Sean Kenney:

I'm Sean Kenney and welcome to the MFS All Angles podcast. Over the past few episodes, we've gone deep into different industries, from pharmaceuticals to software and energy, but today we're zooming out a bit to focus on growth investing more broadly. Growth companies are often synonymous with disruption and we are certainly going through a period of disruption in today's markets. To discuss this and more, joining me today is MFS portfolio manager and growth investor Brad Mak. Brad started his career in 2003, and as a lifelong growth investor, he's invested through multiple cycles of disruption and brings great perspective to today's market environment. So Brad, thanks for joining the podcast.

Brad Mak:

Thanks, Sean.

Sean Kenney:

So you have an interesting investment background. You started in 2003. You then joined MFS in 2010 as an technology analyst. You were technology sector team leader in 2016, and then became a co-portfolio manager for our growth equity strategy in 2021. Do I have that right?

Brad Mak:

Yep.

Sean Kenney:

Okay. We've also known each other for probably close to those 20 years here at MFS, but I just learned that in addition to all your success on the investing side, you are a ultra marathon runner. Is that right?

Brad Mak:

Yeah, I've done quite a few over a long period of time.

Sean Kenney:

So someone told me that you ran 150 mile race over seven days. So tell me a little bit about what inspires you to do that in the first place, but then secondly, what are the lessons you take from that to investing or to your life more generally?

Brad Mak:

Yeah, so it started, I played a year of football then in college, realized I was going to ride the bench, so stopped that and then got into endurance sports, first into adventure racing, teams of three doing these a hundred mile races, and then this event in the Atacama Desert, it's the driest place in Chile where they test like the Mars land rover stuff, where you carry on backpacks, like 30 pounds of food, and you basically run a marathon a day for five days and then a 50 mile run for the last two days. So if it's a long journey, you have to be self-sufficient, and just like investing, it's long-term focused. You go through highs and you go through lows, and the middle part of the day is a grind. You're making sure you got the right mentality, the right nutrition, right mindset. And I think it's the same thing with investing. You have to grind it out, you have to have grit and resilience, focus, a trained mind and then be prepared for the unexpected.

Sean Kenney:

And to put in the work.

Brad Mak:

Put in the work.

Sean Kenney:

30 pounds of food does not sound like enough food to me. I would need a lot more food to do that, but that sounds really impressive. So really interesting background. Maybe we'll touch on it at the end as well. But so let's start with investing. So we're talking about the growth space more generally. You've been a lifelong growth investor. Start with talking about what's your framework for growth investing?

Brad Mak:

As a growth investor, you're looking for industries and the companies within those industries that have a durable ability to outgrow the underlying industry and their competitors because they have something, a product or service, that's unique, differentiated, and defensible. So historically, if you look over the last, call it 15 to 20 years, this has really benefited the compounders, companies that had a stable duopoly or oligopoly, that had high margins, that were capital light, and that you could envision and see a path where they could grow above market for a very, very long time. And that has been the cornerstone of our investment process on the growth team.

Sean Kenney:

So if you think about the market environment today, seems like a lot of disruption, a lot of things happening in the market. How do you approach that now? Are things different?

Brad Mak:

So as you know, the adage history rhymes, it doesn't repeat, so it's very helpful to look at the late '90s with the internet build out, the mid 2000s with the advent of the smartphone and then the cloud transition. I think what's different about this time is it's the scaled incumbents, called the mega cap companies, that are the ones that are doing the biggest amounts of investment in this AI transformation. So it's different in the sense that it's the incumbents who are doing all the spending versus you go back to the '90s, it was literally the telco companies building out, but none of the internet companies had been created.

You go back to the advent of the phone, Apple created the iPhone, it hadn't existed before. And then in the cloud transition it was the companies that were the incumbents were the ones who were at risk of disruption. So in Oracle or an SAP and all of these new companies were created. We're going to see a lot of new AI companies created now. But all of this, it's a combination of existing incumbents investing to grow and defend profit pools and a whole new wave of companies that are being formed.

Sean Kenney:

Yeah, it's interesting, if you look back in history, a lot of disruptions happened. To your point, it rhymes but maybe isn't the same. We were just talking to Jude Jason in the last episode talking about the energy transformation and he shared that you don't typically think of energy companies as growth companies, but yet today, given the AI build out and all the infrastructure required to fund AI into the future, there is growth in the energy space. Talk to me about where are we seeing pockets of growth outside of technology, which is where I think most people think traditionally about growth.

Brad Mak:

So I think we have another adage on the growth team, which, when the facts change, we have to be at least open to change. So Jude talked about how the energy demand grew like 1, 2% for the last two decades, and now it's forecast to grow 3 to 4% because of AI and a lot of the electrification. So even though going from 2% to 3% growth doesn't seem that exciting, that's like a 50% jump in a no growth industry, and that has really permeated beyond the energy sector into the capital goods sector. So you have companies that historically were very short cycles, sold into very cyclical end markets. Now because of AI and these long data center build outs, have 2, 3, 4 years of visibility into a much longer cycle for everything tied to data centers, and then also on the physical AI side with companies like Tesla, they're building out robotics and electric vehicles and autonomous vehicles. These are very long cycle end markets.

Sean Kenney:

So it seems like it's translating into multiple industries. You have the benefit of working not just as an individual growth investor with a small team, but being a part of an interconnected global platform that's cross channel, cross region, cross capital structure. Talk to me about how are you and the team working through this disruption and how is it impacting different industries?

Brad Mak:

Yeah, so the team, when I say the team, just talk about the global research platform across equity and fixed has been collaborating for the last three years trying to figure all of this out. But a couple of recent examples. So we just had an energy sector meeting where they talked about the power bottleneck and understanding the entire supply chain. We've had cross sector teams from technology and cap goods talking about the interconnection between the CapEx from the tech companies and how that impacts companies in the cap goods space. And then literally this morning we had kind of a firm-wide open discussion really talking about all of the news that's been happening, our thoughts about AI data center CapEx and how it's not only impacting companies from revenue, but also the next derivative, which is which companies in the average S&P 500 are starting to see the benefits of AI.

Sean Kenney:

So if you think about the CapEx build out, we've talked about we're in this AI build out phase where essentially creating the capacity for AI, and at some point we'll transition to needing to see adoption. But if you think about AI as a growth investor, thinking more specifically as an investor in your portfolios, how are you thinking about this space and the build out phase and the CapEx phase for now and in the next few years?

Brad Mak:

So let me just put some numbers on it. So at the end of this month, we're at the three year anniversary of when ChatGPT was launched. This year we'll do... The hyperscaler companies will do about $400 billion of CapEx, which is expected have had over 60% growth. Next year is expected to be 40% plus growth in CapEx. So that has tremendous impact across the supply chain. I think there's been a big debate on the magnitude and size of the CapEx relative to the revenue, and we can talk about that. So I think we're in year three of what's going to be a five to seven year build on the CapEx. So we're thinking about the companies that benefit from the build out and then transition to the companies are going to benefit from the AI adoption and usage.

Sean Kenney:

So our global investment strategist, Rob Omita, often talks about we are putting a lot of investment into AI capacity, and the question becomes what is the price per unit you can get for AI adoption? And the pricing seems to be coming down and you look at enterprise adoption, consumer adoption. How do you think about AI adoption? Do we need to see AI firms get consumers to pay? Is it an enterprise play? Is it both? How does this all play out?

Brad Mak:

Yeah, that's a great question. So I think the biggest debate probably for the last couple of months in the market and CNBC has been are we an AI bubble? So in 2023, OpenAI had about a billion dollars of revenue. If you fast forward two years, OpenAI is projected to do somewhere around 12 to 15 billion of revenue. The next largest AI company is called Anthropic. Their main product is used for engineers for coding. They're going to do somewhere between 7 and 10 billion of revenue. And then there's a longer tail of private companies that are replacing labor through agentic workflows, and that group will do about 3 to 5 billion.

So we're sitting here in 2025 with about 30 to $35 billion of AI revenue that literally did not exist two years ago, and that's against a denominator at least for the hyperscalers of 400 billion of spend. And we think that that 30 billion is going to go much higher over time. It'll be hundreds of billions of dollars. So that's the framework today, is the spend going to be matched with enough revenues and profits, and that's the big debate, which we don't have an answer yet today. But we'll tell you anecdotally, we are seeing across industries, healthcare, legal, financial services, average companies in the S&P 500 are starting to move from the experimental phase to the usage phase in getting a real return.

Sean Kenney:

Yeah, I mean I can say personally and I know you as well, I use AI in my daily life. Now how much do I pay for it, I'm not exactly sure, but I know I use it and there's a use case for it. We're obviously experimenting with it within our four walls here at MFS, and not only in the business, but as an enterprise user across the investment platform. So there's clearly adoption happening and use cases being implemented at different levels across different organizations. Matt Doherty, our software analyst, made the point that on the enterprise side, a big part of the opportunity to capture revenue is displacing labor. And how important, in your opinion, if you look at it, zooming out as a growth investor, how important is it to have labor displacement be part of the formula on the enterprise side?

Brad Mak:

So if you think about global software spend today is about a trillion dollars. The labor pool is multiples bigger than that in the US and globally. So the $5 billion of revenue that I said is coming from all these private AI companies is 100% labor displacement today. So a couple examples. So in the legal profession, there's a company called Harvey. It's basically just automating a lot of legal workflows, which is either replacing or augmenting a first or second year legal associate. You mentioned just on the consumer side, so there are a couple of companies that are enabling physicians to literally record a doctor-patient interaction, upload that into an electronic health record.

So I went for my annual checkup, my doctor did that, she's like, "It took 50% of my day typing in notes away." They're doing medical diagnosis. And then in the finance we're seeing it, MFS uses a product called AlphaSense internally, it's augmenting our research process. We just met with that company. They're telling us that the banks that are using it are now saying, "Hey, what about not having to hire as many first year investment banking associates?" You are seeing labor displacement. I think that's just going to continue over time. It may not necessarily mean a ton of layoffs, but it's just going to be that the human capital you have now is just going to become more and more productive.

Sean Kenney:

A few episodes ago we were talking with Matt Scholder, who is a analyst on the pharma side, he's also our co-chief investment officer, and we talked about how it's unique data sets, companies that can apply AI to unique data sets that will likely be the long-term winners, and that actually the models themselves aren't necessarily going to be that differentiated into the future. Do you share that view? Do you have any thoughts on that?

Brad Mak:

Yeah, so on the enterprise side, the application is really taking these frontier models, putting your own data into it, and then driving value out of it. I do think where these models are pushing towards is trying to get right now PhD level talent for solving math, science, chemistry problems. So that's going to unlock a whole new set of use cases. So I think it's a combination of having proprietary data pushing the envelope as a couple of the players want to get to artificial super intelligence, and then you can just do really, really very deep valuable work at the leading edge. Again, each company will take that and use their proprietary data.

Sean Kenney:

So as you think about this build out phase, moving into adoption phase, how do you see this translating into the broader economy? Are there signposts that you're looking for or signals that we should be looking out for?

Brad Mak:

Let me go back. So you'd asked about the consumer side. So what we see as a consumer today would be apps like Google's Gemini, Perplexity, ChatGPT. We've already seen the breadcrumbs of where this is going. So there's one part where consumers are paying a premium for a pro subscription to get a stronger, more robust language model.

Sean Kenney:

I think that's what I have, but I don't know.

Brad Mak:

Okay, well if you get $20 a month on your credit card statement, that's what it's for.

Sean Kenney:

I'll take a look.

Brad Mak:

So then the next part is introducing advertising into that agentic search. So when we search for, "I need to plan a birthday for my 13-year-old son," it'll give you a plan, but it just makes sense, they'll start to introduce, these are the 20 things you need to buy. Cake, covers, balloons, etc. And the extension there will be, why don't you just buy that within the app? So that creates a whole new set of questions for the e-commerce supply chain, the search supply chain. They're eventually going to want to be able to book travel and hotels and restaurants. So I'll be very market-spanning consumer side. And then on the enterprise side, we just talked about a bunch of use cases. I think that'll continue.

Sean Kenney:

So when you think about growth investing, AI is really the topic de jour and is driving a lot of the growth and the market concentration that's in the market. What else excites you in the growth space outside of AI?

Brad Mak:

So there's like all of the AI CapEx and then the use cases, but let me just comment on a couple beneficiaries that are outside of just the ones who are spending. So we are already seeing the advertising get better and better. So these are companies, and think the social media space, where the engagement numbers are going up, the monetization is going up. If you think about companies that do streaming video or streaming music, they're already talking about the cost of content generation is going down. So that just means you're going to see lower costs and more content being created across video, movies, music. So that's going to drive higher engagement.

And then if you think about just outside, where are some interesting areas of secular growth? If you think even in something like consumer staples, historically not a very growth the industry, but they're idiosyncratic pockets of the market that are growing faster. So the tobacco industry is going through a huge shift from tobacco to smokeless products and that's driving acceleration in that whole industry. If you think about something like the energy drink category, that category has gone from what you would buy at 7-Eleven to really expanding the market to health and wellness and broaden the market. There's a lot of innovation going on in the healthcare sector, in medical devices, pharma, life science tools. There's a lot of interesting things happening in the commercial aerospace and defense. There's a lot of broad-based growth outside of just the narrative around AI.

Sean Kenney:

And talk to me about valuations, because I think the narrative is these stocks are incredibly highly valued in relative history. Is that your view? What do you think from a valuation perspective on the growth side?

Brad Mak:

Yeah, so if you exclude one car company, the MAG 6, ex that one company, trades somewhere between 20 times and 35 times forward earnings. Just as a context, Cisco peaked at over 120 times earnings in the late '90s. And then if you think about companies in consumer staples that are more grocery type, those companies are trading at 40 times plus earnings for much slower growth. I don't think we have a valuation bubble here. I think the market is more worried about or asking the question of how long does this CapEx cycle last? So it's really a duration question versus a valuation question. I generally don't think they're overvalued where we have a valuation bubble on these set of stocks.

Sean Kenney:

So as a growth investor, duration matters and you think about duration, I know, in your portfolio. As you look at the build-out cycle, and I know we're talking about getting into the adoption cycle, which is a new phase, but in the build-out cycle there are a lot of bottlenecks. A huge amount of investment has gone in. It's creating bottlenecks and some predictability into the future of where the companies that'll benefit from those bottlenecks and where that spending will go. Can you spend a minute talking a bit about that because that gets to some of the duration visibility?

Brad Mak:

So one thing that we just talked about this morning across all sectors was a lot of these bottlenecks, I'll name a couple. So one is just human labor to do the construction, engineering, and build-out of the physical data center shells. We're in a labor shortage,.so that prevents building too much all at once. It stretches the cycle out over a number of years. Other things like the components that go into data centers, the gas turbines, energy, so natural gas is one input, but we are short nuclear relative to China. So you add all those in, it extends the duration of the cycle. Doesn't mean we may still hit an overcapacity at some point, but it is smoothing out and extending the duration because of these things you just wouldn't think would be a bottleneck, literally putting people on the ground digging holes for the data centers.

Sean Kenney:

So I want to talk about two things that are risk related before we wrap up. The first is I know you and the investment team do a lot of pre-mortems on imagining if something were to go wrong, how would we position, thinking about risk from a variety of different perspectives. Talk to me about how you and the investment team are talking through this potential AI bubble. So much of the market concentration is driven based on the trade for AI, whether it's the build out or the adoption cycle. How are you and the team thinking through that, thinking about pre-mortems and positioning for the potential what-if scenarios?

Brad Mak:

Yeah, it's a great question. We actually just talked about that this morning. I've been spending the last month or so writing that pre-mortem if and when. So the bubble can pop in a variety of ways. The first would be a demand side issue where the growth we thought from these private companies maybe doesn't come to fruition, and that creates a domino effect because the whole financing of the AI data center build out is kind of dependent on these companies raising more and more money. And even if you just look at this week, that's starting to unfold a little bit, some market concerns around there.

The second would be just a mismatch in demand and supply, where maybe the demand and the revenues come, but it's in 2032, not 2030, so we do hit an overbuilding capacity glut and that could cause some disruption. And then the third would just be some existential shock or something happens where it just creates disruption, it shuts down the capital markets, shuts down the credit markets and overall fear and a de-risking. So all of those are on the table. I think the ones we're most concerned about would be a demand side slowing down because that would be the most critical one that would drive all the estimates for the CapEx build out in the revenue.

Sean Kenney:

You touched on the funding piece, I just want to spend a second on that. So talk to me about the funding cycle, because there's a lot of conversation in the news about the circular nature of the funding cycle and the customer financing that's happening. What's your view on that?

Brad Mak:

Yeah, so there's a lot of commentary on the nature of the circular financing between all these players. At heart of it it's vendor financing, so it's nothing new. I think it's happening because the very large companies are reinvesting their cash flow back to strengthen the ecosystem. So that's one thing you have to keep an eye on. The second is we've been seeing a lot of news around debt financing going in to fund this and the complex structures that the private credit players are partnering with the hyperscalers. When you take a step back, and our fixed income team just gave an update this morning, debt financing is only 15% of CapEx for data centers this year. So while you could have complicated structures or something not work out, I don't think it's going to be systemic to the whole ecosystem, but these are all things we're monitoring vigilantly to make sure that the demand side's there and then that there just aren't enough... We want to make sure there's not too much leverage in the system and financing is available.

Sean Kenney:

Great examples is that we're having fixed income analysts on your team, on your hip through this is helpful, right?

Brad Mak:

Totally 100%.

Sean Kenney:

Yeah. So the second risk question has to do with portfolio construction. So you're managing to a growth benchmark that is increasingly, in fact the most concentrated it's ever been in the history, and yet your mandate is really a broad-based growth portfolio. How do you think about risk budgeting across multiple industry sectors when you're competing against such a highly concentrated benchmark?

Brad Mak:

Yeah, it's a great question. So we try to do it bottoms up, finding the best stocks in each industry, but we generally try to stay within plus or minus 5% of each sector. And then we do look at which stocks, what percent of their revenues are tied to AI data center, which ones have exposure to the various public and private companies, and what's the risk on financing all of that. So we kind of do it at the portfolio level, the stock level, and we're just making sure we're not getting too over our skis one direction or the other.

Sean Kenney:

Yeah. Okay, well, let's close out with an outlook. So we're going into 2026. What are you looking out for? What's on your radar as you look at the growth space in 2026?

Brad Mak:

Yeah, so I think 2025 was really the year of the AI data center build out. Servers, people, steel, all the equipment that went into it. And I think we're seeing these green shoots of these enterprise and consumer use cases really start to get traction. I think next year we really need to see all of that continue at a high velocity. If that happens, you're going to get more and more of these positive return on investment case studies from companies across the economy. And as that scales, that should provide support and rationale for all of this CapEx. But that's what the market is probably the most concerned about and taking a look. So that's probably what the most important driver is for next year.

Sean Kenney:

And that's where we're seeing a little bit of the volatility now, is that right?

Brad Mak:

Yeah.

Sean Kenney:

Okay. So let's summarize. We talked about a lot through this. The first thing is, and it might be the most obvious statement, but that AI truly is a transformational technology that will permeate through the entire economy. Is that fair?

Brad Mak:

Yep.

Sean Kenney:

The second is that we are at a critical point in the cycle. We're going from the build out stage, not to say it's over, but truly a build out stage to an adoption cycle. And the things that we're looking out for into the future are a bit different. Is that fair?

Brad Mak:

That's fair.

Sean Kenney:

And then the third is that, and I don't want to put words in your mouth, but we're optimistic about that adoption cycle, but we're staying hyper vigilant and it's really thinking about the rate and duration of growth and thinking about the companies that will benefit from the bottlenecks and capture the demand from those bottlenecks. Is that fair?

Brad Mak:

Yeah, that's fair. So I'd say over a long-term, very optimistic on AI, it's very real, and it's just managing the nuances. A, this is moving so fast. Literally the market will view companies as an AI winner, loser, and it'll flip flop based on some technology leap. And then second, we're just monitoring some of these yellow flags we talked about, the debt financing, the circular financing, but really on the demand side. And I would just say we really will continue to leverage the global research platform, because having these touch points across sectors, across equity and fixed income help us really evaluate as the facts continue to evolve.

Sean Kenney:

Okay. Well, I want to close where we started, which was with your running. What is the hardest race that you've run so far and the biggest lesson you took away from it?

Brad Mak:

So I wouldn't say this is the hardest, but it's probably the one where I had the greatest fear. So the last five years, there's been a new event called 29029, which is like Everesting. So you could hike stairs, you could ride a bike, but the idea is you climb enough elevation where you get to 29,029 feet, which is the height of Mount Everest. So I did one in Colorado two summers ago, and it's about a mile up and you have to hike it something like 18 times. You hike up, take the gondola down. I think about four o'clock, it's 70 degrees outside, we're hiking up. You have aluminum poles, you're in a short sleeve shirt and shorts, and it goes from 70 to 30, like that. So rain, hail, lightning, and you just feel completely exposed. You're far away from shelter. So I think just recognizing things can change on a dime and things can be out of your control and you have to stay calm and be prepared was probably like... That was hard just because there was nothing you could do to escape the situation.

Sean Kenney:

Right, right, yeah, interesting. Well, it's been really great to talk to you about the environment. Thank you for all your background and perspective and appreciate you being with us.

Brad Mak:

Thanks, Sean.

Sean Kenney:

And thank you for listening to All Angles. If you enjoyed this episode, subscribe so you don't miss any future episodes. Until next time, be sure to consider your investment decisions from all angles. The views expressed are to those of the speaker and are subject to change at any time. These views are for informational purposes only and should not be relied upon as a recommendation to purchase any security or as an offer of securities or investment advice. No forecast can be guaranteed. Past performance is no guarantee of future results.

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