainly what we’re seeing from the companies which we invest today.
RLA: And we have talked a lot about the sort of the positives and the outcomes of it, but what are the risks to the growth in AI? Obviously we’ve all seen the sort of Hollywood movie style things, but is that a realistic risk or is there something else in the market that we need to be conscious of?
CF: I think the risks are apparent. Or some of the risks are apparent. I think there are risks, there will definitely be risks that the kind of unknown unknowns, if you like, that will materialise over the course of the next few years. I think the good news is that there is a conversation going on about many of these risks and how they should be mitigated. And that’s very important. I do think the regulators have been slow to respond to burgeoning of artificially intelligent systems into the economy. I think that candidly, there are as many brilliant examples of AI looking to address a persistent and current inequities in the economy as there are examples of AI that will bring it’s own inequities
An example is a company called Upstart, which provides a lending platform in the US, which is looking to provide credit at affordable rates to parts of the population that are traditionally underserved. And of course, traditionally those populations that are underserved are not only those that earn less money, but partly as a function of that, they tend to be immigrant populations. They tend to be ethnic minority populations. And so the opportunity that AI brings to provide a much more objective assessment of credit worthiness in this environment is very, very important, and has been a long time coming. And hopefully should address some fairly, some very significant inequalities in the system. And I should say in America, that really matters because if you don’t have access to credit, you basically can’t go to school. So it’s not just buying the new big screen tele or the new car, it’s your ability to live the American dream through education. And I think that’s misunderstood. So there, there are some great opportunities of AI doing some, some really interesting things to address problems that humans have failed to solve for themselves for a number of reasons.
The last thing I’ll say here is that there are significantly different approaches to the ethical problems associated with AI. Particularly when that’s mapped out of obstraction and brought into the world of regulation. And the regulatory arbitrage that AI is bringing with it is very significant. And so the means by which AI is being regulated in China, it’s very different to the means by which AI has been regulated in the European Union. The Americans have a third way. And this is really important. You know, I would argue now that actually, if anything, the Chinese have a better and more rigorous and more comprehensive regulatory environment for AI than anywhere else, now, we might not like it because our particular, you know Aristotelian philosophical background might think that it’s something which we don’t like, we don’t like the over the over-weaning access that the Chinese system might bring to personal data, for example.
But you know, when looked at from a Confucian background, actually, maybe that’s less outlandish than we than we might think. So I think, you know, from a Western perspective, one has to be a little bit careful that slinging too much mud in the direction of others who would look to regulate their industries differently, particularly in a world where we haven’t got our stuff together yet, you know, at least they are regulating and anybody who’s been invested in Alibaba or Pinduoduo or Bidu or Tencent or JD.com over the course of the last two years will have felt the tetth of those regulations biting very, very hard. But I think we’re now position where by we can understand what the regulatory environment looks like, and we can invest within it and that usually is a very powerful place to be because we now understand what the rules of the game are.
RLA: Well, as ever and as expected, Chris it’s been incredibly interesting thank you very much for your time today.
CF: Not at all.
SW: The Sanlam Artificial Intelligence fund, as Chris eluded to in this interview, uses AI systems in its fund process to help find companies whose business models are aligned to benefit from the growing world of AI. A particular stand out feature of this fund is it’s ability to look for companies that incorporate artificial intelligent systems into their business, rather than simply those companies making AI today. To learn more about the Sanlam Artificial Intelligence fund and read other thought pieces on the topic of AI please find fundcalibre.com
Please remember, we’ve been discussing individual companies to bring investing to life for you. It’s not a recommendation to buy or sell. The fund may or may not still hold these companies at the time of listening. Elite Ratings are based on FundCalibre’s research methodology and are the opinion of FundCalibre’s research team only.
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