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Inside Xtrackers XAIX: Why Most AI ETFs Get It Wrong and How XAIX Does It Better

• Michael A. Gayed, CFA

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Artificial intelligence is driving one of the largest capital spending cycles in market history, yet most AI investment strategies focus on surface level exposure rather than true innovation. In this Lead-Lag Deep Dive, Melanie Schaeffer sits down with Aram Babikian of Xtrackers to examine how AI investing is evolving and why research intensity and patent activity may matter more than headlines.

The discussion breaks down the structure behind XAIX, an AI focused ETF designed around companies that are actively building, protecting, and monetizing innovation. Babikian explains how patent filings and R and D spending act as forward looking signals, why unexpected companies like major banks appear in AI portfolios, and how this approach differs from more crowded thematic strategies.

They also explore how XAIX fits alongside broader technology exposure, the tradeoffs between concentration and diversification, and how advisors think about incorporating AI into portfolios amid volatility, regulation, and rapid technological change.

In this episode:
Why AI investing is not the same as buying tech stocks
How patent activity and R and D spending identify true innovators
Why non tech companies can be major AI beneficiaries
How XAIX differs from broader thematic AI exposure
How investors think about sizing AI allocations responsibly

Lead-Lag Deep Dive is a weekly series that breaks down the forces reshaping global markets. Each episode goes beneath the surface of one critical theme, examining how strategies are built, where risks hide, and what matters most for investors across cycles and asset sizes. Subscribe for research-driven insight beyond the noise.

#AI #ArtificialIntelligence #ThematicInvesting #ETFS  #PortfolioStrategy #Finance #MacroTrends

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SPEAKER_01:

Really, what differentiates us is we're not just investing in AI-centric companies, but we're really investing in the AI innovators. And the AI innovators are not just what you would think immediately about AI companies. Some of them are even banks, some of them are, you know, other companies of the sort. So you're investing in where the greatest beneficiaries are going to be. Thank you for having me, Melanie. Great to be back again.

SPEAKER_00:

Perfect. Yeah, so we're gonna get right into it. Um last week we talked about CRTC, which includes AI. Um, this week we're talking about X AIX, another of your funds that's more AI focused, which everybody is interested in right now. Everybody's talking about it. Uh, just to start off, can you talk about why you've developed the fund, the history of it, and what its real purpose serves right now?

SPEAKER_01:

So this fund is actually a um we already had a fund overseas that we launched um about five years ago. And this is we brought a US version to market, um, tickers XAIX. And AI obviously has been uh one of the most, if not the most important innovation in the past five years. You're seeing lots and lots of uh catbacks go into it, lots of investment, but the landscape is changing every single day. Things are evolving quite a bit within the space. It really feels like what was going on in the 90s with uh this being sort of Internet 2.0. And we believe we have a very unique solution uh in this space that is also one of the least expensive in the market at only 35 basis points.

SPEAKER_00:

Aaron, and you've mentioned that this is quite a unique uh ETF. Can you mention what makes it or discuss what makes it unique and talk a little bit about the methodology?

SPEAKER_01:

Well, uh for starters, we're we're partnering with NASDAQ on this, but uh as I mentioned, NASDAQ has done a lot of research um within the category of RD and what that what the correlation or uh outcome is for RD spenders. Now, with that being said, the way that we're looking at RD isn't just the spending, we're looking at RD as also patent filings. And we're using patent filings as a growth signal. And with that being said, if you look at sort of the patent filers, um, the larger there is a correlation between large patent filings, R D, and the outcome in overall performance. So we sort of start with a universe of 1,700 or so companies. And uh this is NASDAQ's global disruptive tech benchmark. And then you whittle down to 701 companies with patents relating to AI and big data themes. And then you go even further. And right now we have about 90 companies within our portfolio. Again, the limit is 100, uh, so it can change every time we rebalance. But within those constituents, we're looking at cloud computing, deep learning, cybersecurity, natural language processing, speech recognition, and chatbots, big data and image recognition. So each of these companies then get ranked into a certain profile. So, for example, you have certain companies that fit or hit all seven of those categories, and then you have others that might be less than that. So the way we uh create the portfolio, it is market cap weighted, but it's a modified market cap weighted that also takes into account the patents and within the realm of market cap itself. So we categorize uh large, mid, small, and then within those categories, it gets weighted through patents. So again, utilizing natural language processing, uh, the basket and patents are sifted through from NASDAQ, and that is applied through the index itself. And this is a very unique strategy, one that I believe no one else is uh implementing within their portfolios. And again, the purpose for this is it makes it both backward and forward looking.

SPEAKER_00:

Talking about uh the holdings, I want to ask you specifically about Bank of America. It's it was one that I might have felt a little bit surprised to see when I looked at the top holdings. Can you talk about why that's included?

SPEAKER_01:

So Bank of America is actually very unique. And um this is, you know, NASDAQ gives us kind of the data, and all of this is publicly available. But if you look at Bank of America, it is actually one of the largest patent holders when it comes to AI patents. If I'm not mistaken, the data that I saw, it was over 200 different patents within the AI space. So not only are they innovators, not only are they going to be beneficiaries of growth within AI, but all of that is also being implemented within Bank of America itself and the business itself. So it's kind of a holistic look on all fronts of AI. And that's what separates our product versus many others, is that you are going to get some very unique companies that you might not think about that are quote unquote AI companies that are going to be in the portfolio. And Bank of America is one of those that really is one of the most uh the highest holders of AI patents within the universe that we screen.

SPEAKER_00:

Was XAIX something that works well with CRTC, which we spoke about last week?

SPEAKER_01:

So, you know, we we said CRTC would be your thematic core, but if you really are interested a lot more in AI and you want to invest more in it, this is a greater, more precise tool that allows you to just get an allocation to the AI portion of the critical technologies. And what's unique about XAAX is we've partnered with NASDAQ here, utilizing uh their index, but also the methodology does include AI in the form of natural language processing to help create the basket of stocks. And also, our the way we create the basket of stocks is very different than some of our peers within this space. Really, what differentiates us is we're not just investing in AI-centric companies, but we're really investing in the AI innovators. And the AI innovators are not just what you would think immediately about AI companies. Some of them are even banks, some of them are you know other companies uh of the sort. So it it it's you're really in a you're investing in kind of where the greatest beneficiaries are going to be.

SPEAKER_00:

Is there overlap between CRTC and XAIX in terms of the holdings?

SPEAKER_01:

Yes, of course. There's there's going to be some overlap, but it's not as much, it's not as much as people think. Um, at the end of the day, X XAIX is simply just AI while um or uh you know AI and kind of that realm of artificial intelligence and big data, while CRTC includes many other different companies that are within that area. So if if I look at it, I believe I ran an analysis a while back. And obviously this is subject to change uh every time we rebalance the portfolio and so forth, but it comes to about 38% of overlap between CRTC and XAIX.

SPEAKER_00:

Speaking about AI, I mean, there's a lot of shifts that are happening globally with trade policy, tech security concerns, and even AI regulation. How do you think those forces could affect or interact with uh funds like XAIX?

SPEAKER_01:

Obviously, there's always going to be headline risk when it comes to investing. And the, you know, I I've been around doing ETF since 2008, and you're seeing a lot of volatility in the sense of headlines. It is what it is, but you have to kind of look at sort of the premise below. And essentially the investment premise here behind XAIX is we're looking at large cap companies, but essentially we NASDAQ ran an analysis and they looked at the top quartile of RD um and percent sales, and they did that versus the other quartiles of you know, Q uh Quartile 2, Quartile 3, Quartile 4, and then even the zeros that are not investing at all. And they equally weighted that. And they saw that the top quartile um companies that spent the most on RD substantially outperformed those that were RD laggards and non-spenders. So the investment premise here is that the companies that are spending the most on RD, which in this case also translates to patents, um, will be uh hopefully the or potential beneficiaries over the long term when it comes to rewards in their stock price and outperforming those that don't. So essentially what NASDAQ has done is created a different way that is both backward looking and forward looking to help invest in XAIX. And it's sort of hopefully doing it that way, it drowns out some of the noise. Again, you're always going to have headline risk, you're always gonna see certain things. But if you believe in AI, you believe in the future of AI, how transformative it's going to be, the investments that are being done in this space, then the hopefully that also aligns and translates to a higher return as a result of that. But at the end of the day, you know, there's only so much you can do. And what happened in 1999 is often compared to what's going on right now. And in my opinion, there are some parallels. But on the other side, you're also going to see that there's going to be some large beneficiaries in this space, but there are going to be ones that are going to be losers. At the end of the day, uh it everyone can't win at the same time. So it's going to be uneven. And the ones that are going to be winners are probably also ones that are not only within the space as beneficiaries, but also innovators.

SPEAKER_00:

So talking about winning and losing, and I know you talk to a lot of investors and also a lot of advisors. And from that standpoint, I mean, suppose that someone has a traditional diversified portfolio with broad equities bonds, maybe a global mix. What's the most sensible way then to incorporate XAX and even C RTC, which we talked about last week, into this as sort of a satellite allocation?

SPEAKER_01:

Well, it really, it really depends on what you're going for. Um, you know, I speak to a lot of advisors, and uh, most advisors, the way that they're using uh a XAIX is within that opportunistic bucket where they'll put a lot of the thematic. But considering this also is mostly large cap names, if you really wanted to and you were you had a lot of high conviction, there is potential for it to be a sort of core or core plus allocation. And the reasoning behind that, again, comes down to where are the dollars going? What is a represent, what is a great representation of the economy? I mean, if you look at the S ⁇ P 500s, the 500 top names, but if you look at from it from a diversification standpoint, there's now seven companies that are, I believe, over 34% of the index at this point. So if you want a true representation of where the dollars are going, um, there are there are many different ways of doing that. But again, it really depends on how much you believe in the conviction that you have in AI and how transformative you believe it's going to be, and if it's going to be the dominant force in the next 10 years, again, it's up to the advisor and how they go about it. I'm not giving any advice of where to put it, but there is the possibility that they could put it as an core allocation. But usually, for the most part, we see it as part of the thematic category. And it is one of the larger allocations within that thematic, given how important and how much CapEx is going into the space.

SPEAKER_00:

Just lastly, uh, I I'm thinking about what type of advisor, who's the right type of investor or advisor, and how would that person be suited for each fund? So talking about XAIX and uh CRTC, and is it for someone mostly willing to ride volatility in exchange for high growth?

SPEAKER_01:

Well, um, it really comes down to uh a few things. So with CRTC, given it's heavily diversified with over 220 names, it was actually designed to be less volatile and sort of trade-like or um the return stream be very similar to a core type allocation. So the volatility or standard deviation is going to be similar to that. Um, now when it comes to XCIX, obviously you're in a more concentrated portfolio. The the way XCIX is designed is it has a limit of 100 holdings. And obviously, it is thematic, so it is more concentrated into a particular theme of artificial intelligence and big data. So you are going to have a bit higher volatility in that case. Uh, so it might not be um appropriate for certain investors, but at the same time, again, it all comes down to what is the outcome that you're trying to reach. And if you're looking at sort of XAIX with its very low expense ratio, as well as its diversification of nearly 100 names within that category, and also utilizing a very specialized uh way of investing, which looks at the patent activity of these companies to make it sort of both backward and forward looking. Again, it comes down to kind of discussion we had last week of offense and defense. Sometimes the best uh defense is a great offense, and vice versa. And in this case, when you're investing in the greatest innovators, the greatest spenders on RD, and obviously not everything that happens in the past is indicative of the future. But if you're looking at kind of the return stream that is potential for that, where in the past these RD spenders um have been um rewarded while the non-spenders have received less, there is the potential for that to continue. And in this case, you're investing in the companies that have some of the highest RD spend, are the greatest innovators within this category. And again, it really comes down to why we call it thematic is because you're investing in a theme. So the first approach is what is your true conviction in this theme and how is your conviction? And then comes down to the product, but also simultaneously is what is that going to be weighted within your portfolio? And again, that's only something that uh an advisor can help their clients decide according to what their outcomes that they're looking for.

SPEAKER_00:

So outside of going to their advisor, for anyone watching who wants to dig in into more of the details of XAIX and CRTC and the other uh funds that we've spoken about on Lead Leg Deep Dive, where's the best place for them to go?

SPEAKER_01:

Our website is very robust. It has a lot of articles on it. You can reach out to uh or uh go on the internet and uh xtrackers.com, or you can reach out to me uh via email at aram.babikian at dws.com.

SPEAKER_00:

Perfect. Well, thanks so much for joining me again today, Aram. And thanks to everyone for watching. This is Lead Legs Deep Dive. Be sure to like, follow, and subscribe for more episodes and check the description for previous episodes with Aram on Deep Dive.

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Michael A. Gayed, CFA

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