CrowdStrike Issues Sales Outlook Meeting Wall Street Views

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1:59Vlad Rikhter:We'll stay on the technology theme here. We're going to check in with Mandeep Singh, Global Tech Research Head at Bloomberg Intelligence. Mandeep, lots of news to talk about. I want to just start with CrowdStrike. Sales outlook kind of in line with expectations. Stock off a little bit here. Just refresh our memory. What is CrowdStrike and how does it fit into the tech stack? Yeah, I mean, they are one of the pure play cybersecurity names, and clearly they have done quite well in terms of their top line growth over the last two, three years. And, you know, like with everything in the SaaS complex, some of these names have come under pressure because of potential competition from LLM companies like Anthropic.

2:45Vlad Rikhter:And I think that's where you see a muted reaction today. But, you know, they had their best new ARR growth yesterday. And the guidance was a little conservative, but that's what we are seeing from all the software companies that have reported results this quarter is they want to beat and raise for the next one. And I think for a company like CrowdStrike that's growing mid-20 % and very high retention rate, I mean, things are looking good because all these LLMs should potentially drive more demand for cybersecurity. If there's one area that certainly is poised to benefit from LLM usage, it should be cybersecurity.

3:34Mandeep Singh:Mandeep, CrowdStrike has been, as you mentioned, one of the biggest beneficiaries of cybersecurity spending boom. After this earnings report, does it still look like there is still strong secular demand or are we starting to see signs that those budgets are becoming a little bit more selective?

3:50Vlad Rikhter:not in the cyber security complex so if anything uh you know if you have more data now which is the case with llms now you know you are generating a lot more data you are using it for training and and so all that needs to be secured and prompt injection attacks is a new type of attack that you have to secure again. So from my perspective, you know, and based on our conversations, like this is the last thing any enterprise would want to cut. Yes, they are shifting budgets, you know, allocating to AI more compared to the traditional areas. But when it comes to cybersecurity, I mean, the risks continue to get bigger and bigger in terms of data loss or, you know, getting hacked.

4:41Vlad Rikhter:And so from that perspective, you're unlikely to cut back on, you know, especially a primary cybersecurity product, which I mean, in a lot of cases, there are point products, but CrowdStrike is more of a platform with multiple sort of threat vectors that they protect against. So from that perspective, also, they are quite insulated. All right, folks, this is how it works at Bloomberg. Usually, Mandeep, he comes into our studio when we want to talk to him. He's not in our studio today, which got me thinking, Where is Mandeep Singh today? And at Bloomberg, we can tell where everybody is at all times.

5:14Vlad Rikhter:You have to put where you are and who you're meeting with. It's kind of the full disclosure thing they do at Bloomberg. So I know where he is. He's downtown at the Bloomberg Invest Conference. Anytime Bloomberg gets its clients together, they all just want to talk to Mandeep. They want to hear Mandeep talk about what's going on in tech and most notably AI. So I'm going to go right there. Mandeep, what's the conversation today about AI? It went from just build, build, build, build. Now people are starting to think about what are some of the ripple effects, second and third quarter effects here.

5:44What's the investor view of AI these days?

5:48Vlad Rikhter:Yeah, I mean, at this conference over the last couple of days, the focus has been on the private markets. And as you know, private equity owns a lot of these software, traditional software companies that generate very high free cash flow. But everyone is looking at, you know, what are these LLMs going to disrupt and what does that mean, you know, to the free cash flow of some of these companies. And so private markets have been a big focus, I would say, over the last two days.

6:18Mandeep Singh:Mandeep, there's been this trade, the halo trade, focusing on tangible assets when it comes to deciphering, you know, who the AI winners and losers are going to be. I spoke recently to UBS, a global wealth CIO, and she said that she's focusing on the builders and not the coders. How are you thinking about this dynamic between the companies with tangible assets versus intellectual property?

6:41Vlad Rikhter:Yeah, I mean, look at all the hyperscalers, right? They used to have most of them used to have an asset-led business model. Now we are talking about, you know,$700 billion in aggregate CapEx for this year, just from the hyperscalers. And this is likely a multi-year cycle. So from that perspective, I mean, we know AI is compute intensive and you need a lot more, you know, infrastructure to do AI. And so from that perspective, things certainly are shifting, you know, from intellectual property to owning infrastructure. and that's the trend that is likely to continue. Stay with us. More from Bloomberg Intelligence coming up after this.

7:48Paul Sweeney:Get smarter by putting AI where it actually pays off, deep in the work that moves the business. Let's create smarter business. IBM.

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9:27Mandeep Singh:You're listening to the Bloomberg Intelligence Podcast. Catch us live weekdays at 10 a.m. Eastern on Apple CarPlay and Android Auto with the Bloomberg Business App. Listen on demand

9:37Vlad Rikhter:wherever you get your podcasts or watch us live on YouTube. AI story on just yet another angle is how AI is being deployed by the Department of Defense and other parts of the U.S. government, particularly about the Defense Department. We had Anthropic clashing with the Pentagon about how their AI could be used. Then we had OpenAI Chief Executive Officer Sam Altman says, we'll come in and we'll do some of the work for you. And there's a lot of uncertainty about how AI is going to be used and who will actually provide it for various government entities, including most notably the Department of Defense.

10:12Vlad Rikhter:Vlad Richter joins us here. He's the CEO of the cybersecurity company Fencer. Vlad, how do you think this is playing out? AI, the Department of Defense specifically, we've had some uncertainty here. What do you make of it?

10:26Paul Sweeney:yeah look i think there's clearly some sort of misunderstanding internally uh between um uh between the departments uh the pentagon and uh anthropic uh seemingly because from what we're reading over the weekend open ai signed uh an agreement according to sam alvin uh with uh with the pentagon that kind of stated the outlines that i think we as citizens would very much care about which is we don't want to see mass surveillance and we don't definitely don't can't even imagine situation where there would be autonomous weapons going through there. But I think this also speaks to part of the challenge within these AI companies, and specifically the models, is that a lot of the data that they're trained on is effectively the same.

11:06Paul Sweeney:And so over time, the work that they're doing becomes kind of commoditized, and there isn't much of a moat. And so the government will inevitably, in my opinion, turn around and start to work with the vendors that will play ball with them and not try to strong-arm them in any single position.

11:21Mandeep Singh:Opportunistic and sloppy was the language that Sam Altman used. Pretty strong language there. What does that tell us about the rush by AI Labs to secure government contracts and how important of a customer is the Pentagon when it comes to the AI industry?

11:36Paul Sweeney:Yeah, great question. So I think from a perspective of how important the Pentagon is or the government specifically to these AI companies as a customer, it's actually not that much. I mean, if you look at it from the perspective of Anthropic, you know, it was reported that the deal with the Pentagon was around$200 million a year. And I think as reported by Bloomberg today, Anthropic went from$14 billion in run rate a few weeks ago to nearly$19 billion today. It's 1 % of their revenue, right? And I think for the same, probably similar to OpenAI and some of these other ones, that it's meaningful revenue, but as a percentage of the overall base, It's not significant.

12:14Paul Sweeney:And instead, what we need as citizens is that the government actually chooses, and it's more important for them. I think in the case of OpenAI with the contract they just signed, it was a little bit too fast, like Sam said. And the communication was not great. I mean, there was a handful of departures, including some relatively senior people from OpenAI after the weekend that decided to go to Anthropoc. And I'm not sure how much people know about this historically, but the Anthropic founding team was actually all, for the most part, all ex-OpenAI employees that disagreed back in 2021 with some of the direction that OpenAI was heading to and decided to leave and start Anthropic themselves.

12:53Paul Sweeney:And I think today there are roughly 70 to 80 employees at Anthropic that are ex-OpenAI. But at OpenAI, I think there are only about 10 or 12 employees that are ex-Anthropic. So you can see kind of where the movement's been going between the sort of the intelligent folks there.

13:06Vlad Rikhter:Do we have any idea to what extent in the Pentagon and the Department of Defense that AI is being utilized? Are they cutting edge because they have the resources or are they kind of an old government plotting institution? How are they employing AI?

13:22Paul Sweeney:There's a great article, I think it was actually from you guys earlier this morning that popped out that kind of described a little bit of that was revealed by some source of how it's being used. and the understanding of what was reported was that the Pentagon had decided that there were going to be roughly a thousand places that they were going to hit initially, a thousand sites that they were going to hit initially inside of Iran. In previous versions of this, you can't hit all thousands at once. And so people would sit down, they would prioritize them based on a handful of different factors, and it would probably take a couple of weeks to get this done, if not longer.

13:56Paul Sweeney:Right. In this case, what was understood was that they were using Palantir's Maven product, which underneath the hood was also being powered by Claude from Anthropic. And they basically fed in a bunch of data that Palantir has access to from the government and said, OK, prioritize this for us based on what we need to do in the different sort of movements, right? Step one, step two, step three, whatever it may be. I think at that point, just like if any of us were using AI to prioritize some other thing for us, it pulled out a spreadsheet and said, listen, this is, I'm paraphrasing here, assuming, This is what you should be doing.

14:30Paul Sweeney:And I imagine the powers that be sat down, took a look at and said, is this really what we want to be doing? Do we want to hit these first hunter or not? But at a minimum, you're getting that done in 45 minutes, right? This is not a multi-week endeavor. It just kind of gets you a little bit faster there. It might only be 90 % correct, but humans will decide the rest of it from there.

14:48Mandeep Singh:Vlad, we've seen AI leaders call for stricter regulation while simultaneously pursuing defense contracts. Is there a sense that these deals are happening faster than the industry can establish the right ethical guardrails?

15:04Paul Sweeney:Yeah, so I, you know, depends on the day. You sometimes can go back and forth. What I think what I would tell you is that it's not even sometimes so much as the guardrails from the industry, but the guardrails from the government. Right. There are some significant points that I agree very much with Dario, the CEO at Dario Madej at Anthropoc on this, which is the government does need to provide some guardrails for us on what is appropriate, what is not appropriate, how do we protect U.S. citizens, at what point in time does the Pentagon decide to overstep some of these boundaries and if they're allowed to.

15:36Paul Sweeney:But I think these things are moving too quickly at this point, right? I mean, these models come out every, you know, a new version of a model comes out every few months from one of these organizations and it beats the previous one by 10, 15, 20, 30 percent. And all of a sudden it unlocks things that we didn't think was possible. And you hear these comments that I think Dario said this earlier this week where he said that he believes that there's going to be exponential growth later this year. And for a company like ours, we went from 5 % of our code being written by AI a year ago to north of 60 % today.

16:11Paul Sweeney:You start to struggle to imagine what exponential looks like by the end of the year. And so I think it's just tough to keep up with these things.

16:20Vlad Rikhter:Stay with us. More from Bloomberg Intelligence coming up after this.

16:49Paul Sweeney:it actually pays off, deep in the work that moves the business. Let's create smarter business. IBM.

17:19Mandeep Singh:When you're on the line, do that with Acrobat. Learn more at adobe.com slash do that with Acrobat.

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