AI's Role in the Future of Wealth Management, Featuring the AI Character "Morningstar Mo"

(This podcast is for informational purposes only, does not constitute investment advice, and references to specific securities or other investment option mentioned herein are not an offer to buy or sell that specific investment. Stay tuned for additional important disclosure information at the end of this episode.)

Nicholas VanDerSchie: Bill Gates recently said, the development of AI is as fundamental as the creation of the microprocessor, the personal computer, the internet, and the mobile phone. These are strong words. Morningstar has invested heavily in generative AI with Morningstar Mo taking the stage at the Morningstar Investment Conference in Chicago and more recently, Future Proof. A lot has already been said about the potential of AI, but how are people actually engaging with it? And how should investors think about their AI exposure in the context of a portfolio?

Hello, and welcome to Simple But Not Easy, a podcast from Morningstar's Wealth Group where we turn complicated financial developments into actionable ideas. I'm Nick VanDerSchie, Head of Strategy and Execution for Morningstar Wealth. And in a first today, I'm delighted to be joined by a special guest, Mo, the Morningstar AI character. We'll also be joined by Adley Bowden, Head of Morningstar's Individual Investor business, and Grady Burkett, Portfolio Manager of the Morningstar Hare Strategy. Together, we'll turn AI speculation into real-world application. If you'd like to know more about how we support advisors, we welcome you to email us at simple at simple@morningstar.com or me directly at Nicholas.VanDerSchie@Morningstar.com.

Now, let's get started. Adley, Grady, Mo, welcome to Simple But Not Easy.

Adley Bowden: Thanks so much.

Grady Burkett: Of course.

VanDerSchie: So, we're here today talking about AI, artificial intelligence. And I want to start with just a simple definition for listeners who may not be as familiar with the term or the technology. And since we have Mo here with us today, why not start with him? Mo, how do you define artificial intelligence?

Morningstar Mo: AI, or artificial intelligence, is a technology that allows computers to think and learn like humans. It helps them understand and solve problems, make decisions, and even recognize images and speech. It's like having a smart assistant that can do tasks and answer questions just like you.

VanDerSchie: Grady, I'd be interested in your perspective on Mo's definition. Did he get it right?

Burkett: I think it's close enough for what we're discussing. I would probably debate that the learning is at a human level. I think that'd be a little bit more advanced than where AI technology is now.

VanDerSchie: Fair enough. So, Mo, as mentioned, is our AI persona or character, and we make Mo available through a variety of Morningstar products, including Morningstar Investor, which is a platform for individual investors. And I want to bring in Adley. So, Adley, before we talk about the Individual Investor business at Morningstar, it'd be interesting just to get a bit of an intro from you, talk about your career history, how you came to Morningstar. It's a little bit unique, and so maybe you just share a little bit about your background with our listeners.

Bowden: Yeah. Thanks, Nick. I found there's a mighty crew of us at Morningstar that came via acquisition. And my personal story is I started at a company called PitchBook, which Morningstar has now acquired, more or less straight out of college. And PitchBook is a company focused on private markets research, so venture capital, private equity, private debt. We track the full life cycle. So, everything from the original investment through the holding period, and then through the sale, and the returns that that generates back to the LPs. It was much smaller when I started. Now, private equity, venture capital is on the front pages of the Wall Street Journal and whatnot pretty regularly. But during my tenure there, started collecting data, digging through financial filings, and eventually started our newsletter and our editorial function, the research that PitchBook produces, which we can actually produce research on AI. So, we need to touch on that in a little bit and a number of other roles for those 13 years.

But then, after Morningstar acquired PitchBook, I got to know a lot of people across Morningstar and began to use more of Morningstar's tools, including Morningstar.com. And I was kind of perennially frustrated with what I felt the state of those tools were. I think PitchBook was sort of modern and cutting edge, and that wasn't the case with dotcom. And I voiced that to the executive who was running those areas of Morningstar, and eventually the opportunity opened up, and he suggested that maybe I should put my feet where my mouth were and come over and join the Morningstar team focused on dotcom and the individual business. So, that happened about two, two-and-a-half years ago. So, I've been focused on that area of Morningstar since then.

VanDerSchie: Great. Thanks for sharing that background, Adley. Just talking about the individual business for a minute, that is a business line that resides within Morningstar Wealth. Can you maybe talk a little bit about what that business is comprised of and why the connection to Morningstar Wealth more broadly?

Bowden: Yeah, certainly. So, the individual business within Morningstar is a collection of a couple of different properties, the biggest one being Morningstar.com itself really focused on directly selling Morningstar's data, research, and some tools to individuals. Most of Morningstar is actually serving individuals, but via advisors or via third-party platforms like a Schwab or something like that. We're the group that works directly with individuals. So, we've got various, like I said, properties and products, dotcom and editorial team there, but also our subscription product called Morningstar Investor, which in addition to getting our data and our research, you can monitor your portfolio, you can screen using our data and our research to find investments and evaluate them and try to maintain the asset allocation that you're looking for and hopefully grow your wealth over time. We have another set of products called newsletters, FundInvestor, StockInvestor, DividendInvestor, ETFInvestor to help individuals build portfolios or follow some of the portfolios that actually the Morningstar Investment Management team maintains. Tortoise and Hare Dividend might resonate with some of the listeners. So, there's a version of that and sort of a model portfolio and curated research that individuals can directly purchase.

Alongside that, Morningstar.com is just a big media site property for us, both in the U.S. and then we've got 27 different country-specific versions as well that we maintain. And the connection point within Wealth, I think, well, one, there's the Investment Management connection, but Wealth is really close to serving, I think, the end investor as well as the advisors. And that's where we fit in and intersect in a lot of different ways with the content, with the data, with the research, and that focus really on the end investor.

VanDerSchie: Great. Thanks, Adley. So, I want to bring it back to Mo, because after all, this podcast is about artificial intelligence. I guess why did you think it was a good idea to launch Mo, the Morningstar AI character, within Morningstar Investor, and what were you expecting to get out of that?

Bowden: Yeah. Well, it's been a – Moe was a whirlwind. It first appeared, I think, in late March, early April, in some back rooms of Morningstar. And then, a couple of weeks later, it was suddenly at the Morningstar Investor Conference on the keynote stage with Kunal, our CEO. And then, a week or two later, it was like, let's get that into the products. I was involved early on, and I felt that there was a lot of capabilities that Mo would bring to the individual experience in its way that it can help individuals easier with less challenges and friction, find the information they're looking for. And so, that was really the premise of wider-bring Mo to investor, and it's come to other products. But what we're trying to do with the idea of how can generative AI laid on top of all of our data and all of our research help empower investors to be more successful.

VanDerSchie: So, Mo has been out there for a few months now. If you had to observe how investors are interacting with Mo, what have you seen?

Bowden: Yeah. We're seeing all behaviors. I think my guess is a lot of the audience has played around with various AI tools and ChatGPT, and now it's in Google Bard, and Bing, and all these different places. I think we've seen just a lot of experimentation. People trying to see what it can do well and what it can't do well. There's many breakpoints and different things. Where we see the repeat, people who've adopted it and have actually kind of begun to use it as part of their investing workflows is sort of a high-powered search. And instead of them having to dig through and go to a quote page and find a piece of information, they're able just to kind of pull up Mo and ask it a very direct question. How many stars is the Apple stock today and get an answer back very quickly and easily. So, it can make the research process more efficient.

It's also really good at explaining various financial definitions and topics that I think it's underused. You see some usage of that, but it's an area that hopefully we can get more people using it because it does, like its description of AI, a pretty good job of just breaking down a lot of topics and a lot of data point labels if you want to try to understand what they are, it will give you that explanation. So, we see a lot of that type of activity. I'm looking at an analysis of, I think, 55,000 questions that were answered Mo over a period of time and they broke it down by who, what, where, when, why, what, like what the first word was. And it's pretty interesting that about half of those queries started with what, what is the Star Rating, what have been the inflows or the outflows or what are the costs of. So, most people are using it in that research standpoint. Not so many why's. There's only about a thousand questions at why is something. So, they're not expecting again the human intelligence to answer deeper questions about why something is the way it should be, but more around the like what is something, and it is an efficient way to get that.

VanDerSchie: Those are pretty fascinating insights, Adley. I'm sure you're collecting a lot of information and data in terms of how your users are interacting with Mo. Any interesting stats that you can share with us?

Bowden: I think there's some there's some interesting tidbits that if you look at people's feedback is, they don't fully trust AI yet. A lot of the feedback is around wanting to get transparency into where the information came from. And I don't know if that is just the way Mo presents information isn't super trustworthy, but I think it's AI in general. People still don't quite trust it. And if you're going to make an investment decision, you should probably do your due diligence to go beyond what Mo tells you. In fact, there's like three levels of acknowledging that before you can use Mo. But there's a lot of people wanting to just dig deeper and verify what's coming. And then, like I said, it's just people are trying to use it in that workflow research kind of modes. Compare this, this versus that, how many stars, what's the medalist rating, all that type of stuff is primarily how people are using it.

VanDerSchie: That's fascinating. So, just from a practical accessibility perspective, if advisors are listening and they want to access Mo and interact with him, what's the best way for them to go about doing that?

Bowden: Yeah, there's a few different routes. For advisors, it's available via, a Morningstar product called Direct Compass, used to be called Research Portal. But it's essentially a research hub that I think all Direct users, some AWS users, other Morningstar products as well. So, I'd recommend reaching out to your rep or just clicking around and seeing if you see Mo anywhere. For any individuals listening to this, it's also in Morningstar Investor. It is customer-facing-only right now. There is no freely accessible version. Part of that is compliance. Part of that is also there's some interesting limitations to Mo. It's not yet necessarily a conversation bot. It's sort of more a question-and-answer bot. So, there's work to be done yet to continue evolve it, which there's a whole team at Morningstar focused on that and continue to try to build it out and figure out how it can layer into more of our experiences.

VanDerSchie: That's great. So, we heard from Mo at the very outset of the conversation. I want to get back to Mo in just a second. But before we do, I'd be curious, Adley, like, when you take a step back and look at artificial intelligence, do you see this as another passing fad, or do you believe there could potentially be some stickiness longer term?

Bowden: Well, I think most of these start as passing fads. And then, in that you find the spots where it actually is going to stick. That makes sense. And back in my PitchBook days, one of the things we started was emerging tech research. And we built a whole team of experts in different emerging tech areas. AI was one of them, as well as mobility, AR, VR, things like that. And all have gone through their various like Cambrian explosions and then the fad, but then you're like, oh, actually, you know what, that was really useful over here and over there. And I think that's going to be the case with generative AI, which is really what we're kind of talking about where some of the applications in various research workflows, learning, I think it will be interesting in schools now and what it as a tool that people can use will be. So, I think that's where it will stick. I don't think it's this world changing technology yet for many reasons, but I think it's definitely going to be a new tool in everybody's toolbelt for creating various pieces of content or learning various things or trying to understand stuff. But this has evolved so fast, like, who knows how quickly this really could become something bigger.

VanDerSchie: So, we've talked a lot about how Morningstar is using AI and Mo and we heard from him briefly at the outset of the podcast. I think our listeners would like some additional engagement with Mo. So, let's go back to him for a few more questions.

First, Mo, I'd like to know what you think about the hype around AI. Is it exaggerated or just the beginning?

Morningstar Mo: AI has shown great potential in various fields, but it is still in its early stages. While AI can perform tasks like image recognition and language processing, it lacks the ability to truly understand and think like humans. The hype around AI may be exaggerated, but it is just the beginning of a technology that will continue to evolve and impact our lives.

VanDerSchie: Okay. So, Grady, I think Mo is coming around and now agreeing with your earlier point around AI's inability to truly think like a human. My next question for Mo has to do with the future of financial advice.

Mo, I'd be interested to know if you think AI will replace financial advisors.

Morningstar Mo: While AI has the potential to enhance and automate certain aspects of financial advisory services, it is unlikely to completely replace human financial advisors. AI can provide data-driven insights, but human advisors offer personalized guidance, emotional support, and the ability to adapt to complex situations. Job losses may occur in some areas, but new roles and opportunities are also likely to emerge.

VanDerSchie: Got it. Thanks, Mo. So, let's try to use AI to help with one of those practice-level opportunities. Mo, can you help me write a hundred-word email to a distressed client who is worried about market volatility and wants to move her portfolio to 100% cash?

Morningstar Mo: Hi, I hope this email finds you well. I understand that recent market volatility has caused some concern for you. It's natural to feel uneasy during times like these, but it's important to remember that market fluctuations are a normal part of investing. While it may be tempting to go to cash during volatile times, it's important to consider the long-term implications of such a decision. Timing the market consistently is extremely difficult, and it's easy to miss out on potential gains when trying to avoid short-term losses. Instead, I recommend focusing on your long-term investment goals and maintaining a diversified portfolio that aligns with your risk tolerance. This approach can help you weather market volatility and potentially benefit from market recoveries. If you have any further questions or concerns, please don't hesitate to reach out. I'm here to support you and provide guidance. Best regards.

VanDerSchie: Pretty impressive, Mo. I can definitely see how a use case like that could potentially be a time saver for advisors. Okay. Last question for you, Mo. Do portfolio managers have the ability to understand which AI-focused companies will outperform their peers?

Morningstar Mo: Portfolio managers can use their expertise and research to identify AI companies with strong growth potential. However, accurately predicting which specific AI companies will outperform is challenging due to the rapidly evolving nature of the industry and the inherent uncertainties associated with investing in emerging technologies.

VanDerSchie: Great. Thanks, Mo, and that's probably a really good segue to bring Grady back into the conversation so we can start to discuss how he is thinking about investing in AI companies. Grady, maybe to start off, can you share a little bit about your background and role specifically and also share a little bit about the portfolio that you manage Morningstar Hare?

Burkett: Sure. I'm Grady Burkett and I've been in the investment industry for nearly 20 years. I think most relevant to this conversation is I spent seven years covering technology companies as an equity analyst at Morningstar and that was actually from 2007 to 2014. So, two pretty big tech trends at the time. One, obviously, mobile with the iPhone subsuming other mobile phones in the market, and then the other is cloud computing, which happened more slowly. So, one of those trends happened fairly quickly with the iPhones and Android and then the other is an ongoing trend. And then, what I do now is I went to an investment management firm called Diamond Hill Capital Management, where I was a portfolio manager and again a technology analyst from 2014 until 2022. I rejoined Morningstar specifically to manage the Hare portfolio, which is what I'm doing now. And I did that in late 2022 and I started managing the portfolio at the beginning of this year.

The Hare portfolio is a – it's a focused portfolio. It holds 27 higher-quality businesses with what we expect to be above-average long-term earnings growth. And so, many of the companies in Hare have big cloud businesses that have invested heavily in artificial intelligence related technologies for quite some time and are investing heavily in generative AI specifically now. And some of those larger holdings in the Hare are Microsoft, Amazon, Alphabet and Meta. And so, I'm following this space pretty closely and looking to see what a variety of companies are doing with this.

VanDerSchie: Great. Thanks, Grady. And we'll come back to the Hare portfolio in just a minute. But maybe to start things off as it relates to AI, can you maybe share a little bit of perspective from where you sit as a portfolio manager and how you're assessing and thinking about the AI landscape?

Burkett: Yeah, I think that there are a lot of different ways to look at it. And one of it, I think that Adley mentioned, which I agree with the sort of rates of adoption and how this technology would be adopted and used by various companies and what it means. When I think about different technologies, and Clayton Christensen and use the term disruptive technologies versus enabling technologies, and so far, largely what I'm seeing, I would characterize these newer AI applications as sort of enabling. But as far as for investors and the landscape, I mean, one way to think about this is, you can bracket businesses into five different categories. The first is the semiconductor and hardware companies that make the chips and the various components that allow machine learning algorithms to happen at scale and companies like NVIDIA, AMD, Taiwan Semi. So, those are examples of these types of businesses.

The next is infrastructure companies, companies that deliver software and hardware systems. And this is, I'm thinking, Microsoft, Amazon, Alphabet, they have large cloud businesses and they're going to provide AI services to business customers and individuals who care to use those services on their clouds. Then there's a whole swarm of newer companies and PitchBook would follow these very closely, but they're starting to bubble up in the public sphere as well. And these are the companies that are building software applications based on newer AI technologies, foundational models, generative AI, things like that. There are also new chip design companies and companies that are providing very specific consulting services to help organizations build AI applications and workflows.

Fourth, you can think of the traditional software vendors and consultants. So, like a Salesforce.com is embedding AI tools into its various software or an Accenture announced earlier this year, it's investing an additional $3 billion to help provide AI services to their clients and are on a big hiring spree around AI skills. And then, finally, just really, you can look at any public company and go to their website and read through their transcripts and listen to their management teams and how they're talking about AI. And I think that most of the larger public companies, if not all of them, are at least experimenting with AI. So, those are some different ways to look at the various types of companies involved in AI.

VanDerSchie: Yeah, that's really helpful, Grady. Appreciate that perspective. From where we sit at Morningstar, there seems to be a heightened interest. Some might call it a craze amongst investors around AI. Just a couple of headlines that I've seen recently – of the S&P 500 companies, one-fifth of them mentioned AI in their latest earning calls, which is more than double from just a year ago. And then, ChatGPT, which we all know, has reached 1 million users faster than any other online application, outpacing even Twitter, Facebook and Instagram. I didn't know this, but it took two-and-a-half months for Instagram to get a million users and only five days for ChatGPT.

I guess the question for you, Grady – do you see investors reacting to this? Is the interest overhyped? What's the reaction that you're seeing?

Burkett: A couple of things. I think that there are certain areas and certain pockets where you've got overvaluation. I actually don't think that overall and broadly, we've seen this doesn't feel like a hype or some sort of – yeah, it doesn't feel like sort of euphoria to me at this point broadly. I mean, there are some pockets and there are some specific companies that I would say are overvalued. But I think going back to the ChatGPT application and getting back to how we're talking about it as sort of a productivity tool or more of a business tool, I think one thing about ChatGPT that I find interesting, it was also very entertaining, frankly. It was something completely new, delightful to see a machine respond in a way that feels very human-like. And so, I think that was just a very, very new thing for people to experience. And then, of course, we saw these image generators that were also just amazing. And actually, there's a company called Adobe that makes an application called Firefly that people can experiment with now. If you go to Adobe, go to Firefly, you can get a free trial and you basically say, make me whatever image you want to see, and it will make it. And then, you ask for a change. So, you want it to be night, it makes the pictures in nighttime. You say, okay, make it in the morning. It changes the picture in the morning. So, these are just sort of interesting little things that people can experiment. So, I do understand why the adoption happened so quickly or the early adoption happened so quickly.

VanDerSchie: Yes, I think that's fair. There's definitely no denying the fascination and entry with the technology. You mentioned NVIDIA earlier, and they're arguably one of the first names that comes to mind when identifying AI-focused companies. As of this recording, their stock price is up about 200% year-to-date, and they claim to be the world leaders in artificial intelligence computing. What's your take on NVIDIA?

Burkett: Yeah, I think NVIDIA is interesting because that is one where I do think there's a lot embedded into the valuation in terms of future expectations for that company's revenue. And so, obviously the company is growing incredibly fast. It's a very good business. But the expectations are that the current revenue run rate will sustain and they will continue to be pretty strong growth. I mean, the thing about NVIDIA is that it started as a graphics processor company largely involved in the video game space. And what made it interesting is that these graphic processors can process information or take instructions in parallel. So, they can do certain types of tasks much more quickly than a general processor can, like something from an x86 processor from Intel. And then, the other thing that's interesting about NVIDIA is they created software development library so that researchers could code, or video game developers could actually program their GPUs. And the combination of this coincided with some new algorithms coming up in the academic community around the 2012 timeframe and up until 2017, where their GPUs became the best way to do these machine learning and artificial intelligence algorithms and approaches.

So, the company has certainly just over a long period of time invested in software and hardware in a way that puts them in the best position to continue at least in the near term to capitalize on this. So, totally understand why the business is so highly regarded. I do think that investors need to be a little bit thoughtful and careful about how they're modeling future revenue for the business, because at the end of the day, it is still largely tied to graphic processors, which is maybe a cyclical business.

VanDerSchie: That's a good perspective to have. I'd be remiss not to ask you, especially with Adley in the room, about any private opportunities within the AI space and kind of how do you assess private opportunities more generally versus the public opportunities here?

Burkett: Well, I'm focused on public markets. And so, my interest in private markets are looking for potential competitors to the public companies that are held in the Hare. I would say – and I'd be interested in Adley's take on this too – but I would say investors who are investing in private companies, it's a specialized skill set, and I think often there's more risk involved. So, for me, the private companies are something I watch just as competitors to the holdings in the Hare.

VanDerSchie: Adley, anything to add there?

Bowden: Yeah. I mean, AI is the new buzzword in VC land, they get a lot of jokes. I think there's probably a lot and a lot of applications on top of this AI and the ability to see what shakes out. I think people are a little suspicious that there's some durable businesses in there. I think a lot of times you'll hear the thing thrown out there that that's a feature, not a business. So, there's probably some of that. I think the chip makers are interesting. There's a couple of pretty well-funded chip makers who preexist ChatGPT that we're working on sort of novel chip designs for better AI and the algorithms underneath AI support. So, I think those will be interesting for sure. And then, there's various non-generative AI that is still out there that people forget that some of these algorithms working at pretty interesting problems. I mean, look at driverless tech. A lot of that is underpinned by these neural networks and these very complicated calculations that are essentially AI. So, I think there's some interesting things happening in places that we've all forgotten about AI but certainly still are.

Burkett: Yeah, actually, I want to comment on the feature versus product comment. I think that's one thing to think about is the sustainability of these new companies introducing products and coming in and raising capital. So, if you have a consumer-facing company that largely is selling an application through the iPhone, it's going to be hard to build a durable business just doing that. It's not to say that you can't, but it's one of those things where you make a little bit of an explosion, a little bit of a noise, and then you probably sort of fade back. But I think the more interesting as Adley mentioned, I think chip design, that's a much harder, the barriers to entry are much higher to design a chip that's actually going to get designed into various systems and used by large customers. But if you can do that, that can be a good business. And then sitting between those two ends, there are these software developers or independent software vendors that are making applications that might be used by businesses. And that's another business that can be very sticky, a little harder to break into that market as well. It's not a fast driven consumer market. But there can be some interesting applications. But I think a lot of these private companies end up just going to be purchased by a lot of the large public companies, the ones that are interesting.

VanDerSchie: Thanks, Grady. I want to come back to the Hare portfolio for a minute. So, you shared a couple of names a few minutes ago that are contained within that model. But I guess I'd just be curious, like, can you go a little deeper on some of the stocks that we own within that portfolio that do have AI exposure, why we own them? And maybe if you can share some insight as well on some stocks that we don't own and why those aren't in the portfolio.

Burkett: Yeah, sure. I mean, just the first thing is obviously ChatGPT – all this got really strong attention late last year with ChatGPT. But of course, most of the portfolio holdings have been in the portfolio for a long time. And so, I think it gets to the point on we're owning good businesses, good-quality businesses with good earnings growth prospects. And so, there's some new interesting technology around, they're going to have some exposure to it or they're going to be building tools that utilize this. And so, AI, already given trend, isn't really necessarily the reason why a company is in the portfolio. So, I just want to just generally say that.

VanDerSchie: No, I think that's fair. That's fair.

Burkett: Yeah. But as far as, I mean, going back to those classifications, I will start with the pure infrastructure layer. Taiwan Semi, while they don't actually design chips or make AI-specific chips, they are the leading semiconductor fabrication company. And so, NVIDIA, Qualcomm, AMD, any company that's building chips is going to use Taiwan Semi's fabs. And so, that's a holding in the Hare. And their CEO, C. C. Wei, mentioned in the last earnings call that he thinks AI is going to drive a lot of growth. So, I mean, their forecast is probably not – it's hard to forecast, right? But they believe they're going to get 50% annualized growth in chips that are involved in AI workloads over the next five years. So, they do expect strong growth. And obviously they have to plan for that growth. So, they're actually building capacity to support that growth. And then, I mentioned Amazon, Microsoft, Alphabet, which are all three going to provide – they have different AI services that they're providing. They're all going to use very similar the large language models or foundational models to deliver the services. And honestly, they're going to provide different models. And so, the fourth company I didn't mention that's big and is involved in AI obviously is Meta and even Meta, which has a foundational model that's an open-source model, I expect certainly Amazon and Alphabet are going to run Meta's model in their clouds.

But the Meta is kind of interesting, I think, and I'm going to go a little bit here. So, I'll cut what you need. But Meta is kind of interesting because they're sort of more – I think of them as more the entertainment side of AI right now largely. So, when they mentioned at their most recent conference that they really want everybody to have one of these personal chatbots, but they're thinking of it as an entertainment outlet as well. So, that's interesting. And then, I think that if you go beyond what everybody knows as companies with some exposure to AI, you can look at even like the credit card companies, which are holding in the Hare, so Visa and Mastercard. This gets back to Adley's comment. They're using machine learning tools that are more about classification. So, here's this person with these attributes, is this person credit worthy? And so, this is artificial intelligence that's been around before generative AI took off. But these companies have – they invest heavily into machine learning and they're now investing heavily into generative AI. So, Visa just announced that it's got a $100 million sort of VC fund specifically designed for generative AI companies. Mastercard purchased a company a few years ago called Brighterion, which uses machine learning and will invest in generative AI. And these companies, they use it for their own services, and they also provide value-added services to banks and other retailers and companies to help them with risk assessment and marketing and customer modeling. So, I can go through others, but I think the card companies are examples of companies, hey, these are just really good businesses that are investing in this stuff.

VanDerSchie: So, Grady, if our listeners, advisors like what they hear, and they just want to learn more about the Morningstar Hare portfolio and how they can access it and where they can access it. What's a good call to action for them?

Burkett: Yeah, appreciate that. And advisors can visit Morningstar's US Wealth platform and that's mp.morningstar.com. And they can download back sheets and they can also get commentary on the portfolio there.

VanDerSchie: Super. And then, just from a practical perspective, Grady, as our listeners are considering potentially tapping into AI as an investment opportunity, either for other clients or for themselves, I guess what are some of the principles that they should consider as they navigate those?

Burkett: Yeah. I think that I would not change anything that I'm doing as a portfolio manager, as an advisor. So, I buy high-quality businesses with earnings growth. I wouldn't deviate from that. For me, I have a certain level of diversification I'm looking for in the portfolio, so I wouldn't overweight based on the particular trend like AI. So, honestly, I think, we can look at different opportunities and where companies are exposed, but generally, I wouldn't change an overall investment approach or philosophy around it.

I will say this. There are going to be companies that position themselves as AI companies that probably aren't. And I think that there are lots of ways to snuff that out. But I would be careful about companies or specific funds or whatever that decide to start position themselves as AI companies or AI funds and they're really not. And I would just stick to the first principles that serve you and your investors well would be my suggestion.

VanDerSchie: That's good guidance for our listeners, Grady. Appreciate that. The last theme I want to touch on is just overall disruption and particularly, potential disruption that financial advisors could face as a result of generative AI. Maybe I'll start with you, Grady. I know I asked a question of Mo earlier but interested in your perspective on this. How do you see AI either competing with or complementing an advisor's business?

Burkett: I personally think AI is a great complement to a financial advisor for a lot of reasons. One is it can be a great research assistant or great personal assistant. And I've used a Bard and ChatGPT. I use them both just to play around with them. I've used them before. Like, I'll have a call with an investment relations person from a company and I'll just ask them, Hey, what are the relevant acquisitions in some specific business unit that the company has? And that's a starting point. And then, I can actually ask them questions deeper about those each acquisition. And it's a great way to just get that foundational early research.

Another thing I think that could be interesting is I could see an AI bot or AI chat assistant that knows everything, all the information it needs about a financial advisor's client base and can start your morning for you with like a list of things. And even it can reach out more broadly and say, Hey, this client's daughter just won districts at the tennis districts, and you might want to shoot them an email or give them a call. So, I can see lots of ways it enables. But I think the financial advisors, it's such a relationship-driven business, and it's so important to have a human being in those types of businesses, I just don't see it anywhere on the horizon for this to be disruptive to that industry.

VanDerSchie: Yeah. No, that makes good sense, Grady. Adley, what's your perspective from an individual investor point of view? Do you see any disruption here?

Bowden: The foolish person is the person who says, no, there's no disruption possibility, and then you watch it all change. I think there will probably be some changes. On the individual's side, what is this now possible? And I think, robo-advisors took a lot of individual money, I think, out of individuals making their own investment decisions. And I wonder how AI begins to maybe compete or evolve those to be more personalized versus such kind of formulaic that they are now. And then, just also the ability of certain technologies to be humanized the AI I think has some interesting implications in the financial space where there's a lot of jargon, there's a lot of inaccessible terms. Financial literacy varies wildly. I think AI can maybe close and solve some of those gaps to hopefully help investors be empowered to invest more, invest more confidently, invest more successfully. So, I think for that DIY investor, there's some disruption ahead with AI layered into different tools.

Ultimately though, I think on the advisor side, and even if you step a little bit further back, I think it's an enabler. I don't think the underlying investment vehicles are going to change that people are using. People are still going to be using funds and ETFs and equity ownership and various things like that. But it's more that presentation layer that's going to change.

VanDerSchie: Great. So, we have a consensus from both Grady and Adley that AI will be a net positive for investors and advisors. Thanks guys. All right. So, before we wrap one thing we always do at the Simple But Not Easy podcast is to do a 10-second takeaway. Adley, I'll start with you. If there was one thing you would like our listeners to take away from today's episode on AI, what would it be?

Bowden: I think it would be just keep using it. Keep experimenting. It's still early days. So, the more experiment, it's evolving rapidly, the more ability to maybe be ahead of some others.

VanDerSchie: Great. What about you, Grady?

Burkett: I'd say for the most part, strong, well-managed companies might use this to get a little bit stronger. So, just watch out for that.

VanDerSchie: And there you have it. Another episode of Simple But Not Easy. As always, we thank Adley, Grady and of course, Mo for their time and engagement. Once again, if you'd like to know more about how Morningstar can support you, please drop us a note at simple@morningstar.com or me directly at Nicholas.VanDerSchie@Morningstar.com. Until next time, thanks again from the team at Morningstar Wealth.

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