The Canadian Investor - 50 Ways to Invest in the AI Revolution - Part 1

Episode Date: September 22, 2025

Simon and Dan kick off a two-part deep dive into 50 Ways to Invest in the AI Revolution. From the obvious giants to under-the-radar plays you may not have considered, they explore how AI touches everything from chips and cloud to healthcare, cybersecurity, and even utilities. Along the way, they drop dozens of tickers and ETFs across multiple subsectors—some household names, some you’ll be hearing for the first time. If you’ve ever wondered how to get AI exposure beyond just NVDA, this episode is packed with ideas. Tickers discussed:Semis & equipment: NVDA, AMD, ASML, TSM, AVGO, ARM, MU, AMAT, SMH, CHPS.TOHyperscalers / platforms: MSFT, AMZN, GOOGL, META, QQQ, CLOUPure-play AI software/models: PLTR, SOUN, ZXLK.TOEnterprise software with AI: ADBE, CRM, ORCL, SAP, NOWData-center REITs: EQIX, DLR Check out our portfolio by going to Jointci.com Our Website Our New Youtube Channel! Canadian Investor Podcast Network Twitter: @cdn_investing Simon’s twitter: @Fiat_Iceberg Braden’s twitter: @BradoCapital Dan’s Twitter: @stocktrades_ca Want to learn more about Real Estate Investing? Check out the Canadian Real Estate Investor Podcast! Apple Podcast - The Canadian Real Estate Investor  Spotify - The Canadian Real Estate Investor  Web player - The Canadian Real Estate Investor Asset Allocation ETFs | BMO Global Asset Management Sign up for Fiscal.ai for free to get easy access to global stock coverage and powerful AI investing tools. Register for EQ Bank, the seamless digital banking experience with better rates and no nonsense.See omnystudio.com/listener for privacy information.

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Welcome to the Canadian Investor Podcast. I'm back with Dan Kent. My name is Simon Belanger. if you're new to the podcast. I feel like we will get some new listeners here because we're going to do a deep overview of how to invest in AI, of course. There's a whole lot of different ways, but I think it's something that people have been wanting us to do. So I think we will probably attract some new listeners that are intrigued by the different ways to invest into AI.

But one thing that I found before we get started is clearly there's a lot of different ways. some ways, I think, that I didn't even fully realize that there were some companies that were actually some AI plays that maybe not full AI plays, not pure plays, but were still AI plays that I didn't realize that they were. Yeah, could you argue that, like, has a new piece of technology ever touched, like, so many industries? Like, as we were going over this, the notes kept piling up and piling up because, like, every, Almost every segment of the market has some sort of exposure to artificial intelligence. And I mean, even if you look to something like utility players, which a lot of people really wouldn't think of, but we'll get to it obviously when we talk about them.

But I mean, this stuff requires a lot of energy. Yeah. Yeah, exactly. It does. And we'll also talk about some, you know, well, there's a section on healthcare too. Yeah. How healthcare is really using AI, for example, to make diagnostics better, developing new drugs. So there's all these different ways that you can actually invest in AI without investing in Nvidia, for example, which we will be talking about Nvidia.

Like, we'll talk about the obvious ones as well. But like, my view here is that AI will make us more and more productive and efficient. I think most people will agree. Some might disagree that AI. as a high likelihood of being as transformative or even more than the internet has been. But so far, I think it's a pretty safe bet to take. And as an investor, my goal is definitely, it's to increase my purchasing power. Like, that should be your goal too.

Like, at the end of the day, there's one reason you invest is to increase your purchasing power. Because if that's not the case, then just go put your money at EQ Bank and, you know, collect 2.5% and interest which is higher than most competitors out there go ahead and do that you will slowly bleed purchasing power away but it's going to be probably the least worst option if you're looking to put cash that's how i view things when i invest i think that's how you invest as well right yeah want to increase your purchasing power yeah so like right now i think you have to be living under rock to not say that the obvious AI names are really hitting sky high valuation and And that's not just for the big, well-known publicly traded companies.

I mention Nvidia, but you can talk about all the hyperscalers, the Googles, the meta, the Microsoft, and so on. And if you start looking at outside the public markets and based on Pitchbook data, it's pretty common to see AI startups trading at 20 times EV to sell. And EV is just, if you're kind of new, it's just the market capital. and then you add in whatever amount of debt they have or you subtract the cash if they don't have any debt. So it's just a metric that's pretty common you use. You can always all use sales to their price to sell, which would be the market cap compared to the sales.

But 20 times plus EV to sell and upwards of 50 for AI startups is extremely rich. Like I know a lot of people might not be familiar with the venture world, but it is its nosebleed to. say the least. And you're also seeing multiple expansion for, of course, AI-related public companies. We're also seeing investors get extremely excited for companies that are AI-related based on revenue growth expectations. We saw that happen just last week with Oracle. Like a lot of the hype around Oracle is revenue growth expectations, which, you know, I'm sure they have a,

good way of projecting that. Of course, they have these backlogs that should result in revenue, but they still need to execute and doesn't mean that they'll be profitable. So you're seeing all these things and you're seeing more and more investors that are less or the market that's less focus on profitability and just more revenue growth or even just the story, the story behind the company. And I've been, I've had people share names with me that have little to no revenue, but there's a nice story behind it. The reason I wasn't to mention all of these things is just to emphasize how much hype there is

in the market right now around AI. And we'll be talking about waste and invests, but it's just, I just wanted to remind people that because even if we can all agree that the internet will revolutionize or the internet revolutionize the world, I know some of you may be a bit too young, but the internet was, I think, invented back in the 1970s. In 1990s, you started seeing a bit more the adoption,

but you saw some massive hype in the 1990s and you saw companies that actually were trading at ridiculous valuations but were profitable. Microsoft is one that comes to mind and it took decades until those investment if you invested during the hype actually became positive and I think that's really important because there's really a real risk that investing in a lot of the AI plays I will be talking about will end up being a poor investment, even if the fundamental of the company continue to be strong and improved over time, because you're just paying too high evaluation. So for example, say you're paying 50 times sales to EV for a company today. And we'll just focus on sales right now. Obviously, there's other kinds of metrics. If you're looking at more

profitability, you can use price earning, price to fees cash load. These are more profitability metric. but there's a lot of hype and you think that the true value of this company is around 10 times sales to EV, which is not cheap to say the least, but you think that's a true value. In order to get returns of around 9% per year, you would need the company to grow sales at a compounded annual grade of 50% per year over the next 5 year just to get around 8% to 9% in returns, if you're just looking at that price to end, that sales to EV the number because there's a multiple compression. So the sales really have to catch up to counterweight the massive valuation that you're paying for right now. So I know it's a simplified way, but I think it's important for

people to understand that when valuations are really stretched, that's usually when there's the most risk in an investment. And of course, course now we're talking about AI. But I wanted to preface this because there is a whole lot of hype right now. And I think it's really important that people know that before they put too much money in AI. And I think one good way to counterag that is just making sure you allocate appropriately and your position sizing makes sense and you factor in the risk within those position sizing because investing 20% in a company versus 3% in the same company, it's going to be very different risk profiles. Yeah, so I think we went over this on our market top video.

I think it was a few weeks ago, and Goldman Sachs has a speculative trading indicator, they call it, and they kind of track like a certain amount of speculative activity based on particular metrics they look at. And one of the metrics is companies that trade at more than 10x. EV sales. So this would be publicly traded companies, obviously. So when we have those startups, they wouldn't really include this startups typically trade higher. But if you're having an institution like that stating that anything over 10x EV sales would be highly speculative and then you have some of these companies trading at 20, 30, 40x. I mean, there's, yeah, there is a lot of growth priced in right now because obviously a lot of this guidance and a lot of these outlooks, it's

publicly available information. I mean, the market is going to price that in generally, like immediately actually. So in this situation, you kind of need the story to work out. And the story right now is there's no doubt that AI is revolutionizing a lot of the things we do. But I mean, the profitability is the one thing that is probably the most up in the air, like how profitable will it be? And when we, especially when we talk about the hyperscalers eventually, like how much money they're dumping into AI infrastructure is just crazy. But yeah, I mean, often people feel safest investing in a market like this when in fact it's the riskiest part of the market to invest in, but it feels the safest because you buy a

stock today and it's up 50% in six months or a year. But when valuations get this high, risk actually goes up, whereas, you know, during bear markets where generally people are the most scared to invest often is the best time. So yeah, I mean, there's no doubt that this industry is going to grow. For me, it's just the profitability side of things, like how efficiently will a lot of this capital be invested. If people say they know they're kind of lying, like nobody knows really how truly profitable be. Because like you said, in the 90s, I mean, the internet was a big thing. People were buying. People were We're paying absurd valuations for this growth, growth that never materialized for,

well, what was it, 10, 10, plus 10, 15 years. Yeah. Or we're paying crazy, just crazy amounts just for a good story. Yeah, right? I think pets.com is one of the one that is most often cited here. But I think it's just a good reminder that even though it may really revolutionize and you really believe in the time. technology, it still doesn't mean that it's going to be a good investment. And I think that's

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and there's other stuff like learning duolingo style education lessons that are completely free. You can search up Blossom Social in the App Store and join the community today. I'm on there. I encourage you go on there and follow me, search me up, some of the YouTubers and influencers and podcasters that you might know, I bet you they're already on there. People are just on there talking, sharing their investment ideas, and using the analytics tools. So go ahead, Blossom Social in the App Store, and I'll see you there. enough of that anything else you want to add it before we get started here for some actual

go by i don't know like sub sectors would kind of be the way to name it no i got nothing else okay so the first one probably the most obvious one semiconductors slash hardware related to the to ai so that's more those are often described as the picks and shovels of AI because you know the gold rush, the biggest, you know, there's a saying that no one really made money during the gold rush except those selling the picks and shovels. So yes, they will, whether AI becomes big or not, as companies keep buying Nvidia GPUs, I mean, Nvidia is selling those GPUs. So whether, you know, those GPUs end up doing something great in terms of AI, who knows, Nvidia doesn't really care at the end of the day.

They're still selling those GPUs right now. And that's the hardware on which AI runs. So the figures I was able to find is that semiconductors global market reached a bit more than $600 billion in 2024. And PWC, one of the big accounting firms, is forecasting that it will surpass $1 trillion by 2030. And to be fair, that's more than just AI, but a big portion of that clearly is related to AI expenditures.

Semiconductor demands should remain strong due to things like electrification and the fact that they're putting chips in almost everything now, whether it's AI or not, right, related. So one subset that should also see some strong demand according to PWC and it's hard to not agree is self-driving vehicles. And of course self-driving, there is going to be some AI in there as well. so it kind of goes back and touches everything. But some of the names here that are well known in the AI space,

and I think you have a few to mention too, but feel free to add them if I missed any here. NVIDIA and AMD, ASML. So obviously, NVIDIA making the GPUs, AMD in that same space as well. They're designing those ASML. They manufacture the machines that are used to make those semiconductors to keep things simple for people that are not. familiar.

TSM, Taiwan semi-conductors, they are the ones that actually manufacture the chips with the machines from ASML, from designs, from companies like Nvidia and AMD. I know it's a bit, can be a little bit complex, and you hear a semiconductor, but they are, they are different places in the semiconductor, I guess, life, life of a semi-cor creation. Life cycle, yeah, the assembly line. assembly line exactly there's also broadcom ticker avgio they design different types of chips that play a role in AI including networking chip wireless chips rob pan chips

they also work with hyperscalors to design custom AI chips arm is another one it doesn't manufacture or arm it doesn't manufacture chip but licenses its design an intellectual property which is used by companies like Nvidia Apple and Qualcomm and there is really one big question for these companies, in my opinion, is can they grow quickly enough to justify today's valuation? That would be the biggest question here. And anything you want to add, aside from that, I'll also provide an ETF idea of people are just looking to do

the basket approach, which we'll try to do for most of the subsectors here. Yeah, I mean, I guess all I would say for this is, like, I would probably view that. this as what I would say is most likely to succeed or at least be steady in the in the realm of AI and the reasoning for this is as you had mentioned they're kind of I don't know how to say at top of the food chain I guess I mean no matter how profitable it is for somebody developing an app or a piece of software or something I mean they're going to buy the semiconductors these companies get paid before all of that happens I mean obviously if AI KPEX were to dip or slow down I I mean, obviously, there would be lower demand from these companies as well, but it wouldn't really evaporate because like you had mentioned, they're putting chips in absolutely everything.

These aren't necessarily AI pure plays. Obviously, a lot of the run up in valuation over the last year or so is related to AI. Like, I don't get me wrong, if it were to slow down, these companies would be impacted quite a bit. But in terms of other companies, I mean, there's so many different types. I mean, you have micron as another one I can think of. I think they trade under the ticker MU. So they provide a lot of the, like, memory-based chips that these, like, LLMs and AI systems use to store the data or even have something like applied materials, which would kind of be on the, like, the ASML side. They're kind of above in the fact that they kind of supply equipment needed to actually build these.

So, I mean, yeah, these are the picks and shovels plays. And as you had mentioned, I mean, in a gold boom, the first ones that get paid are these types of companies. while, you know, farther down the chain, there's a lot of boom and bust here. But yeah, that's kind of what I, my thoughts on these companies. Yeah, and if you're looking for an ETF idea, the VanX semi-conductor ETF, ticker SMH, would be one to consider here. Again, all these companies, we're just providing ideas. Make sure you do your own research.

I know we talk about, we have a disclaimer, but, you know, some we know better than others, and whether they're good investments or not right now, it's, you know, it's not for us to say you need to make your own assessment for those looking to get the tickers we'll try to say the tickers as we go if you miss them that's fine we'll also have most of them if not all in the show notes so the tickers of the stocks and etf discuss so if you're not sure just go to the show notes and you'll have them there because i know you know a lot of people want kind of actionable ideas or ideas to to be able to you know get exposure so we'll be saying a a whole lot of names during this episode. So make sure that you take note for the ticker and again, do your own research for all of these. Anything you want to add before we move on? The only other one I would say is if you're looking for a Canadian

ETF, Global Exx1 Chips, I think it trades under the tickers, C-HPS. So it's kind of, it contains much the same as a lot of these, like US semiconductor ones, but it just trades in Canadian dollars. I do think they have a US dollar version as well, but I'm not 100% sure on that. But I know a lot of people listening to this are obviously going to want to keep the currency in their home currency. So that's one of the more prominent Canadian semiconductor ETFs. Yeah, and a lot of these names, too, I think that's good you mentioned that,

because a lot of these names will be available in Canadian dollars on the Neo Exchange. Yeah. So at a smaller cost than the share cost in the U.S., So for those who want to buy the companies directly or, well, they're not directly. They're still CDRs. CDRs, yeah, exactly. But for those who want to like get exposure to each specific company or maybe they have two or three in mine, but you don't have a big enough portfolio to say, oh, I'm going to put money in NVIDIA or Google or whatever it is,

you can always look at the NEO exchange. So they have some, most of the big names, they have them at a lesser dollar value. And it's not direct ownership, but you, it's pretty close. Yeah, it's just the, the currency hedging is really the only difference. Like, I think it's CIBC or whatever, kind of holds the shares. Yeah, I believe so. Yeah. Yeah, so they'll hold the shares in trust and then kind of issue units that you can buy in Canadian dollars.

And I think there's just like a 0.6% annual fee for currency hedging, which kind of stops those fluctuations in terms of currency, which can be a benefit or a detriment. But, yeah, for those, just make sure you understand kind of the hedging aspect of it. Yeah, exactly. Now, the next one that probably people think about when they come to AI, so the hyperscalers. Now, it's a term we talk about a whole lot. So I just wanted to define a little bit how it came about the term hyperscaler. So back when cloud computing started taking it off, I think it was like late 2000s, early 2010s,

companies like Amazon, Google, Microsoft, and obviously. META built these massive data centers that could expand almost endlessly to handle more and more demand. Traditional IT on the other hand scaled more slowly, but these firms engineered their system to grow very rapidly and efficiently, and that's why they became known as hyperscalers. And you'll see them in financial media. We've been guilty of that as well. And the podcasts, we'll refer to them as hyperscalers. But I just wanted to mention that because I feel like a lot of people don't know how they got to that name.

they're just like, yeah, there you go. Yeah, there you go. A little bit of fun fact here. And I know it's a word that's thrown around a bit, but I think of them a bit as the utility providers of AI. That's kind of how I may mean, do you agree with that? Yeah, yeah, yeah. Okay.

So they supply compute, storage, and platforms to consumers and business alike. In many cases, they integrate AI and those platforms, think Microsoft Office, Gmail, Instagram, YouTube, AWS. The companies in the space are the very well-known names. Think about the mega caps. A lot of them would be in that like, well, one trillion dollar club. I think they're all in there now. So Microsoft, Amazon, Meta, Google would be some of the names in terms of the hyper-scalers.

One of the big draws here is that these companies are very, very profitable and are growing very rapidly, despite their... gargantuan size. Yeah. They're still growing very rapidly. And there are some risk associated with these companies. I think it's important to highlight that. First, antitrust issues.

We saw that recently with Google. So it ended up being somewhat favorable to Google, although, you know, there are some things that they'll have to do. The law of big numbers. Can they continue to grow this quickly when they are already so massive? I mean, people were saying that five, six years ago, and they've continued to grow this quickly. But at some point, the law of big numbers does catch up. And can they justify their valuation going forward? So that's something that we alluded when we did our introduction

is they still have some pretty steep valuations and lofty expectations too going forward. So especially if you're looking at valuation on a forward-looking basis, make sure you keep that in mind because when expectations are sky high, you know, the market will put more of a premium on that, but it also means that if they miss, that's when you get some big drawdown. So something to be aware of. And I guess the last question here is, will the massive amounts of capital expenditures, so the spending, the investments that they're doing in all this infrastructure, all these Nvidia chips they're buying, all this invasive. meant will it actually be well spent or we're going to look back five 10 15 years from now and be like

wow boy did they waste a whole lot of money on all of that so that is the big thing and if you're thinking oh there's no chance for that last one just look at meta look at how they their reality lab spending as done and sure it could still turn around them but they've spent spend billions and billions and don't have much to show for it so far. So there is always a risk when you spend that much money, no matter how good your vision is, you never know whether it comes true or not. Well, I remember what the market did to meta after something like that,

after they like said they were going to spend that much money? Like the stock, obviously it's recovered, but the stock absolutely bombed, yeah. And I mean, I think the key difference I see here is like in terms of artificial intelligence. I mean, you're kind of investing in companies with massive, massive profits. So, you know, a lot of these companies like Alphabet, Microsoft, they're making large scale bets on AI. But a lot of their capital expenditures, and this will be a difference from what we go over next, which would kind of be like the pure plays. I mean, a lot of their KPEX is just, it's not funded by

debt or equity. It's just cash flows from their core operations. Like these companies make a lot of money on their businesses that don't even really utilize AI. I mean, when we look to something like alphabet or meta, it'll be mostly advertising, things like that. And so, I mean, if you think about it, if this capital were to kind of be ill spent in regards to AI spending, it's not like these companies are in dire straits or anything. I mean, they're still going to generate a ton of capital from core operations.

It'll just kind of be ill-spent money, which again like it's not a small thing to waste hundreds of billions of dollars but in the end they will fall back on the core business models which are still growing at a double digit pace which is actually why I think they can continue to grow this quickly when they're that big I mean when you're generating this amount of cash flow it becomes very easy to be able to invest tens of billions of dollars into new growth opportunities with like barely straining the balance sheet which is pretty crazy. But there's also kind of the element that a lot of these, and I don't know too much about the chips that they are building, but a lot of them are building their own chips kind of to remove the reliance on, you know, the companies we talked about before, those semiconductor companies like NVIDIA.

I would imagine this would help improve margins, which in turn would improve profitability. And again, they do have the cash flows to do it. And yeah, I mean, I think the biggest risk here, like a very quick example of the type of risk is you have all these. companies, spending a ton of money on building out data centers. I mean, what happens in five or 10 years if a lot of these are underutilized, like they aren't keeping, you know, they're building up all of these and a lot of them have to outsource some of them too because they cannot keep up with demand right now. But what if they overspend and the demand is and they're down the line? Like that's kind of the risks here with all of this spending. It's not guaranteed to turn into profits by any stretch. And yeah, I mean, You pulled up the chart here of Microsoft's capital expenditures.

Exactly. It's mind-boggling. So it's just essentially the CAPEX, obviously, it's money going out that's being invested. So it's a negative amount that's showing here on fiscal.a.i. And, you know, it's a company that's always invested pretty heavily in capital expenditure. You were looking prior to like 2020, the higher end, it was increasing, but, you know, $10, $12 billion. Now, I guess it would be the last 12 months, you're looking at $65 billion or close to $65 billion capital expenditure for Microsoft up from, let's say, $8 to $10, $12 billion just five, six years ago. And it's been a steady increase.

And then if you want to look at Google, well, it's almost the same chart. Not quite, but you see that same kind of thing where KAPX is just going through the roof. If you look back at, you know, six, seven years ago, it was in the 20 billions and now you're looking at their last 12 months and it's at 67 billion. And they keep making announcements and projections that it's not going to stop anytime soon. Yeah, no, I don't see it stopping anytime soon. But again, the key difference here is you look to a company like, say, Alphabet who's spending $66 billion a year while they generate that in free cash flow. every year where you have a company like Oracle who generates around 11 or 12 and is planning to spend 35. You know what I mean? So there's there's kind of a big difference in that regard. And

I mean, if you look to these companies, they're spending, but they're not kind of breaking the bank to spend, I guess is what I would say here. Because they just, their core businesses are just so profitable. Yeah, exactly. And they're still generating free cash flow, despite. all that spent. Yeah. So, like, obviously the free cash flow has gone down because the amount of spending they're doing. But if I'm taking here, Google again, or Alphabet, their free cash flow went from 2024, around

$72 billion. And now the last 12 months it's dropped to $49 billion because of that increased spending. So it's still, they're obviously able to afford it, but it still becomes a question whether that money will be well spent or not. So, yeah, because if you think like as shareholders, you're entitled to a chunk of that money, right? So if they go and spend all of it and it's ill spend, obviously as a shareholder, that's, that's really not all that beneficial to you, which is, I think it's a big question moving forward is how profitable this spending will be. And we're already seeing some major companies who are integrating AI systems, especially in the healthcare situation. Like they're saying it's pushing positive ROI like a year after implementing.

So obviously those systems are a lot different, but there's definitely questions. Okay. So now in terms of ways to play it, so probably one that comes to mind, but it's going to be a broader approach, but these names are definitely heavily weighted because it's market cap weighted QQ. So any kind of NASDAQ, ETF, you'd have quite a bit of exposure. Of course, you'll have Nvidia, you'll have other names. So it won't just be these. But another one that would have some other names would be, Global X cloud computer ETF, ticker CLOU, would be another one. Again, these are just ideas. If you do some research, you'll be able to find some other ETS, but we're just trying to get some ideas for people to, you know, different ways to get some exposure to it. Do you keep hearing about these all-in-one ETFs lately?

Well, I have some exciting news. BMO ETFs just cut the fees on their flagship all-in-one ETFs to 0.1 5% making them one of the lowest cost options in Canada. That's right, more value, same smart diversification, all in a single ETF. Whether you're just starting out or simplifying your portfolio, BMO all in one, ETFs make it easy to invest with confidence. Just Zed it and forget it. Considering ETFs like ZEQT, BMO's all equity ETF, or ZEDGRO, BMO's growth VETF. Calling all DIY, do-it-yourself investors, Blossom is an essential app for you. It has been blowing up with now more than 50,000 Canadians plus and growing who are using the app. Every

time I go on there, I am shocked. The engagement is amazing. This is a really vibrant community that they're building. And people share their portfolios, their trades, their investment ideas in real time. And it's all built on the concept of transparent. because brokerage accounts are linked. And then once you link your brokerage account, you can get in-depth portfolio insights, track your dividends, and there's other stuff like learning

duolingo style education lessons that are completely free. You can search up Blossom Social in the app store and join the community today. I'm on there. I encourage you go on there and follow me, search me up, some of the YouTubers and influencers and podcasters

that you might know, I bet you they're already on there. People are just on there talking, sharing their investment ideas and using the analytics tools. So go ahead, blossom social in the app store, and I'll see you there. Now, we'll move on to the PurePlay AI software models. Yeah. Okay, so there's definitely a bunch of companies that would fall into this category, and they tend to be very, very, very hype.

So keep this in mind. These are the companies that you'll often hear the big narratives around. So they may not have super high revenues or they're just starting to have revenues that are growing really quickly. They may not be profitable, but investors are focused on the fact that there's a narrative or a very nice story to tell behind them. So these are the companies that, not all of them, but there's a lot of companies that fall in this bucket. And we'll give a few examples, but keep in mind that you will see nosebleed valuations. Like you will see the 20, 30, 40, 50 times sales to EV, you will see this in this space. Like, this will be more common than not because of all of the hype.

And one of the comes to mind, probably the poster child for this is Palantir, ticker PLTR. It's an AI-driven data analytics platform. There's really strong governmental adoption, specifically in defense and intelligence. Another one, I didn't even realize they had an AI play because I used to, use Soundhound for, I think, discovering songs and stuff back in the day. Soundhound AI, ticker S-O-U-N. My understanding is that they specialize in AI voice agents.

It's a customized option for companies so that companies can own their own customer interaction. Think of a restaurant if you're ordering via voice kiosk, for example, so they could use some of their solution. There's other companies, of course, and they might have. have a whole lot of upside, but again, they also have some of the highest risk profiles here. In terms of ETFs available, there aren't really specific ones that I could find, but an interesting play would be if you're looking for Canadian options, ZXLK from BMO, which is the Canadian

hedge version of the Spider-SPDR technology sector ETF, XLK, so it's the Canadian version of that. So it's pretty much a combination of semiconductor hyper-scalers and pure play AI software like we just mentioned. So that would be kind of an ETF route. Again, a lot of these ETFs will include a bunch of different sub-sectors. So keep that in mind. Yeah, I don't know if there would be like a pure play for these types of companies. But yeah, like if we looked at the hyperscalers of companies that have those core business models and are instead like kind of investing in this as an additional avenue of growth.

I think a lot of these companies are all in, like they are all in on the AI infrastructure. I mean, if adoption were to slow down or be slower than expected, the hyperscalers will probably be just fine as companies. They haven't really strained the balance sheet all that much. Core business pretty much still intact. But like when you look to a company like Soundhound, like debt necessarily hasn't been a big issue, but equity has, the company is burning through about 110 million a year in free cash flow and shares outstanding have doubled, I think over the last like five years or so. You get to a

situation where, you know, if AI is the core of the business and it doesn't come to fruition, it's, it's kind of devastating. Whereas I think the hypers, not as much definitely would still be impacted, but not as much. But then as said, like if you flipped a script and demand continues to go up and you know the software that they're developing or whatever they end up developing like the the voice tech with soundhound I don't know a lot about soundhound I did get a lot of questions when they were going through the roof in terms of price but I mean in this situation there can be explosive growth but on the 50 like the EV sales or whatever I think like 50x would be a low point for some of these companies I mean palanteer Palantiers at like 120 I think

I don't know what Soundhound is trading at, but they, like, is it? Yeah. Yeah, 120. I mean, that would be trailing EV sales, obviously. So, I mean, it depends on how much they're going to grow. But yeah, Palantir is at 115. What would? Soundhound's at 44. So, I mean, a little bit more reasonable. If you can see that. At least Palantir, it's 82 when you're looking at the next 12 months. So that's not too bad. And a little bit of a sarcasm here, but yes. Yeah, remember when we started the episode, when I talked about that speculative trading indicator and it was 10x or more, like 80x forward is, yeah, yeah, that's pretty crazy. But I'd say like these highest risk reward had probably be safe to say. I mean, in terms of, you know, returns, but also in terms of risk just because of just overall valuations, like I don't even know what a company like Alphabet would trade at on an EV sales basis, but probably not even close to a. company like Palantir? No, no, exactly. Like, I can pull up, so Alphabet, 8x, 8x, EV sales. So, yeah, it's quite the difference. Yeah, exactly.

So I think, so just to keep in mind, we're trying to, again, I think it's just an important reminder, there's a lot of hype around AI, so just be aware. I know it's very exciting, and I think we both have some exposure to it, probably more in indirect ways, but I, we just, you know, I think it's a fun episode to do, just the different ways to look at it. Now, the next big one, I'll let you take the lead for that. So enterprise software. So what kind of companies, you want to explain what enterprise software is and what kind of companies people could look at to get some exposure via those? Yeah, so like enterprise software would primarily sell tools to businesses. So a lot of these were kind of normal businesses and are now

integrating AI into their platform. Like the one I can think of right off the top of my head would be something like Adobe. They sell a lot of platforms to businesses. Let's think like Premiere Pro. You have the PDFs. You have like audio systems, things like that. And they're kind of integrating AI into their platforms to kind of fuel revenue. I guess I would say the one, the other thing is a lot of the hyperscalers would be to a certain

extent enterprise software like 365, like Microsoft's 365. Google too. Yeah, Alphabet with their whole work workspace, whatever it's called. Yeah. So they kind of like those, the hyperscaler companies kind of touch on a wide variety of the markets. I mean, another one would be Salesforce. So they kind of provide customer relationship management for businesses. So they manage their data marketing systems. They kind of construct sales funnel. Ticker, CRM. CRM. Yeah. Now they've kind of integrated AI under their platform that makes the systems easy. easier to run, but also more efficient and kind of delivers better results than humans. And in this situation, I mean, when you have these integrations into these platforms and you can actually drive more efficiency through customers, obviously retention rates are going to become stickier because they're making more money, which kind of creates a situation where you can raise prices and these companies which are now doing things more efficiently making more money

will have no problem paying those higher prices because the added functionality you put in here will help them so other companies I can think of Oracle SAP service now I'm trying to think of the I don't know the tickers Oracle what is Oracle trade that Oracle stock would be well even if we don't have the tickers just look in the show and notes. Yeah, we'll drop them there. The tickers will be there. Yeah, exactly. Yeah, and I mean, if you think of something like customer service and you imagine, like, I mean, you've heard like the traditional call center or the traditional like call in, wait on hold,

I mean, if you can construct something like that, that it can be automated through AI and a lot of companies are doing this, like they have literal AI service people that you call into and it's a voice and it kind of manages that, or something like, you know, these companies go through large scale hiring. I mean, if you can save the human element of having to go through all that paperwork in order to do so and you can instead, you know, kind of put that through AI. Like you can imagine the amount of overhead. A lot of these companies will be able to trim and then you can imagine the situation

where they will find these types of software platforms extremely valuable because they're ultimately making them a lot of money. And a lot of these companies were, Pretty prominent, like long before AI came around. I think the angle here is AI additions to a lot of their tools that will just make them become more sticky, probably expand margins, retain more customers, drive more profitability effectively. Yeah, yeah, exactly. I think the biggest thing with these companies, though, is they're, as much as they, a lot of, well, pretty much all of them are integrating it to their enterprise software is there is a real risk that there's also going to be disruption. because of AI to their businesses.

And Salesforce, ticker CRM and Oracle, I think it's ORCL. I mean, one of these things that we've seen for Salesforce specifically is that it's been struggling. Like the company has not been firing on all cylinders, and they do have a bit of issues there. So it is something you have to keep in mind that there could be some of even these larger players that do get disruptive. Because one thing that we probably forget is coding has become much easier with AI. One of the first thing AI was really good at was coding. So it is not that hard if you have a decent background in coding to build out some of your own software. Or so I've heard, like I'm not an expert in that.

But you can, yeah, it's good at coding. Oh, we used to have to hire a web developer. and now it's like I can pretty much do it all myself. I just put it into GPT and kind of ask for like functionality changes. It'll spit out the code and I can just put it right in there. I think on like the larger scale end like with larger companies, obviously the switching costs are higher. Like it is it would be a pain.

It is. Yeah. For some of these companies to like swap over. And that's kind of what Adobe had mentioned is, you know, on the higher end level, they're not, retention and use cases for their for their AI tools but once you get to the smaller end of the market that's kind of where they're where they're not I don't think they said they weren't

seeing results but they're a little more uncertain because obviously if you think of a small company like a 10 or 20 employee company it's probably not a big deal to swap to some you know a more efficient way more nimble yeah but you you have you know 20,000 employee company where they're all trained on a specific set of enterprise software I mean you're talking a ton of money to switch so it's a little trickier in that regard but yeah and they're usually longer term contracts yeah exactly so something else to keep in mind there but we'll do the one last one here and then the rest it will be in part two of the episode so what we'll do because you you did a segment pretty big on your own so we'll do data center reads and then we'll call it an

episode and then we'll continue there's about six seven subsectors left so yeah we have quite a of content so people can understand why it took us a while here so data center reits so this is another type of uh it's a type of infrastructure play data center reads on the data center so the actual buildings and leaves the space to companies it could be smaller companies that may not need like a large like they don't need a large data center or don't have the capacity to outright build it and they'll just leave the space from a data center read and maybe they don't want to use one of the hyperscaler solutions either. It can also be those hyperscalers that we talked about earlier who can't keep up with demand with their own facilities so they decide to complement that with leasing

space from data center reads. So there are different ways here that data center reads get business and could continue growing into the future. Two names to get exposure here would be Equinix, ticker EQIX or Digital Realty Trust DLR. You just have to pull up the chart of either of those company to see how revenues have progressed over the last five to 10 years to see that demand will likely stay strong for data center rates for the foreseeable future now dLR for example has seen its revenues grow at a compound annual growth rate of 11% over the last five years while equinix is sitting around 10% during that same time frame it's a really i think it's under the radar play that's still pretty direct to AI because it gives you that exposure to AI infrastructure if you're

looking to get some exposure, but you also get some income at the same time. So I don't, I haven't looked, I forgot to check what kind of dividend they're paying right now. So I'm looking at Equinix. So it's yielding about 2.4% and digital realty trust, 2.8%. So you're still getting for especially something that's related to tech to some extent, you're getting some decent income. So in my view, it's one of the less risky ways of playing AI today. Of course, you're not going to get as much potential upside because it's still some big investments to build these facilities. It's not cheap. But you're probably going to get some steady growth. It won't blow you out of the water it's more boring than investing in those pure play AI softwares but you still get some

of that exposure and i think they should do pretty well in the next five 10 15 years again you're trading off some of the potential growth here for a bit more kind of steady as she goes and some additional some income so definitely if you're someone who likes to invest in dividends and that's your kind of basis, that's your foundation of your portfolio, and you want some exposure to AI. I think that's a really interesting play as looking at those data center rates. Yeah, double-digit compound annual growth rate for a reed, like in terms of sales would be, like not a lot of them grow at that pace. I mean, I guess my main issue here would be, I'm pretty sure the largest tenants of these companies are still the hyperscalers. I'm pretty sure for the

most part. I believe so. So I mean, a lot of the, if, you know, a lot of this money spent by the Apple's, or sorry, the alphabets, the Microsofts is to build out data center infrastructure. So I mean, I guess my main worry here would be to the point where they can expand fast enough to keep up with demand. And at that point, they might, you know, these REITs might not be, you know, leasing those data centers or whatever it may be might not be. Might not be. the route they want to go just because they can build out the infrastructure fast enough to kind of not have to go to these companies. I mean, I don't know much about this area of the market at all, but that would be, you know, initially when I thought of it, I was like, well, if demand slows and these, the hyperscalers have the buildings, they obviously won't need the leases or if the point where they can keep up with demand, it might, you know, cause a bit of non-renewals, I guess. But again, I I don't pay attention.

No, that's definitely, that's definitely a risk there. Obviously, you have to make sure to, like, I know typically they'll have escalators in their rents, but you want to make sure to that the costs are, like, contain and they don't increase too rapidly. That's definitely a risk there, so it's not without its risk. But if demand is as strong as they say it is, all the large tech companies, then you would think that's probably not a big risk, but it's definitely one there. So it definitely should be mentioned. So I think, so we're around 45 minutes so far.

So I think this is definitely a good point to call it an episode. So part two, so we'll be released this Thursday instead of the news and earnings. So it will be an episode that will be part two. So we'll go over some more subsectors, some that are a bit less conventional, some that will sound pretty obvious for some people too. So make sure you join us on this upcoming Thursday for the rest of the list. It was a really fun episode to do, and we'll take a little break and record the second episode in a minute. If you haven't done so, if you can give us a five-star review on the platforms you listen on,

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