Appian Corporation

vision of AI and that's what we'll be facilitating. So I mean, we've already made a lot of AI functional drops, right? So we're in the market today with a great deal of AI related functionality, large language model related and otherwise. So just in terms of volume of AI functionality, I believe we're doing great. But more importantly, we're guiding toward a sensible philosophy of AI use and where AI is going to belong in the enterprise. And I think that because we're correct about that, we're going to be facilitating a usage model that customers are going to want to invest in. Also, you asked if buying patterns were changing. I would just say simply that they're not, that we didn't see much change in buying patterns.

And I appreciate that. Thank you.

Thank you. One moment for our next question. Our next question comes from the line of Steve Enders from Citi.

Okay, great. Thanks for taking the question here. I guess I'm just going to ask on the deal environment currently and I guess How should we be thinking about the stability of budgets and willingness for customers to be investing in automation and low-code and AI initiatives at this point?

Well, I think there's a tremendous amount of excitement around AI, but I also think it's a little bit early for us to appraise that because the AI boom happened less time ago than the length of our sales cycle. So I think it would just be premature to speak to the way that's opened pocketbooks. I don't know yet. I will say that it appears that customers are applying extra scrutiny to purchases this year, that their sales cycles are slightly extended by that. There's been some delays, more delays than cancellations. There's just, I think, just extra consideration around investment to be made. And, you know, the counterpoint to that is an extreme amount of excitement about the way technology could create better efficiency, specifically around AI.

I guess on the deal cycle point, I mean, I think you remember back to the past couple of quarters that, you know, there might have been some slight impact, but not a real, I guess not an overarching challenge there. I guess has that continued or has it gotten maybe a little bit little bit more strenuous in the past quarter or so?

I would say that it's somewhat consistent with last quarter. We see deals taking longer, but not disappearing, just taking longer. The interest is there. And I don't deny you could see it in the numbers, right? If you were to see a side by side of a regular year versus what we're seeing now, there would be an evident difference. It would be a delay. But I also don't want to make it sound like that's an enormous difference because it's not. This is a quantifiable but small factor.

All right. That's helpful. And then I want to ask on Data Fabric, And I guess maybe kind of the extent that's penetrated throughout the base at this point. And I guess, you know, kind of secondarily is that you think about data fabric and that differentiation is, think about the AI initiatives that you're undertaking. I guess, how much is that helping those conversations and maybe pushing towards a purchase decision with the data fabric element in there?

Yeah. Data Fabric is going to help us make a specific form of AI argument. So let me clarify this before I address your question. Data Fabric allows you to gather information in dispersed locations across your enterprise and use it for a common purpose. It's like a common semantic layer for addressing all that data, as if maybe we'd put it all into the same database, except we didn't. We just came up with a common way of grouping it and addressing it, even though it's really scattered across the enterprise. Well, that's super useful. If what you want to do is train or fine-tune an AI algorithm, if you bring in an AI model, you want to use it behind the firewall so that you keep the data. It's always yours. You keep the algorithm. It's always yours. It's a very private, customer-centric environment. data-centric vision of how to use AI, then Data Fabric is fantastic. Data Fabric will grab you that data set, allow you to customize, select the information you want to train your algorithm with, bring it together neatly, and serve it up to the AI algorithm so you can train it. It's very good for that kind of a vision. It's also very good for that matter for our typical use, which is to inform the actions in a process. And remember that now AI is one of the primary actors in a process. And so the more data connectivity you have, the more you can inform, you know, send the right questions to AI, be sure that they're better informed to give you the answers. So Data Fabric is a key supporting player in an AI future. As for how that's playing out in terms of winning deals, closing deals, it's going to be too early to say. So I can't speak to that. But I... I have strong belief that we are facilitating a form of AI usage that's going to appeal to large organizations in regulated industries with important data sets and mission critical intentions.

Perfect. Appreciate the answer there.

Thank you. One moment for our next question. Our next question comes from the line of Sanjit Singh from Morgan Stanley.

Excellent. Thank you. This is Dion for Sanjit. I just have maybe two quick questions on the go-to-market. The first one, last quarter you spoke a lot about public sector strength. I would be curious to hear kind of where the strength was this quarter and then maybe contrast that with where you also see the most excitement around AI that could materialize later on. And then the second one, On the new partner program that you announced, anything that you can share in terms of what you're seeing in terms of early momentum or what we should think about in terms of timing, some of those new leads materializing, that would be very helpful.

Okay. Okay, great. With regards to the industry that did the best this quarter, I'm going to public sector again. It's just a really strong... sequence here in the U.S. public sector specifically, which isn't to say that that's where there's the most excitement around AI. The public sector is a cautious segment, and I don't think it's going to be the AI pioneer. I think we're going to see AI pioneering in places like pharmaceutical, financial services. I think it's going to make sense, insurance, healthcare. I I'd actually put public sector as a likely AI late adopter, relatively. So we're succeeding for other reasons in public sector. And then the other question was about partners. We are adopting a new methodology of working with partners. I think it's dynamic. It's exciting. It's premature to cite anything, of course, totally. because it's not even rolled out. So I can't say what it has done, but I believe that we're onto something important. Having learned what we have about how to motivate partners, I think that we're gonna take a powerful step in the right direction. And that's all I can say about it, just a future expectation kind of a statement.

Great, thank you.

Thank you. One moment for our next question. Our next question comes from the line of Kevin Kumar from Goldman Sachs.

Hi, thanks for taking my question. Matt, Appian has an expanded set of AI-related features and capabilities that is going to be released, I think, later this year. Are these features being released across all on-premise and cloud customers? And do you think AI could potentially catalyze more customers to migrate towards cloud over time?

You know, I think AI will catalyze more customers to move to cloud. We are focusing on cloud as the primary AI environment. We will deliver more AI functionality faster in the cloud. And yes, I do believe that that will be an incentive for customers to choose it. I want to be careful not to say that it will be an incentive for customers to migrate to it because I'm not convinced that the customers who aren't, who have not yet migrated by cloud, will be motivated by any new feature set.

Okay, that's helpful. And then maybe one on margins. Operating expenses, I think excluding certain one-time items, has been relatively flat the last three quarters. Obviously, I know there's a focus on expanding margins, particularly in the second half of the year. So I'm curious, Mark, how you're thinking about resource allocation and How much is maybe new headcount in international regions, such as India, helping with some of that operating leverage? Thanks.

Yeah, sure. Thanks for that question. I mean, there's definitely a focus on extracting operating leverage from our R&D center in India, but it's also just making sure we're investing in growth where it counts, right? And so we're not looking to make any operating expense reductions in areas that might impact our growth rate or our expansion, and it's really just some OPEX initiatives around scrutiny items that have led to some tightening of the ship, if you will, and then some operating expense moderation in all areas across the board. But we definitely have a goal in mind that we shared in the past and that I've spoken to in my prepared remarks with operating expenses, and I think we're continuing to see through that plan.

Thank you both.

Thank you. One moment for our next question. Our next question comes in the line of Terry Tillman from Truist Securities.

Hey guys, this is Joe Mears. I'm for Terry. I'm just curious, Cloud Sub NRR is remaining steady at 115%. I'm just curious, are there any moving pieces under the hood as far as better results from upsells or new logos?

I mean, it's pretty consistent, to be honest. If anything, expansion is slightly healthier. I mean, our GRR is so strong that it's hard for it to go any stronger. But overall, I would say it's been more the same than different.

Cool. That's helpful. Just from the margin question, I understand that you're investing where it counts and maybe doing some moderation in other areas, but I think you had said that you expect to be EBITDA break-even next year. Are there going to have to be larger cuts to operating expenses or in order to get there in the medium term, or is it just going to be a factor of revenue leverage? Thank you very much.

Yeah, I'll take that. Yeah, I'll take it. You can get that in, Matt, if you want. It's the latter. It's really, we're not going to cut our way to an even or break-even point. And just to clarify, you know, we're saying we're going to reach a break-even point next year. It's not the full break-even. But yeah, that is going to come through through the growth and the natural growth of our revenue streams and not through some concerted effort to cut out costs.

Thank you. Thank you. One moment for our next question. Our next question comes from the line of Derek Wood from TD Cowan.

Oh, great. Thanks. It's Andrew for Derek. Matt, just wanted to come back to the federal business. How did federal bookings compare to last, software bookings compare to last quarter and heading into the big September quarter? Can you give us a sense for how pipelines are tracking, how they compare versus last year this time? And can that new, the GAM solution, are you expecting pretty good upsell this year?

All right. First of all, let me just second what Mark said a moment ago about growing our way to breakeven. That's the plan for next year. We're not going to cut our way there. We're going to grow our way there. Secondly, with regards to the performance of public sector and the pipeline, specifically heading into the big Q3, we feel good about the pipeline. It shows real strength. I'm pleased with public sector's progress so far this year, and I think we have momentum and reason to believe that we can do well in quarters ahead.

Great. And I think last quarter you talked about Appian World prospects or leads being up 2x year over year. Maybe just talk about how those leads are moving through the pipeline and your ability to convert and close some of those deals in the second half.

All right. Now, I'm going to speak based on what I know of this, which is not everything. I understand us to be doing well with regards to new opportunities, stage one leads, and a lot of that comes from events like Appian World, but not exclusively Appian World. We're seeing strength in that broad category, and Appian World is just one of the sources. It's true that Appian World is well attended. It's true we got more prospects than we typically get. Those are great signs. Appian World is like a showcase for what people can do with our software and the strength of the community and the enthusiasm around our users. I mean, 98% gross renewal rate is a number until you show up at Appian World and then it's an experience. And those people are, it's contagious, right? The excitement. So I think it's great to get our prospects there. I believe that that led to a set of quantifiable leads, but I don't have the numbers that show that that's where the leads came from, so I don't want to be too definitive about it. I just expect that that was a great experience, and we exposed a lot of prospects to it, so good things are going to happen.

Great. Thanks, guys.

Thank you. One moment for our next question. Our next question goes in the line of Jake Roberge from William Blair.

Hey, thanks for taking my questions. Data fabric vision definitely sounds very interesting. I'm just, I'm curious when we think about your core products within low code RPA and process mining, do you think any of these products will see outsized benefits or headwinds from generative AI? And then how do you think AI impacts existing productized solutions within maybe your KYC or the GAM suite, and could it impact kind of the future solutions roadmap from here?

It can definitely impact the future solutions roadmap. It's a terrific way to enhance the value of our application in all contexts. It enhances it in a solution. It enhances it as a platform build. AI is one. One is like a star addition to the team. The AI is more powerful than it's ever been. It's more popular than it's ever been. It's more likely to be adopted than ever. And it's part of a great suite of automation tools that can do work. So this is a efficiency boost for all of our applications and all of our clients as soon as we can get them to make proper use of it. Yeah, so I see it as a lift across the board. No, no, we're the disruptor here. We use AI to create the value that we create. When customers buy Appian platform or solutions, they're counting on efficiency gains. We deliver some of that with AI. We're going to make the most effective use of AI technology toward efficiency gains. That's exactly what we're focused on, is finding a way to get practical value out of this terrific new area of technology. We will be the vehicle whereby our customers achieve their AI efficiency gains.

Very helpful. And then, Mark, when we think about the numbers, when do you think AI could start showing up on the revenue side of the house? Do you think that's more of a Q4 story or more of a 2024 dynamic? And then on the margin side, are there any AI investments that we should be cognizant of?

Yeah, on the first part, AI, in my view, is a pretty big sea change and a long-term opportunity for us. And it's not necessarily something that would expect in the short term on a revenue basis. But certainly, to dovetail into the second part of your question, we are making appropriate investments as part of our R&D strategy. We have had investments in the past for years. It's not like we're waking up and saying, oh, we should look at AI. It's been part of our blueprint for a long time, and we're certainly going to keep that investment in view as we move forward. Two or three years out, I think we'll still be talking about AI.

Yeah, look, there's definitely a reallocation of resources internally. With the takeoff of large language models, we definitely want to put a lot of focus behind the proper utilization of that form of AI. And so we're shuffling investments internally, but what we're not doing is bolting on a big new investment. We already have expertise. We're just reallocating internally in order to match the explosion in customer interest and the power of these products. Like Mark, I don't want to make a prediction for when it will show up in revenue, though.

Great. Thanks for taking my questions.

Thank you. At this time, I would now like to turn the conference back over to Sri Anansa for closing remarks.

Great. Thank you very much, Gigi, and thank you all for joining us tonight. We look forward to catching up with you on our next earnings call. Talk to you soon.

This concludes today's conference call. Thank you for participating. You may now disconnect.