Vodcast transcription

JM: Hello, technology is reshaping every part of the global economy – from how we work to how we invest. A warm welcome to The More You Know. It’s the podcast from STANLIB Asset Management. I’m Jeremy Maggs and my guest today is Mark Lovett, Head of Investments at STANLIB.

Mark has just presented “From Stagnation to Acceleration, Lessons to Navigate the Next Great Disruption”. It’s a compelling look at how generative AI is transforming the world of finance and whether this wave of innovation could also be sowing the seeds of the next market bubble.

Mark, a very warm welcome to you. Your presentation begins with a line from the James Bond movie Skyfall. Let me just remind you: “Youth is no guarantee of innovation, age is no guarantee of efficiency”. Now, we can either talk about your favourite Bond movie or you can tell me what that quote tells us about the mindset that is needed these days to navigate disruption. I sense you’ll go for the latter.

ML: Well, Jeremy, it’s taken 35 years to get a James Bond quote into an investment presentation.

JM: And congratulations.

ML: So that was one achievement. But there was some thought behind it as well because, you know, we’ll obviously talk about AI as a technology. It is absolutely transformational and it is going to affect everybody. The insights, the views, the need to respond, it’s not around age or anything like that. It’s around everybody recognising that this is going to be a transformational technology for large parts of the global economy. I thought that was a nice one to introduce the presentation.

JM: How transformational are we talking here? Is this a radical sea change?

ML: Over the decades, we’ve had technological changes in lots of different areas and they’re always talked about as being revolutionary. But I do think this technology is one that will have a material effect across a number of segments of the global economy. For me, it’s the breadth of the influence that AI will have, not just the opportunities that exist within the technology itself.

JM: In fact, you call it the next great disruption, don’t you?

ML: I do. Again, it’s just a phrase. We’re in the foothills of AI at the moment, not so much in terms of the investment that’s going into it, but certainly in terms of the applications. But you can still witness what a dramatic effect it will have on the global economy. Unlike other technologies, which have perhaps been in the manufacturing sector or the retailing sector, where there’s a real dominance of the effect of the technology, for me, this is one that is across the broad spectrum of the global economy, but most noticeably the service sector.

My middle son works in the advertising industry and he’s already seeing the effect of AI completely transforming that industry, even though we’re at the relatively early stages of its development. It’s that breadth that makes it a real disruptor across large segments of the economy.

JM: Let’s thread that back to the market, if we can. You’ve lived through three major market cycles. Against the canvas that you’ve just painted for me now about the disruption era, what makes this one different? And let me throw the word “difficult” in as well.

ML: I would recalibrate your question to some degree. I’ve actually worked through a number of different market cycles, but I’ve worked through what I would call three major bubbles. That’s the Japanese commercial property bubble in the late 1980s, the internet.com bubble in the mid and late 1990s, and then obviously the US residential boom and bust and the subsequent GFC in 2008. I’ve personally witnessed what people have always described as “once in a career”-type bubbles. The fact that there’s been three of them tells you they’re not once in a career.

Although those bubbles are never identical, there are traits from each one that you can learn from. That’s really what I think is important in terms of trying to learn those lessons from previous cycles, in terms of what might unfold with this technology, and most importantly, what might happen in terms of financial markets and how they incorporate this technology into share price performance.

JM: Are we in a bubble right now, do you think, or a potential bubble?

ML: I will answer the question, but I’ll start with context. The one bubble that this resonates with is the dotcom internet bubble of the mid and late 1990s. There are definite echoes of this cycle compared to that one, both in terms of the technology development and how the financial markets have developed. We can perhaps touch on that a little bit more later on. But that for me is the comparison that we need to look at.

In terms of are we in that financial market bubble, I would say, yes, we are at a stage of that financial market bubble. But the problem with those type of market environments is that they can go on for a long time. It doesn’t feel to me that we’re at the tail end of that bubble, but we’re somewhere in the development of that, what I would call over-enthusiasm towards a trend, which can go on for a period until the bubble bursts.

I’m caveating a little bit. I think we’re definitely developing some bubble-like traits, but I don’t think we’re at the stage in which it’s going to conclude with a big bust.

JM: How does the asset management industry need to either recalibrate its mindset or start applying new protocols and principles? What I’m asking is, how are you changing your thinking right now?

ML: You have to be very focused analytically in terms of what’s going on, because there’s a lot of news and a lot of hype that goes around every single announcement that occurs within AI. It’s important to try and keep a degree of objectivity about trying to understand what goes on, the investments which are taking place, the return expectations that can come from that. It is that, I think, which is important at this stage in terms of ensuring that the financial market interpretation doesn’t become unrealistic relative to what’s going on.

JM: How do you find a better way of filtering that?

ML: There is no perfect way, Jeremy. If there was, we probably wouldn’t have bubbles. People would be able to see through some of the characteristics that occur. I have a personal barometer that I always look at, and that is when I see flaky business models being validated and supported with capital. That always feels to me that you’re at the tail end of a bubble cycle, where people are throwing capital at models or ventures.

JM: In the expectation that it’s going to stick?

ML: In the expectation that it ticks a couple of boxes and that it will stick. It doesn’t feel like we’re there at the moment. I mean, we are seeing some incredible investment numbers, trillions of dollars, which is quite scary when you look at what’s being invested in terms of building the infrastructure. But while the valuations which are attached to those are high, the business models themselves are not silly. It’s not like the logic behind the build-out doesn’t have some business support. That was very different in the dot-com internet. Towards the end of that, in 1999, there were what I would call very suspect, very flaky business models being validated with capital, left, right and centre.

So that’s why I feel that while there are traits of a bubble developing, we’re not quite at that stage to be fearful that it’s going to burst any minute.

JM: Which sectors are you interested in right now and which are most exposed?

ML: The most exposed is the service sector. It is already under attack from AI in terms of resetting some of the work processes, some of the business models that sit behind that.

JM: Give me a better definition of the service industry or service sector, it’s very wide.

ML: It is and by its nature, it’s wide. It’s the people-orientated businesses that serve a number of different end industries. The 1970s and 1980s was very much a manufacturing disruption. This one is much more about the services sector.

JM: What other sectors are exposed?

ML:  I think it’s across the whole economy. I’ve talked about services. If you think about manufacturing, which itself has gone through a big change, there’s a huge trend going on in terms of robotics. Now, robotics have been around for 30 years in manufacturing, but AI and the large language models and the sophistication that can come with that are going to take that further. You can see in the marketplace some interesting transactions with companies buying into robotics businesses to enhance their capability in that particular area.

JM: How do investors need to start recalibrating the way in which they approach their money and investment philosophy?

ML: In most technological developments, you get a more enhanced winners and losers environment going forward. I think that will be exactly the same in this technology.

JM: What you’re saying is that the risk is more pronounced?

ML: The risk is more pronounced, even within subsectors, that good management teams are the ones which will navigate this technological development and put their businesses on a firm footing to be successful going forward. For me, it’s going to be about identifying the winners and losers. It’s going to be identifying the sectors which are most exposed to it and making sure that you control your exposure there. It’s also about ensuring that you’ve got the right management teams in the investments that you’re supporting.

JM: In that respect, the management teams become that much more critical. It’s difficult but necessary to balance data-driven models with human judgment. It’s not one or the other at this point, is it?

ML: No. My own industry, asset management, is increasingly a hybrid model between man and machine, or between person and data, or however you want to classify it. That is an environment that I think is going to be prevalent across a lot of industries. It’s been a trend for the last 20 years in terms of increased data usage in a lot of industries. But that’s just going to accelerate substantially. If I talk about asset management, because that’s the one that I have the detailed knowledge of, I certainly see an environment in which the asset management industry is much more of a hybrid between data-driven, AI-driven insights and work processes, but also the importance of human insights and intervention in terms of creating products that can deliver the output that we want.

JM: It’s also going to focus sharply on investment performance. AI is going to possibly widen that gap between great and mediocre managers.

ML: Yes. The industry has always been about performance.

JM: But maybe that pronouncement is a little bit sharper now.

ML: It could be. I think, again, the focus between winners and losers will become more intense. It will drive people’s focus in terms of how that performance is being delivered, how people are using technology to enhance what their investment managers, their analysts are doing as a day job.

JM: Mark, can I come back to the words “flaky companies” that you used a little earlier? How can investors separate genuine technological revolution from market hype and that flakiness that might come at the fringes?

ML: Incredibly difficult, because when you’re in the height of a bubble, it’s very difficult to disaggregate between the business logic that every chief executive will be involved in terms of how they’re taking their business forward and what is fashionable, what is causing people to respond positively, which sometimes can be just words and phrases rather than…

JM: But are there not basic rules that you should be applying?

ML: No, I don’t think there are.

JM: It depends on what?

ML: It depends on your own insights, your own views whether what is being pushed, what is being developed is tangible, is likely to occur. Those are subjective judgments.

JM: You also, in your presentation, pointed out that sceptics still have cash on the sidelines. What’s it going to take for them either to put it in or pull it out?

ML: We’re at that stage, I think, in terms of AI technology, in that people are increasingly looking for evidence that the big spend is delivering tangible benefits for companies, both in the subjective form, but most importantly, in returns. That’s increasingly what people will be focused on. You’ll be aware that we’ve already had some surveys out, one from MIT saying, whatever it was, 95% of investment in AI so far has seen no tangible benefits for people. While you have that developmental curve, you will have sceptics. Sceptics will keep cash on the sidelines, believing that there are opportunities elsewhere or later in the cycle. It will need those return expectations to be validated for that more cynical element of capital to come into the marketplace.

JM: At what point do AI-driven markets become too efficient and it leaves no room for that human judgment that we spoke about earlier? At some point that will happen, won’t it?

ML: Yes, it’s a logical question because markets become more efficient with access to information. It’s a very different environment from when I started in the industry, back in 1987, when most data was delivered physically and it took time to aggregate. Through the years, that’s changed. With technology, more data is digital, there’s more aggregation simply at the press of a button. You’ve had that process of technology driving improved information, hopefully improved insights, and therefore markets becoming more efficient.

AI will do that, but I don’t think it removes the importance of human insight. What it will do, unfortunately, in asset management, is remove some of the entry-level jobs which have been part of the industry. These are the type of jobs, when I started as an equity analyst, where you learnt at the coalface and you learnt through doing the grunt work, which is now going to be replaced by AI. That means that you’re going to lose an element of employment in the industry.

JM: You end your talk by urging investors to, and I quote, “embrace, adapt, and improve”.

What does that look like in practice?

ML: I’m a born optimist. When I look at history in terms of technological change, everyone is so pessimistic at the time. But actually humans have a fabulous capacity to evolve with what’s in front of them. I’m a big believer that both in your professional life and in your personal life, technology is a massive stimulant to improvement. That occurs if you are prepared to adapt, integrate these things into the way that you operate and ensure that it results in an improved outcome. That’s why I used those three phrases. It’s really just a touchstone to say, this technology should be viewed as exciting, not in a defensive way that some people want to think about technological development.

JM: Let me end with this. Is there one piece of advice that you would give to a young professional building their career in an AI-transformed asset management industry such as we’ve been speaking about?

ML: It’s a great question. I’ve got three children, young adults, not in this sector, but it’s the same type of question that you need to be asking. I would say from two different perspectives. I think in terms of people at entry level coming into the industry, they’re going to have to recognise that the traditional training ground might not be as robust as it’s been historically. Those entry-level jobs that I’ve talked about as an investment professional will probably, those commoditised processes will probably be taken over by technology. If you’re coming into the industry, to a degree you’re going to have to drive your own training and your own experience through that. It’s not going to be as comfortable a path as it was in my time.

That’s at the entry level. If you talk about people in their 30s, 35, whatever it is, still young, I think that very much goes back to what I just talked about, which is, you’ve really got to embrace this technology in terms of how it can improve how you operate as an investment professional. Having your head in the sand that, you know, things can carry on as they’ve been, I just don’t think is the right way. Other people will use this technology and to be competitive, you have to move forward with it.

JM: With the caveat that you have to be nimble and flexible because probably what you learnt a month ago is not going to necessarily apply in real time and it will change all the time. That’s an exciting road to walk, isn’t it?

ML: It is. It doesn’t mean the end environment changes. But it could be more fluid.

JM: The building blocks are changing?

ML: Yes, and you might have to be able to adapt quickly to make sure that you stay on top of it.

JM: That’s where we are going to leave it. Mark Lovett, Head of Investments at STANLIB Asset Management – thank you very much.

ML: Thanks, Jeremy.

JM:  Generative AI is more than a buzzword, as Mark has reminded us. It’s a powerful force that will transform how we work, invest and interpret risk, creating new winners, new losers and new ways of thinking about value. My thanks to Mark Lovett, Head of Investments at STANLIB Asset Management for his insights. This has been The More You Know from STANLIB, where sharper conversations lead to smarter investment decisions.

Till next time, from me, Jeremy Maggs, goodbye and thank you for watching.