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Making Markets EP51: Elastic’s CEO Ash Kulkarni on Recent Earnings and the Company’s Generative AI Prowess

Making Markets EP51: Elastic's CEO Ash Kulkarni on Recent Earnings and the Company's Generative AI Prowess

On this episode of Making Markets, host Daniel Newman is joined by Elastic‘s Ash Kulkarni, CEO for a conversation on Elastic’s recent earnings report and an in-depth discussion on the company’s advancements and strategies surrounding generative AI.

Their discussion covers:

  • A detailed review of Elastic’s recent financial performance
  • Insights into Elastic’s strategic approaches to incorporating generative AI technology
  • The impact of generative AI on Elastic’s product offerings and customer experience
  • Future directions for Elastic in the realm of AI and machine learning technologies
  • Challenges and opportunities identified by Elastic in the current technology landscape

Learn more at Elastic’s website.

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Transcript:

Daniel Newman: Ash Kulkarni, CEO of Elastic, welcome back to Making Markets.

Ash Kulkarni: Thank you for having me.

Daniel Newman: It’s good to have you again, Ash. I was telling you in the green room, I was like, “I think when you came on and spent time with me last, you were in the role.” You’ve been at Elastic for some time, but you were in the role of CEO for about five minutes and I had the honor of being one of the first people that had the chance to sit down, it was right after the first earnings results with you as CEO. Yeah, Ash, it’s been a couple of years now. You’ve settled nicely into the role.

The company’s growing, mid-double digits. It’s showing strength in its Elasticsearch, which was so well-timed around gen AI and we’ll talk more about that later, but love to just, the audience of this show loves to get inside the head of CEOs of publicly traded companies. Elastic is a growth story, it’s an exciting story. As you’re in a couple of years into this role, what are some of the observations? What are some of the interesting things you’ve experienced, and maybe what was different and what was exactly as you expected?

Ash Kulkarni: Well, just taking on the role itself, one of the wonderful opportunities I got was to take on the role from within. I joined the company a little over three years ago, and Elastic was a company that I had known and loved from the outside. I’d been a user of Elasticsearch, I’d used the product in a couple of different ways in prior companies, and so when I got a chance to meet the team here, the board, the executive team, it was just fantastic. I started as the head of engineering and products, and then a year later, so two years now I’ve been in the CEO role. There’s something really nice about being able to step into the CEO role from within because you’ve had a chance to meet the team, you’ve had a chance to really understand the cadence of the business and what’s working and it gives you, with the right kind of humility because you’ve had the learnings, you can step into the role and know what you want to do about it.

Where do you want to really focus your attention, focus your energy. And that worked out very, very nicely. It was a challenging first year. I learned a lot through that because the macroeconomic environment became quite tight six months into me taking on the role. That resulted in all kinds of challenges. We saw cloud consumption become quite challenged, customers were actively trying to optimize their workloads, that put a lot of pressure on revenue. But through all of it, one of the things I learned is the importance of being true as a business to what we are best at, focusing on the customer, focusing on the way we innovate, and making sure that we never lose that ethos of constant innovation, trying to stay ahead of the competition, trying to differentiate in ways that really wow our customers. The way we turned all of that to our strength, to our advantage is even when we were going through all of those challenges with the macro.

We were able to lean in and help our customers consolidate onto our platform, save money overall, but do it in such a way that they didn’t sacrifice on innovation and it gave them an opportunity to do more with less on our platform. That was a win-win. It was a win for customers, it was a win for us, but it would not have happened if we had strayed from what was always true about Elastic. At the core, we are a company that believes in the power of innovation, that believes in the power of technology, and we’ve always put our customers front and center, we put our community front and center. And so that was a big learning and I’m glad we got it right. Lots to do still, and I’m having fun.

Daniel Newman: Yeah, it’s interesting, the different routes to the seat. Technology and product certainly is one. You tend to have the bean counters. I always joke the people that come through, they’re the ones that know how to get the numbers done. And then there’s often there’s another route for sales, people that really know how to drive revenue, and all three can work. But as I’ve gotten to know what you’re doing at Elastic, I think product-led is very, very important because the product itself is often embedded in everything else so making sure that the product truly stands on its own is so important because of course you want to get some mass awareness. I mean every company wants to have a brand and you may end up putting your name on the side of an F1 vehicle at some point, or a Super Bowl commercial.

I kind of joke, but the point is that’s not really the intent. The intent is that there’s a few hundred companies and then a few thousand enterprises around the world that really benefit from the technology you’re building and it’s your job to make sure the product’s evolution is so crisp, so well understood that your team can go to market to those cloud hyperscalers, software developers, enterprises, and clearly articulate the value. And so it’s a very product led. It’s funny though, you talked about the macro, Ash. It was a really tough ’22, but funny is I wrote a bunch of pieces. I wrote a bunch of op-eds in ’22 when the market was going absolutely terribly. By the way, when NVIDIA was $120, I went on Squawk Box and I told them that the market’s got this one way wrong. It’s my victory lap of the year when I said, “Just watch what’s about to happen with AI.”

So every once in a while you’ll run, but one of the things that was interesting is I kept talking about deflationary, Ash. I kept talking about tech is super deflationary and people went no, no, the only reason stock prices were up in ’21 was interest rates are low. But we’ve been now in what? An eight, nine quarters of tightening now since the end of ’21 when they started, when they turned the direction of the Fed and the QQQ is up 30% during the tightening period. I mean, I’m interested in your take on that, but I think tech has been, while there was a period that was really dark for everything, it felt really dark, tech has been really resilient. I mean yours included is that these companies are growing, earnings are growing, revenues are growing, and it’s against a really tough backdrop.

Ash Kulkarni: Look, I’m a big believer much like you, that technology is one of the fastest moving industries and it’s helped us as an economy. Not just us as a country, but globally. It’s helped improve productivity. When you talk about AI, we can get back to that and how that can potentially be the next step-up in terms of improving productivity. But everything that improves productivity at the end of the day tends to act inflationary like you talked about, right? This real value that gets created, look, it’s not like tech is immune. In my opinion, I don’t think tech is immune to interest rate changes and qualitative tightening and qualitative easing and so on. I think there was some aspect of maybe some of the future demand being pulled in a little bit in the early days of the pandemic when everybody was trying to figure out how to work remotely and so on.

But the reason, in my opinion, why tech has held out so well, even though interest rates have been high for as long as they have, is fundamentally because tech is performing well. Earnings are going up, and earnings are going up because inherently there is something in technology that allows technology to run to be operated quite efficiently. When I think about what are our biggest cost factors as a company, for us, it’s two things. It’s the people, the compensation that we pay our people for, all the great work that they do, the innovations that they create, and the second is our cloud hosting costs. So for our Elastic Cloud business, we pay the infrastructure, the cloud infrastructure, hyperscalers for effectively renting their compute and so on. But that’s it, those are the two biggest cost components. We don’t have massive supply chains, we don’t have manufacturing costs and so on.

Technology and software especially tends to be extremely efficient, and over a long period of time, that’s the reason why you’re able to see significant over the years operating margin expansion, you’re able to see these businesses operate in such a way that’s admirable. That’s the kind of company that we are trying to build. And what I’ve seen in the last about three quarters or so is some of the pressures on optimization. So the macro seems to be a little more normal than it was in 2022 like you talked about. It doesn’t mean that CIOs are expecting budgets to be flush and everything to go back to the top and right, budgets are still tight, but they seem more normal. There is more predictability. CIOs feel comfortable spending again. Not with abandon, there’s still constraints because now they have to spend on AI.

There’s a lot of demand on what they can do with AI to improve efficiency and so on, that’s taking away from some other parts of their budget. But overall, I’d say things seem more normal, things seem more stable. We have seen less pressure in terms of cloud optimizations that were happening, that’s abated. That’s helping, right? All of these things help. That’s why we feel so optimistic about the future, we feel really good about the momentum that we have as a business. Obviously AI is a great tailwind. Right now we are seeing a lot of that in terms of customer adoption. The revenue will come because of our consumption model. Revenue tends to be more back end loaded, but there’s a lot in the economy to feel great about. There’s a lot to feel great about just the way in which technology has fared through all of these ups and downs in the last 24 months. That’s why I really feel fortunate to be in the space that we’re in.

Daniel Newman: Yeah. You said a couple of really important things that I think are worth noting. I mean, first of all, you mentioned that the impact that AI is going to have, and by the way, I still think we’re in early days. I’m going to come back to you about this in just a moment here. You also though mentioned about earnings growth. And that, while I have you, just reported a couple of weeks ago, I think two and a half weeks or so, and you had some really good results, mid-double digits growth, you had some strength in the Elasticsearch platform, which I think is one of the really big connectors to Elastic and generative AI in this whole trend line. Talk a little bit about your recent results for everyone.

Ash Kulkarni: Very happy about the way we performed. We delivered 19% year-over-year growth in our fiscal Q3. Cloud grew by 29% year over year, and we delivered operating margins of 13%. And effectively, we exceeded across all the metrics that we set guidance for so we feel really good about it. And again, if you look back at our history, we have successively every year increased our operating margins and made our business more efficient as we’ve gone. But really what drove our momentum in this past quarter, I’d say three things. The first is generative AI is real, and it’s becoming more, I mean it’s maturing every day. We saw hundreds of additional customers that if it started using Elastic in Q3 for generative AI use cases, for storing dense vectors, for doing vector similarity searches, for using our Sparse EncodeR model for semantic search. So lots of awesome use cases. On the earnings call. I talked about the interesting use cases like Stack Overflow, Consensus, a document management company that we didn’t name, that they specialize in serving the needs of legal professionals.

All of whom have reached that level of maturity where initially several of them were using pure play vector database products, but displaced them and chose Elastic as they started to realize that to build a true enterprise grade generative AI application, you need a lot more than just what those vector pure plays provide. They saw all of that in Elastic. They saw the breadth of functionality, they saw the performance, they saw the open platform that we’ve built. They saw the value that they get from the fact that there are hundreds of thousands, if not millions of developers who already know Elastic, already understand how to use Elastic. So that, gen AI was a big part of the story in Q3. The second thing that we saw, which has been a continuation, and I touched upon this earlier as well, we saw a lot of customers consolidating onto our platform, displacing incumbents, especially for log analytics and SIEM.

So security and observability are both doing very well for us, and we saw that momentum because as budget pressures remain, customers are looking to find platforms that they can consolidate onto where they can reduce their overall spend but do it without sacrificing innovation. So the kinds of things like the AI assistance for the AI assistance for security that we have delivered that our customers find to be incredibly valuable to make the overall task of a security analyst or a site reliability engineer that much easier. They love that innovation and the fact that they can get that at a price that’s lower than what they were paying an incumbent for inferior technology, that’s a no-brainer. So that was a big continued source of momentum for us. And then the third, cloud. We are continuing to see strong momentum, especially in enterprise and commercial segments that we service through our sales teams. Continued momentum there, and all those three things really helped us deliver the kinds of results. So now we are busy in Q4, it’s usually our biggest quarter, and then we get to do this all over again. It’s the joy of having a growing business.

Daniel Newman: And listen, I mean, congratulations on the success. You said a couple of things that I feel are worth noting too. Our intelligence actually has looked at the budgets of IT, and you are absolutely right by the way. We’ve talked to thousands of CIOs and decision makers and budgets are actually pretty flat. Your getting more budget is indicative of market share or market shift. Those are the two things that it’s coming from. Now, I think we know that the edicts are coming down from boards. Boards are saying spend on AI. It’s funny, I had a chance in some public comments to a group of analysts from Chuck Robbins and he talked about money being thrown at CIOs and they’re not even quite sure what to do. It’s like, do AI, what does that mean? What does it mean to do AI?

He said something along the lines of that, and I thought it was really telling because what we found is that there’s about a 3X intent for companies to spend multi-millions on AI implementations in the year 2024. But again, I think two things are really worth noting. One is you’ve been doing AI a long time, you’ve been influencing AI with your platform for a long time. And second of all, I think this kind of AI rising into the consciousness of the world has made it more front and center. Like I said, board, CEOs, CFOs, let’s do AI. But it really still is about two things, right? It’s efficiency and productivity. It’s about unlocking the power of data. I’ll go as far, Ash, just to suggest something, I’d love to get your take on this is that I actually think the LLM craze was a bit table stakes.

I actually think to some extent these open data LLMs, meaning the ones where you just scrape the internet for data. I think one, there’s a whole era of IP rights litigation coming on. Who owns this stuff? That’s a different story. I also though think that we’ve determined that a lot of people can build a model that can somewhat well parse that stuff and give decent feedback. The real value is locked in the proprietary data that sits on-prem in companies’ data centers, in companies’ legacy paper. I mean, all this stuff that needs to be still digitally enabled and transformed and then processed, ingested, synthesized, that’s the opportunity I see for you is that how do you search that and say the company has petabytes and petabytes of data that’s unstructured, plus structured, and this all needs to be easily at the fingertips of people and then of course of auto GPTs and tools that we’re going to build that are going to build processes and workflows. How big of an opportunity do you see that as?

Ash Kulkarni: We see generative AI, especially in the context of what it means for businesses to be just a massive opportunity in the long run. So the thing that I always remind myself of, I started my career in the mid ’90s and the internet was still pretty young then. I recall reading articles about what the internet could be. And in those days, there were the people were talking about, oh, this is going to someday be worth hundreds of billions of dollars, and in the next five years, this is going to be massive, hundreds of billions of dollars. Well, here’s what really happened. It ended up being at least two orders of magnitude greater than that. It’s tens of trillions of dollars, but it took a little longer. You went through different phases where different business models evolved on the internet. It took a little bit of time for people to understand how to do transactions in the internet in a secure way. There were all these moves that happened, but it created this massive economic uplift for everybody.

The same thing happened in cloud computing. Initially, there were these things about, oh, cloud computing, it’s going to be great. You’re going to be able to rent your machines, and it’s going to be worth hundreds of billions of dollars. But guess what? It’s going to be worth way more than that, but it took a little longer. The same with mobile computing. Every time there is a big tectonic shift in terms of a new kind of technology platform, which is exactly what gen AI represents in my opinion. It takes longer, but it ends up being way bigger than anything that the early pundits tend to predict. I think it’s going to be the same thing. Where the value is, like you said, it’s in each organization’s data.

It’s in their private data. Data that they’re never going to give away, data that they want out of from everything that they have within the organization. And what we see happening is companies, you mentioned Chuck Robbins, like interestingly, Cisco has co-presented at one of our conferences on how they’re using Elastic to get value out of their product information to do internal customer support better. They’ve put in a GenAI application that their site reliability engineers are using, they’ve co-presented on how they built it. It’s a wonderful use case. I’ve talked about DocuSign. DocuSign, everybody knows DocuSign is the company that you use to sign documents digitally, but they’re moving away from just a model where they capture everything just as big blob of information with only a few things like your date and signature and so on being searchable to making their entire document searchable for their users so their users can get value.

So if I’m an insurance company, I should be able to ask the question. There’s a hurricane coming in Florida, I want to know what is my overall insurance risk. So you want the analysis to happen across all documents, search for the right zip code, understand what the risk is, how much have you insured, summarize it all for you, give you a nice answer. That is so powerful. There are so many use cases, this thing is going to be massive. It’s going to take time to build up to it because we are still in the very early days. But you see the early kinds of use cases, they give you a flavor. One, of how broad spread it’s going to be.

Two, of how impactful it’s going to be to every business. Three, just what that could mean to a company like Elastic that’s at the heart of all of this as the mechanism by which you do that retrieval, augmented generation, the thing that connects GenAI to your proprietary data. That’s why we are so excited. That’s why we are leaning in so entirely on the product side and the marketing side and the go-to-market side. I think five years from now, we’re going to look back on this, and be so happy that we kept leading through this period in this area.

Daniel Newman: Well, Ash, there’s so much more I could cover, but we have to get going, and I want to just say thank you for joining me here on Making Markets. Let’s have you back soon in the next few quarters. Let’s hear how it continues to progress. Congratulations on the success. Thanks for sharing a little bit about this quarter, giving us some of the insights on both your run-up as CEO to date. Hopefully, it’s a long healthy tenure ahead of you. And then of course, some of your insights on where you see the opportunity around AI, generative AI, and Elastic’s growth. Let’s have you back soon.

Ash Kulkarni: Thank you. Thank you very much for having me, and as always, the conversation is so much fun. Take care.

Daniel Newman: And thank you all for tuning in to Making Markets.

Author Information

Daniel is the CEO of The Futurum Group. Living his life at the intersection of people and technology, Daniel works with the world’s largest technology brands exploring Digital Transformation and how it is influencing the enterprise.

From the leading edge of AI to global technology policy, Daniel makes the connections between business, people and tech that are required for companies to benefit most from their technology investments. Daniel is a top 5 globally ranked industry analyst and his ideas are regularly cited or shared in television appearances by CNBC, Bloomberg, Wall Street Journal and hundreds of other sites around the world.

A 7x Best-Selling Author including his most recent book “Human/Machine.” Daniel is also a Forbes and MarketWatch (Dow Jones) contributor.

An MBA and Former Graduate Adjunct Faculty, Daniel is an Austin Texas transplant after 40 years in Chicago. His speaking takes him around the world each year as he shares his vision of the role technology will play in our future.

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