AI Investing Opportunities Outside of Tech - 8/13/24 | Market Sense | Fidelity Investments
HEATHER HEGEDUS: Hello there, and thank you so much for joining us today for Market Sense. I'm Heather Hegedus with Fidelity. So from a wild start to a calm finish, stocks are roughly back where they started after last week's sell-off. But even though the market has largely recovered, some investors have been left a little bit shaken up by this, of course, by those big swings and may be wondering if it's a sign that the market is now on less stable footing.
So we're going to be talking about that today and to talk about how investors may be impacted and how they might be feeling about all of this. And that's why we're joined today by Naveen Malwal, who's an institutional portfolio manager here at Fidelity. Also today, our topic of the week is how artificial intelligence is impacting the economy and all kinds of businesses and not just the tech sector. Today, we're excited to be welcomed by Tom Rollins. He is an institutional portfolio manager here at Fidelity with a focus on US stocks. He's going to be laying out for us the spectrum of potential opportunities that this growing technology may present for investors now and in the future.
So thank you both for joining us. I think this is going to be a good one today. And Tom, welcome.
TOM ROLLINS: Thanks, Heather. Appreciate you having me. NAVEEN MALWAL: Yeah, it's good to be here. HEATHER HEGEDUS: Well, thank you very much for making the time as we welcome the dog days of summer. Today is Tuesday, August 13. Before we dive into the AI topic today with Tom, I do want to get caught up on the markets.
We've got a lot to talk about today, Naveen. You know, this time last week, you were helping to calm the fears of our viewers, Naveen, after that stock sell-off. But since then, conditions have improved.
The market seems to be rebounding nicely. But it was quite a ride, to be sure. So can you, first of all, talk about what the latest is right now at this moment? Where are we right now? NAVEEN MALWAL: Yeah, so to your point, much of the volatility we experienced last week, the market has thankfully recovered from that.
I think what drove the volatility was a couple of data points that came out showing perhaps some softening happening with the economy. So we got a slight uptick in unemployment. We saw some soft manufacturing numbers. And some investors started to focus on that a lot.
But the good news is if you zoom out from those two data points, you look at a broader range of economic data, things are still pretty good for the economy. I think that's what investors started focusing on as days passed. And I think that's what's led to the recovery. So for example, unemployment did tick up. But still, it is very close to all-time low levels in its history. So that's good news for the job market.
So a lot of jobs out there. Consumers are still out there spending their money. And that is a big driver of US economic growth year to year. And finally, the profit outlook is still positive. We had good earnings growth in the second quarter.
Expecting further earnings growth in the third and fourth quarter of this year. So overall, maybe a constructive backdrop for the stock market. HEATHER HEGEDUS: So that update on the job market was welcome news for sure. What else do you think helped to turn things around after the sell-off last week? NAVEEN MALWAL: So I think just in general, thinking about the general movements of the market, it can feel like when we have a sell-off, oh no, this is the beginning of something really big and something really challenging coming up.
But more often than not, the market does recover relatively quickly. And what we saw last week is pretty typical. The sell-offs take place.
Some worrying headlines come out. And some investors may react to that. But these bad days can come pretty quickly on the tail end of it. So this is a reflection of stuff you hear from us day to day on Market Sense-- or week to week, I should say, on Market Sense, which is about being patient, not overreacting. And last week was a good example of that.
For those investors who did react to the market volatility and did cash out, they have missed out already on a few days' worth of gains. And they may continue to miss out on gains if the market continues to recover from here. Whereas the patient investor, sure, they had some volatility, but they're pretty close to back to where they were before the volatility began. And these are the little things that, over time, can add up in favor of the patient investor, whereas the more active investor can sometimes leave themselves out of a recovery. HEATHER HEGEDUS: OK, so hopefully, since the economy seems to be growing, this was more of a near-term event.
What are some of the other takeaways that stand out in your mind for investors out of all of this, Naveen? NAVEEN MALWAL: So there's a few things that stand out. I think the other big one I'm thinking about is if you are invested in some of these big growth companies right now, you probably aren't feeling that great because the recovery hasn't made up for the volatility you have experienced over the last few weeks. These stocks had a tremendous run to start the year, but the last few weeks have been more punishing for these stocks.
And here, I think history can be helpful again. So we have seen sell-offs either for the entire market or parts of the market in the past before. And patience is the key here. As long as the investment thesis hasn't drastically changed in the investor's mind when it comes to the long-term outlook for stocks or for bonds or parts of those markets, then generally speaking, over time, the market has recovered. We've seen the market come back from sell-offs before.
It just may take a little while. But I wouldn't abandon a long-term plan just because we've had some volatility for a few weeks. HEATHER HEGEDUS: How about the takeaways for investors who saw parts of their portfolio come under stress over the last few weeks, perhaps in the technology space, which we're about to talk about right now? What would the takeaways be for them? NAVEEN MALWAL: I think here, it's focusing a lot on the fundamentals, the individual investments one has. So if there are specific companies or parts of the market that one is following, then trying to understand what has driven the volatility and how much of the thesis do you agree or disagree with. So for instance, some of the volatility over the last few weeks seems to have been driven by these rising costs for developing artificial intelligence and other technologies.
And some investors were surprised by that and were wondering, gee, this is kind of expensive. When will these technologies start to pay off? So that's a question for every investor to ask themselves. But that's just one part of the technology space. It's thinking about the other components as well and wondering if something's shifted here with this specific business or this part of the technology space that maybe I want to lean away from. Or perhaps, maybe this is a buying opportunity.
Maybe this is an opportunity to buy a dip because long-term, I still believe in this story. Patients that research, I think those can be valuable tools for investors. HEATHER HEGEDUS: OK.
And those are questions that only an investor can ultimately answer for him or herself. They have to take a look at what their goals are. Is that what you're saying too, Naveen? NAVEEN MALWAL: Yeah, generally speaking, just focusing on, what are they trying to achieve? What is their time frame? What is their risk tolerance? All of that can go into, how much of this recent volatility is going to affect my plans and my long-term outcome versus what I need to do right now or, in many cases, what I don't need to do right now, which is don't overreact, and don't get off track. HEATHER HEGEDUS: Well put.
That helps a lot, my friend. Thank you, Naveen. And speaking of investor challenges in the technology space, so AI has been driving big tech growth for more than a year now. But as we've been saying, big tech has gone through some volatility lately. And that's why we wanted Tom to come on for our discussion today of AI opportunities. Tom, first of all, let's talk about AI.
I think, for some of us, our experience with AI is simply an everyday task, things like using ChatGPT to write a wedding toast or write a presentation or maybe even come up with a grocery list or brainstorm ideas. So it's clear to a lot of us that it has the potential to transform nearly every industry. The capabilities seem almost endless. Where have you seen opportunities in AI so far, and what other sectors do you think could benefit from this technology? TOM ROLLINS: Yeah, thanks, Heather.
So I totally agree that AI is likely to impact most industries. And so far, the world's really in the early stages of building out the infrastructure for AI. So far, much of the market capitalization value associated with this infrastructure build-out has accrued to some of these mega-cap tech companies in the semiconductor industry or cloud computing industry companies we've all become more familiar with by now.
And many of them were at the center of the volatility that you and Naveen were just speaking of. But there have also been AI beneficiaries outside of the technology sector. So for example, some industrial companies providing important components for data centers have been in very high demand. So cooling systems, for example, are really important in these data centers. A lot of industrial companies are making those cooling systems. Another example would be US electricity, where demand historically has increased by only an average of about 1% per year for the last 30-plus years.
Increased power demand by data centers could cause this rate to increase to mid-single digits, which doesn't sound like a lot, but cumulatively, over time, the difference of mid-single digits versus 1% per year could have a really big impact. So that could create opportunities for growth for utilities companies supporting the power grids as well as energy companies that can provide needed power. In addition to that, what we've seen in terms of businesses translating AI investment into increased revenues, so far, we've seen social media companies, which are typically classified in the communications services sector, have been effective here. They've been investing in the graphical processing units from NVIDIA, for example, to serve more relevant content to their customers. Also, programmers use AI to write code more efficiently. And of course, there are the software companies that are providing chat assistant functionality, like what we've seen with ChatGPT from OpenAI.
And there may be applications for AI that we, as an investment industry, haven't even thought of yet that could emerge in the coming years. HEATHER HEGEDUS: Right. Yeah, I was just thinking that as you were saying that. There must be so much we haven't even anticipated or thought about yet because we're just simply in the early stages of this build-out, as you said, Tom. So you said this technology has the ability to transform or re-energize current business models. What do you mean by that? TOM ROLLINS: Yeah, so while it's unlikely to replace human advice, our research team thinks AI is likely to play a growing role in financial services, for example, and health care.
So in financial services, for example, some financial companies are already using AI to help with fraud detection and compliance. In health care, AI has similar efficiencies that it can provide. Some health care companies are using AI to reduce the amount of paperwork and other repetitive tasks conducted by doctors and nurses, potentially giving them more time to spend with patients. AI has also shown promise in analyzing diagnostic images, like X-rays and MRIs, where some doctors think the technology can help them work more efficiently. There's certainly debate in all of these industries. And with every new technology, there are potential drawbacks.
As health care companies implement AI to manage their businesses more efficiently, they have to ensure they're acting ethically and responsibly, for example. But across industries, AI is being used to analyze large data sets quickly that would typically take people a lot longer to evaluate. So it can reduce repetitive tasks and allow employees to spend more time on bigger picture initiatives. HEATHER HEGEDUS: You make a good point, that investors really should understand some of those drawbacks and risks and debate as well. But as you said, we're really just at the beginning stages of this build-out.
And a lot of people are comparing this boom to the tech advancements in the late '90s. I remember being in college and using email and the internet for the first time. And a lot of people are comparing where we are now to that.
And so I'm wondering, do you see those similarities? And just in terms of what this all means for investors, what can investors learn from what we know from history? TOM ROLLINS: Yeah, no, absolutely. And I think that's one of the most exciting aspects of being an investor in this type of technical innovation cycle is there's likely to be a lot of innovation using AI in the future, but it's, at this point, really hard to foresee exactly where that innovation is going to come from, similar to how, like you mentioned, how other technology trends have unfolded in the past. So yeah, like you said, a lot of people compare what's happening with AI today to the internet in the late 1990s.
At that time, it was impossible to predict the future business models that would be enabled by the internet, for example, the internet-enabled smartphones. But the iPhone didn't come out until 2007, years after, obviously, the internet. And we first started learning about email in the 1990s.
But even in 2007, when the iPhone came out, it was difficult to anticipate the future business models that would be built on that platform. So when the iPhone was released in 2007, the market was very focused on the various industry players who were clearly impacted at that time, like wireless carriers who could profit by implementing data surcharges or hardware companies who could sell more handsets or more phones or cell phone tower companies that could profit by transmitting more wireless data. Those were the obvious industries and companies connected to the theme.
But at that time, it was impossible to anticipate the emergence of platforms like Uber, which came years later. Uber didn't raise its Series A financing until 2010 and didn't go public until 2019, again, years after the creation of the internet and years after the release of the iPhone. So we don't know what the next disruptor will be for AI. We don't know what the future Uber business model of AI is going to be. But as active investors with a big research team, we will hopefully be early to identify these applications in the future.
ChatGPT, which you mentioned, came out in November of '22. So right now, if you compare that to past cycles, it feels like we're at a similar stage as where the iPhone was in 2008. And as we mentioned earlier, a lot of the market activity and most of the stock price moves related to AI in 2023 and in the first half of '24 have been concentrated among a small group of these mega-cap tech stocks. But as more use cases for the application of AI emerge, we think participation in this long-term theme is likely to broaden out into companies in a range of industries and different market caps, smaller cap companies in addition to the large caps we've seen so far. HEATHER HEGEDUS: It really is fascinating when you take a step back and you think about how it all unfolded and you think of it from the vantage point of the iPhone and where it was in 2008, right, Tom? TOM ROLLINS: Yeah.
HEATHER HEGEDUS: So let's bring Naveen back in now. Let's talk a little bit about how these stocks are being valued. And I know that a question on investors' minds, Naveen, might be whether some of these tech stocks have been overvalued given the events of the past month or so. What would your answer to that be? NAVEEN MALWAL: So valuations, in my mind, are subjective.
Where one investor might see something as too expensive, someone else might say that valuation is justified. So thinking about these technology companies, first, some context. The valuations, looking at metrics like price to earnings ratios on technology stocks, the big growers right now are not at the levels they were at in 1999 or the early 2000s. So this is not a repeat of those kinds of valuations we saw during the tech bubble. These valuations feel much more reasonable. They are much more grounded.
Not only that, but a lot of the valuations attached to the, quote, "higher valuation companies" are for companies that have had tremendous earnings growth and where the outlook remains promising. So back in the '90s and early 2000s, a lot of companies had actually not a lot of revenue and no profit to speak of with very high valuations. This feels very different. Having said all that, looking at valuations by themselves, it may lead the investor to conclusions that are not all that constructive. So just because a stock is valued more than other stocks in the market doesn't necessarily make it a poor investment.
If that stock has a very strong growth outlook, stronger than average or extraordinary earnings outlook, then the valuation might make sense, as investors expect that stock price to reflect future earnings growth. I think that might reflect the situation that's true for many of these companies. And yet, as Tom has been talking about, there's still that is so unknown about artificial intelligence. So while there's a lot of enthusiasm and promise and potential here, whether or not the earnings will actually deliver on the valuations, that remains to be seen.
But as Tom also pointed out, this will probably take years to play out. So I think the valuation piece may be part of the research process. I don't believe it needs to be the only thing investors can focus on. HEATHER HEGEDUS: Important point there, Naveen.
And so given this discussion today, how much exposure might investors consider in AI, in semiconductors or tech? NAVEEN MALWAL: So just to go back to my earlier points, when we think about risk, whether you're thinking about market volatility or how much to allocate towards something, it comes down to everyone's individual situation. And some of the more common things that our friend Leanna will talk about is, what is your risk tolerance in terms of comfort level with market volatility? When do you need the money? How long is your time frame for this? And then, how much diversification do you want to have? Do you want to have more than one type of investment in your portfolio to perhaps help reduce the volatility? And that can all tie back to your goals. What are you trying to accomplish with all this money over time? So let's take an example here.
If you have a longer-term time frame, if you don't need the money for perhaps another five years-plus, perhaps these investments have more appeal because even if there's near-term volatility, there is time on the investor's side to make up for that versus the investor who maybe needs the money sooner than that. Perhaps there needs to be less exposure to some of these volatile stocks. As exciting as they might be, that volatility might come back to haunt them if they need that money sooner rather than later. So that, I think, is how we think about managing risk here. For some investors, they can figure this out on their own, based on their own research and experience, whereas others may benefit from discussing things with an investment professional.
HEATHER HEGEDUS: Yep, yep. And really quickly, because we're getting a little tight on time now, Tom, for those investors who might want to navigate this new field on their own or might want to do a little bit of their own homework before talking to a professional, what is the best way to research AI and AI-related investing ideas, Tom? TOM ROLLINS: Yeah, I mean, I think it's clear that AI is here to stay. It's going to be a big transformational move for technology.
It's likely to create disruption and potential opportunity. So some incumbents across all industries could be disruptive if newer companies come along that are able to implement AI better. So our research team is really focused on navigating these risks by looking to identify the business models we think are best positioned regarding AI across their respective industries. HEATHER HEGEDUS: All right.
Great job, Tom. And quickly, before we go, we always like to talk about what we're watching. So Naveen, what's on your radar for this week? NAVEEN MALWAL: Three quick things for the consumer. One is inflation, two is consumer spending, and three is consumer confidence. So a lot of data coming out in the next few days, giving us a better feel for how the consumer is feeling and doing in the United States. HEATHER HEGEDUS: Which will all be important data as we look ahead to the FOMC, the Fed meeting coming up in September.
All right, Naveen, thank you so much. And Tom, thank you for joining us today. It was so nice to meet you. And you gave some terrific insights today. And just a reminder that just sometimes, it's helpful to talk through some of these financial questions or concerns with a professional.
And you can always call us, go to our website, or download our app if you're looking for that. If you missed any part of the discussion today and you want to see it again, we do have a full catalog or a partial catalog, the full catalog of the most recent shows, I should say, on YouTube. You can watch the replay from today too.
And while you're there, give us a like. You can also catch us wherever you get your podcasts. On behalf of Naveen Malwal and Tom Rollins, I'm Heather Hegedus. Thanks so much for your time today.
We'll see you back here next week. Remember, we're on Tuesdays at 2:00 Eastern. [MUSIC PLAYING]
2024-08-19 19:07
