Hot Picks: Three software stocks poised to benefit from AI

Software stocks have rebounded, but select companies could still offer upside as investors better understand the competitive implications of artificial intelligence.

BNN Bloomberg spoke with Kevin McVeigh, managing director at UBS, about valuations across the sector and his investment cases for Constellation Software, SS&C Technologies and Thomson Reuters.

Key Takeaways

• Software valuations continue to imply substantially lower long-term growth than their historical rates despite the sector’s recent rebound.
• Mission-critical products, high switching costs and fragmented proprietary data could help established software providers withstand competition from large language models.
• Constellation Software’s acquisition strategy targets specialized software businesses that customers are unlikely to replace.
• SS&C Technologies’ deeply embedded financial systems and regulatory expertise could make the company difficult for general-purpose AI platforms to displace.
• Thomson Reuters plans to use its in-house Thomson-1 model to control AI costs while retaining external models for more complex legal tasks.

Read the full transcript below:

LINDSAY: It’s time now for Hot Picks. Our next guest sees opportunity across software, from financial infrastructure to legal technology. Joining us now is Kevin McVeigh, managing director at UBS. Good morning. Great to have you back.

KEVIN: Thrilled to be here, and thank you so much.

LINDSAY: So, before we get into your top picks, just kind of a broader look at the sector. As always, we’ve seen a pretty strong rebound when it comes to software stocks lately. Do you think the sector has run ahead of its fundamentals, or is it, is it where it should be?

KEVIN: Not at all. We still think there’s a lot of upside across this group. We think it had gotten way oversold, and, you know, to be fair, there was a lot of uncertainty around AI. And I think what we’re starting to see is fundamentals start to dictate the pricing action in the group. And to your point, they’ve really recovered, but they’re still down meaningfully. And one of the things we’ve looked at, leveraging the work of our terrific colleagues in our HOLT department, is how oversold these stocks still are. So, if you think about a stock like Constellation Software, the stock’s discounting six per cent longer-term growth after kind of a three-year period. That’s as opposed to 15 to 20 per cent historically. If you look through the same lens, Thomson Reuters is discounting five per cent growth longer term. That’s down from 10, and then SS&C is even more stunning. It’s discounting negative one per cent revenue growth, as opposed to five to seven per cent historically. So, despite the move, you’re still seeing really, really attractive risk-reward fundamentals based on where the current valuations sit.

LINDSAY: Are we starting to get a clearer picture of who might become AI winners out of this and who might not be?

KEVIN: I think so, and really, it’s predicated. And we’re trying to use the analogy of Amazon back in 2000, where there was so much concern around retail, right? And last time we checked, Lowe’s, Home Depot, they’ve done just fine, as has Walmart, right? And I think what you’re starting to see is the market reallocate capital to companies with what we think are embedded intellectual property, very high moats, very high regulatory barriers and differentiated data. And across the group, that spans Constellation, SS&C, as well as Thomson Reuters. And we think the risk-reward, particularly given where the fundamentals are, is really, really skewed to the upside here.

LINDSAY: So, let’s start then with Constellation Software. Tell us more about why you like Constellation right now.

KEVIN: Sure. So, Constellation historically has been, and continues to be, a prolific capital allocator. One of the keys to the stock, pre-AI, was the debate as to whether they would be able to really continue to acquire at pace. And what you’re seeing now is them leverage those AI tools. And the key to this opportunity is mission-critical software, where 95—90 to 95 per cent of the revenue is really sourced against mission-critical software that companies can’t really do without, and typically smaller, medium-sized businesses that typically don’t switch out software. A lot of disaggregated data that’d be very difficult to, we think, harmonize with LLMs and creates a nice moat around their business.

LINDSAY: Next up is SS&C Technologies. Tell us more about what opportunities you see here.

KEVIN: Yep, really deeply embedded software, mission-critical. Anything from ordering, executing, back-office accounting for trades. They serve very large multinational clients. Very high risk-reward in terms of getting this infrastructure right, mission-criticality. You can’t worry about hallucinations. Very high regulatory component to it. The stock is a structural AI winner, and I think one of the keys across all of these stocks is they’ve got very favourable margins, very low cost of delivery, and we don’t think the LLMs will be able to displace them. And these companies are leveraging the AI to deliver better products to their clients. And it’s a key part of the story that I think the market just initially overlooked. And that’s why you saw the valuations really reset to the lower levels they did. It created a terrific opportunity to be able to rotate into this group.

LINDSAY: Your third pick is Thomson Reuters. There’s obviously some big news coming out today for this company about it launching its own AI model to reduce reliance on big tech, specifically Claude. I want to talk about that specifically in a moment, but just first of all, maybe tell us your investment case for Thomson Reuters here.

KEVIN: Yep. And again, the one common theme we’ve been trying to focus on is differentiated data, and I think the key to this stock is the market view historically has been all legal data is publicly available. It’s not. There’s a certain amount that’s linear in terms of still physical courthouses, that that data needs to be aggregated. Then there’s the digitized. The key is the curation process, and then you layer on the analytics to help create a product that, you know, big, complex law firms, as well as smaller businesses, can use too. And you bring up a really important point today. I think what’s really encouraging: Two of the three stocks you’re talking about, Constellation and Thomson, they’re Canadian-listed. And particularly given the tariff news out today, really encouraging that you’re seeing these stocks rally into that, as well as, I think, what we want to talk about in a minute is maybe the software that they just announced. But happy to take this wherever it’s most helpful.

LINDSAY: Yeah, maybe explain to our viewers about the software that’s just announced. It’s going to be building its own AI model off Chinese tech. Maybe if you want to explain that, first of all.

KEVIN: Yep, of course. And this follows the theme of token maxing, right, where you saw so much investment, as well as just leaning into these AI models. And what companies are dealing with now is an incredible amount of cost. So, what they’re trying to do is manage that cost as effectively as possible. One of the concerns around Thomson Reuters was that these LLMs, right, the large language models, whether it’s Anthropic’s Claude or there’s a dedicated one called Harvey, would come in and disintermediate them. We think what the market really miscalibrated was how embedded their data is and their ability to respond, not only based on the existing data that they have, but also introduce LLMs, right? So, they’ve got their own legal CoCounsel agent, if you would. To your point, now what they’re looking to do is create their own in an effort to manage that cost. And it’s a critical part because if you’ve got a usage-based model, right, you can triage certain tasks, some based on the model, right, and things that are easier to kind of help get delivered may be lower cost. But when you think about complexity, particularly legal complexity, it can get very, very costly. So, what they’re trying to do is help their clients manage that overall cost of delivery. But the key theme across this entire sector is: Is the data really differentiated? Is the go-to-market differentiated? Is the IP really going to help your clients deliver? And we say yes, and that’s why we’ve been so selective. It’s really, really encouraging to see the market re-rate the stocks.

LINDSAY: I wonder, though. Let’s be quick with this last answer. But building on Chinese open-weight technology, that introduces potential regulatory scrutiny. Do you think Thomson Reuters has assessed, like, export controls, data sovereignty risks, all that kind of stuff?

KEVIN: I think so. I think they’re going to be really, really thoughtful in terms of how they roll this out. They always have been. And remember, when you’re dealing with large multinationals, whether it’s U.S., whether it’s international law firms, their client secrecy and kind of, you know, security of the data is sacrosanct. So, they’re not going to, you know, go in and go out and kind of try to cut any corners in terms of trying to manage expenses. They’re going to be doing it in a very compliant way that I’m sure will, you know, not run afoul of the regulators.

LINDSAY: Okay, we’ve got to leave it there. Kevin McVeigh, managing director at UBS. Appreciate you joining us today. Thanks for your time.

KEVIN: Thank you so much.

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This BNN Bloomberg summary and transcript of the Aug. 24, 2026 interview with Kevin McVeigh are published with the assistance of AI. Original research, interview questions and added context was created by BNN Bloomberg journalists. An editor also reviewed this material before it was published to ensure its accuracy and adherence with BNN Bloomberg editorial policies and standards.