Appian Corporation (APPN) Q1 2026 Earnings Report, Transcript and Summary

Good day, and thank you for standing by. Welcome to the Appian First Quarter 2026 Earnings Conference Call. [Operator Instructions] Please be advised that today's conference is being recorded. I would now like to hand the conference over to your first speaker today, Brian Denyeau from ICR. Please go ahead.

Thank you. Good morning, and thank you for joining us. Today, we'll review Appian's first quarter 2026 financial results. With me are Matt Calkins, Chairman and Chief Executive Officer; and Serge Tanjga, Chief Financial Officer. After prepared remarks, we'll open the call for questions. During this call, we may make statements related to our business that are considered forward-looking. These include comments related to our financial results, trends and guidance for the second quarter and full year 2026, the benefits of our platform, industry and market trends, our go-to-market and growth strategy, our market opportunity and ability to expand our leadership position, our ability to maintain and upsell existing customers and our ability to acquire new customers. These statements reflect our views only as of today and don't represent our views as of any subsequent date. We won't update these statements as a result of new information unless required by law. Actual results may differ materially from expectations due to the risks and uncertainties described in our SEC filings. Additionally, non-GAAP financial measures will be discussed on this conference call. Reconciliations to -- of GAAP to non-GAAP financial measures are provided in our earnings release. With that, I'd like to turn the call over to our CEO, Matt Calkins. Matt?

Thanks, Brian, and thanks to everyone for joining us today. In the first quarter of 2026, Appian's cloud subscriptions revenue grew 25% year-over-year to $124.5 million. Subscriptions revenue grew 19% to $160.3 million. Total revenue grew 21% to $202.2 million. Adjusted EBITDA was $26.6 million. Our weighted Rule of 40 scored 42, the highest level since we introduced the metric last year. Our go-to-market efficiency metric posted its 11th straight quarter of improvement. Appian continues to build on our success in 2025. We met or exceeded financial expectations in Q1 and raised full year guidance. Serge will share the details. Last week, Appian announced the results of a study done with the Harvard Business Review on the state of AI in the workplace. It captures this unique moment in which every organization intends to use AI, but many struggle to get value from it, especially in the most important use cases. HBR found that AI is used more for personal efficiency than it is for strategic applications. If an application is customer-facing or makes business decisions, it's probably not benefiting from AI. Appian's purpose is to bring AI into mission-critical applications, at large regulated companies where errors are not acceptable. We make AI reliable enough for such use cases by wrapping it in a deterministic framework of process technology. AI is a probabilistic technology unreliable by nature, while the most valuable use cases require complete dependability. HBR's study shows how corporate users know what's needed to make their AI reliable. 92% know they need guardrails for AI, though most have not created them. Most intend to integrate AI into process, though only 18% have done it. Organizations now understand how to equip AI for serious use cases even if they haven't done it yet. HBR's conclusion states and I quote, "The next phase of AI maturity will depend on embedding AI directly into the core of how work gets done." Appian has been embedding AI into the core of how work gets done for years, with our leading process automation technology. My conversations with customers indicate that we've helped them move faster than the market as a whole. Nearly 40% of Appian customers have purchased our AI-inclusive license tiers. Driven by AI demand, our 2026 pipeline is above our expectations and a key factor in our increased guidance for the remainder of the year. Excitement over Appian AI was evident at our annual user conference, Appian World, which took place last week in Orlando. Our theme was serious AI, meaning AI used for strategic and valuable work. Our point, of course, was that serious AI requires process. Over 1,000 customers, prospects, partners heard from Appian experts and peer organizations, including Citi, Pfizer, Merck, GE Aerospace, GE Healthcare, NASA, AARP, Regeneron, Munich Re, CIBC Mellon. Customers reported that AI transformations are increasingly a Board-level priority. AI alone operates at a low level of reliability. But with Appian's framework, AI can work and write applications at a high level of reliability. We've created technology that complements AI, enabling it to be used in the most valuable situations. Appian DocCenter is a great example of deploying AI within process. DocCenter automatically extracts data from incoming documents, then takes action accordingly. DocCenter runs at scale with over 95% accuracy, significantly higher than the 60% accuracy of traditional document recognition technology. Our customers processed more document pages in Q1 this year than they did in all 2025 combined. Production use cases span all major industries. I'll share a few customer examples. First, an international insurance company is automating processes and working to eliminate $100 million in operational costs by 2030. It named Appian its AI document intake standard after DocCenter processed complex unstructured physician statements with 98% accuracy. Next, a global medical devices company manages its order to installation processes on Appian. This quarter deployed DocCenter to automatically compare order packages against client documentation. It can now process items 80% faster. Once rolled out globally, Appian will validate 100,000 orders annually and save the firm an expected $16 million in operational costs over the next 3 years. Finally, a top oil and gas company has been an Appian customer for several years. It uses our platform to onboard customers and suppliers 70% faster than before. This quarter, its finance department chose Appian to spearhead its AI transformation and purchased a 7-figure software deal. Appian will automate the procure-to-pay process, starting with invoice payments. DocCenter will extract data from millions of supplier invoices annually and automatically reconcile them against the company's order management system. Appian will provide significant labor savings and help the company achieve its goal to reduce operating costs by $400 million by the end of 2027. Legacy modernization is a fast-growing component of our business and perhaps the most popular topic at our conference last week. C-level executives respond immediately to the promise that we can migrate their legacy apps to our modern platform. According to McKinsey, 70% of Fortune 500 software is over 20 years old. We've been doing modernization migrations for a decade with good results. The U.S. Air Force saved $80 million after modernizing its tech stack with Appian and Hitachi consolidated over 500 systems into a single central Appian application. Legacy modernization may be an idea whose time has come. New AI technology has expanded the opportunity by lowering the cost and increasing urgency. The cost is lower because natural language development is now a mainstream way to compose applications in Appian. The urgency is higher because products like Anthropic's Mythos threaten to expose security weaknesses in all applications, especially old code stacks without modern support. Many applications cannot be vibe coded written by AI alone. As I often say, code may be cheap, but mistakes are still expensive. Important applications will require a greater degree of reliability and precision, which Appian provides. We make AI enterprise-grade reliable in writing apps, just like we make it reliable in doing work. For example, a major European automotive manufacturer manages supply chain operations, finance and warranty claims on our platform. In Q1, it named Appian as its core modernization platform and purchased a 7-figure deal for more software licenses. The company's sprawling tech stack includes over 3,000 outdated and incomplete applications. Now Appian will unify the enterprise as the organization decommissions legacy systems. The manufacturer aims to reduce its application landscape by about 40% as it builds enhanced workflows on Appian. Customers have strong interest in Appian's Agentic AI. Like all types of Appian AI, our agents are informed by our data fabric and deployed within the guardrails of our process. For example, a leading telecommunications company is using Appian to unify its digital advertisement operations. This quarter, it decided to automate compliance reviews and purchased more Appian licenses. Every network and streaming provider has unique rules about when and what type of content can be positioned on their channels. Before Appian, the company validated content manually. Now Appian data fabric will unify client policies so our AI agents can reference a holistic data set. Our agents will verify thousands of ads every day and flag outliers that need human review. Early results suggest Appian agents will achieve 98% accuracy and require 33% fewer resources. The AI economy asks for transparency and openness. Appian is a long-standing believer in these values, as shown in our data fabric that unifies distributed data sources without moving them. We've embraced what I call the 3 rules of the AI ecosystem: be useful; be open; and be safe. Our technology utilizes MCP inbound and outbound. Data fabric is an ideal data source for AI agents because it is comprehensive, open, performant and secure. You can now deploy, develop -- you can now develop Appian applications without ever opening an Appian interface, entirely from an AI command line in a product like Claude or Kiro. Our AI-enabling layer is also AI agnostic, preventing AI lock-in and empowering our clients to switch AI platforms in the background without losing any of their capabilities. Appian is off to a strong start in 2026. Our position as an essential enabler of AI continues to drive business momentum as customers gain real-world value from our platform. With that, I'll hand the call to Serge.

Thanks, Matt. I'll begin with a detailed review of our first quarter results and then finish with our outlook for the second quarter and full fiscal year 2026. Starting with Q1 results. We had a strong quarter of new business driven by continued AI traction and ongoing momentum in our focus on the high end of the market. The standout performer was our EMEA region. Cloud net new ACV bookings were approximately 82% of total net new software bookings in Q1, consistent with the prior year. Appian exceeded the guidance ranges we provided on our key metrics of cloud revenue, total revenue and adjusted EBITDA. Cloud subscription revenue was $124.5 million, an increase of 25% year-over-year. On a constant currency basis, cloud subscription revenue increased 20% year-over-year. Total subscription revenue was $160.3 million, an increase of 19% year-over-year. On a constant currency basis, total subscription revenue grew 15% year-over-year. Professional services revenue was $41.9 million, up 31% compared to the first quarter of 2025. Total revenue was $202.2 million, an increase of 21% year-over-year. On a constant currency basis, total revenue grew 17% year-over-year. Our cloud net ARR expansion was 115% in Q1 compared to 112% a year ago and 114% in the prior quarter. As a reminder, we present net ARR expansion on a constant currency basis. Now let's turn to profitability. I'll be discussing our results on a non-GAAP basis unless otherwise noted. Gross margin was 74% compared to 75% from the year ago period and 73% in the prior quarter. Our subscription gross margin was 86% compared to 87% in the year ago period and consistent with the prior quarter. Professional services gross margin was 29% compared to 25% in the year ago period and 23% in the prior quarter. Total operating expenses were $125.6 million, up from $110 million in the year ago period. Adjusted EBITDA was $26.6 million, ahead of our guidance range of $19 million to $22 million and compared to adjusted EBITDA of $16.8 million in the year ago period. This outperformance relative to our guide was largely driven by greater-than-expected revenue. Net income was $19.8 million or $0.27 per diluted share compared to net income of $9.8 million or $0.13 per diluted share for the first quarter of 2025. This is based on 74.4 million diluted shares outstanding for the first quarter of 2026 and 74.5 million diluted shares outstanding for the first quarter of 2025. Turning to our balance sheet. As of March 31, 2026, cash and cash equivalents and investments were $206 million compared to $187.2 million at the end of last year. For the first quarter, cash provided by operations was $48.8 million compared to $45 million for the same period last year. In the first quarter, we purchased $21.8 million worth of our stock. Turning to guidance. Starting with the second quarter of 2026, cloud subscription revenue is expected to be between $126 million and $128 million, representing year-over-year growth of 19% at the midpoint of the range. Total revenue is expected to be between $191 million and $195 million, representing year-over-year growth of 13% at the midpoint. Adjusted EBITDA for the second quarter of 2026 is expected to be between $5 million and $8 million. Non-GAAP earnings per share is expected to be between negative $0.02 and $0.02 per share. This assumes 74.2 million fully diluted weighted average shares outstanding. For the full year 2026, our cloud subscription revenue is expected to be between $515 million and $521 million, representing year-over-year growth of 18% at the midpoint of the range. Total revenue is expected to be between $819 million and $831 million, representing year-over-year growth of 13% at the midpoint. Adjusted EBITDA is expected to range between $97 million and $105 million or an approximately 12% margin at the midpoint of the range. Non-GAAP earnings per share is expected to be between $0.94 and $1.05 or approximately 60% growth at the midpoint. This assumes 73.9 million fully diluted weighted average shares outstanding. Our guidance assumes the following. First, we anticipate our non-cloud subscription revenue to be down in the mid-single digits in Q2 related to timing of renewals versus Q3. For the full year, we expect non-cloud subscription revenue to be flat to slightly up. Second, we expect professional services revenue to grow in the high single digits in Q2 and low double digits for the full year. Third, total other income and interest expense will be approximately $3 million in Q2 and $12 million for the full year 2026. Fourth, our guidance assumes FX rates as of early May. Please note that we expect FX to benefit our reported revenue growth rate by roughly 1% in Q2 and have a neutral effect for the rest of the year. Finally, Q2 is our seasonally high quarter for marketing and event expenses, impacting our sequential EBITDA guidance. For the full year, we are raising our EBITDA guidance as we expect more than 1 percentage points of adjusted EBITDA margin expansion in 2026. Before wrapping, let me also touch on our increased share repurchase program. As most of you know, we have always been careful about dilution. Thanks to a strong start to 2026 and our increased guidance, we are in a position to increase our buyback authorization from $50 million to $100 million. We plan to execute this buyback during 2026, which will reduce our overall share count this year, driving further growth in our earnings per share. In closing, we're pleased with our Q1 results. We are excited about the opportunity ahead, and we'll continue to invest responsibly to maximize our long-term value. We look forward to seeing many of you next week at our Investor Day in New York. We'll be sharing updates on our product and strategy, and you'll have the opportunity to hear directly from our customers and partners. If you'd like to attend, please reach out to investors@appian.com. Now we'll turn the call over for questions. Operator?

[Operator Instructions] Our first call comes from the line of Steve Enders with Citi.

Maybe just to start, I want to dig in a little bit more into just the conversations you're having around Agentic AI with your customers. And I guess, where are we in terms of customers just starting to deploy agents in production? And maybe what kind of the initial conversations like, as they're beginning that and maybe moving from experimentation into actual production use cases?

I have heard lately that there have been a lot of concerns across the economy about the efficiency of agents, the return on investment that agents have provided. And I first of all want to say that our conversations are in contrast to that. I think we've been really deliberate and practical about the way that we've deployed agents, and they've been adopted as such. And we are, therefore, a high ROI agent vehicle. I've also -- I want to mention that some have considered the agent -- agentic decision-making capability to be, in some ways, a substitute for the process model's decision-making capability. And in fact, I find that agents are not substitutes but complements and need process more than any other form of AI, in my experience. Agents are -- they need the guardrails, they need the tracking. They need the support and the teamwork that process provides. I have enjoyed seeing how agents have fit into a team and a portfolio approach. And at this point, when customers ask us where they should use a process to make a decision versus where they should use an agent to make a decision, I feel like we have a clean and time-tested answer to that, which is that it depends on whether you need adaptive intelligence at that point in the process sequence, if you have a lot of ambiguity. If you have a -- an extremely large context set that can't be contained within rules, then you're going to need some adaptive intelligence. But otherwise, you should stick with process to make those decisions because it's faster and cheaper and more accurate. And best of all, of course, is to have agents at your disposal, but also have the rest of process and automated decision-making at your disposal so that you may select the appropriate tool at the appropriate moment, which I call a kind of a portfolio approach. I think the portfolio approach is going to be especially important as we go into the future and we depart eventually from this era of subsidized AI. Today, AI is underpriced, but we all know that, that can't last forever, and it's already pretty expensive. And over time, AI is going to rise to its cost of provision more or less. And when it does, there'll be all the more pressure to find a cost-effective and equally accurate manner of making a lot of these decisions. And that's where the portfolio approach that the process provides will come in. So anyway, good feedback on our agents, good usage and particularly, I think, differentiated ROI from what I understand to be happening in the rest of the market.

Okay. That's very clear, and it's great to hear. Maybe just switching gears a little bit to the outlook. It sounded like the pipeline and the build there is coming in pretty solid. Just maybe what are you seeing in terms of top of funnel, like what's driving those incremental use cases? And I guess, what does that kind of imply as we think about the guide, what's underpinning, I guess, either productivity rates or close rates and the assumptions there, especially compared to some of the volatility that we're hearing about in the macro situation right now?

Yes. Yes, we seem to be cruising through that volatility on a macro basis pretty solidly. I think what's driving our pipeline is the fact that we've got the answer to the biggest question in business now, which is how do you apply AI to strategic applications. Everybody wants to do this. Study after study shows that it's the new frontier in AI, how can you attach it to complex, error-intolerant, mission-critical regulated processes and get value, and we're doing it. Time and again, we have the answer to that question and the enthusiasm and the electricity at our show last week showed us that people are delighted with the actual returns they're getting on our investment, and they're deploying AI places they wouldn't have been able to deploy it otherwise, because of our deterministic process layer. So I think that's what's driving the pipeline is the fact that we've got a reliable answer to this large unanswered question.

Steve, the only thing that I would perhaps add is a particular area of strength is DocCenter. We see it as the first very broad use case, both across industries and geographies. It just applies to so many situations. And as Matt said, customers are leaning in, and that was also obvious last week in Orlando.

The next question comes from the line of Raimo.

Congrats the great quarter. What are you seeing at federal was -- you have a fair amount of exposure there, and that was a big discussion point, but it does seem like the world is changing there again. Can you speak a little bit what you're seeing there and how that's playing out for you?

Great. What was that critical word? It dropped out on my phone?

Federal. Federal.

Thank you. Thank you. Okay. So yes, we've seen -- I feel really good about where we stand in federal right now. This has been an arena where efficiency has mattered more than ever, where technology has been a means to an end and not just cost cutting for the last 5 quarters. This is an arena in which we can win. And I feel like we've got momentum. We've got pipeline. We've got access to legitimately larger deals than we have done in the past. I am excited about where we stand in federal and very pleased with both the -- our capabilities and our performance.

Okay. Perfect. And then one for Serge. Serge, the good profitability performance this quarter as well. So it's like a nice combination of revenue growth is getting better, but profitability also kind of improving as part of that. Can you talk a little bit about like how sustainable is that? Like what drove that? What can we expect?

Sure. So first, I'll just kind of remind you that we've been doing a good job of balancing growth and profitability for a while now. So if you look at 2024 and 2025, between those 2 years, we've expanded our margins by almost 20 percentage points. And I think of 2026 as a year in which we're building foundations for sustainable and efficient growth going forward because, first, we're returning to growth in our sales org, not because it's going to have a dramatic impact on this year's numbers, but because in order to sustainably grow the company, you need to grow your field operations. And obviously, we all have aspirations for Appian to be much bigger than it currently is. Secondly, we're continuing to invest on the R&D side, mostly in India and also investing in AI capabilities, and I really applaud our R&D leadership for using AI to rethink how to develop software. And then finally, building backbone systems and processes, including AI, especially Appian's AI, to, again, put us in a position to grow efficiently going forward. So in that context, we are showing margin expansion this year despite the incremental investments and the return to investing that we're showing, and it's absolutely sustainable going forward.

The next question comes from the line of Pat McIlwee with William Blair.

This is Jacob on for Pat. I just wanted to ask about cloud NRR ticking up to 115%. Is this being driven more by AI tier upgrades and the 25% price uplift? Or is this more customer adoption across just new workflows and more penetration within the base?

Yes, it's both. I would say it is the 2 themes that we've been talking about for over 1 year now. One is AI adoption. So we're continuing to have success in upgrading our customers to the advanced tier. Matt just mentioned that nearly 40% of our customers have some percentage of their ARR on the advanced tier. And then the second one, honestly, is just our move upmarket, selling large strategic deals. Our sales team is doing an excellent job at that, and there's still plenty to go.

Got it. And then one on go-to-market. You talked, I think it was last quarter about it being the strongest for commercial in North America in 3 years. Are you seeing some of that translate into Europe or APAC regions?

Yes. In fact, we called out Europe as the standout performer this quarter. Some of our largest deals, including a couple that Matt mentioned in his prepared remarks, actually came from that region. And look, the story with Appian and the go-to-market is that we've done a lot of work to transform our sales org, including new leadership in selected places. Our EMEA leadership started, I want to say, roughly middle of last year, and they're putting incremental rigor and focus on value in places -- in place, and we're seeing -- starting to see evidence of that in Q1.

The next question comes from the line of Sanjit Singh with Morgan Stanley.

Congrats on the cloud revenue acceleration this quarter. Matt, I thought you made a really excellent point on the era of kind of token subsidy and subsidization potentially going into a rearview either now or very shortly. I was wondering if you could unpack for us a little bit about how you guys are going to be a destination to drive more efficient AI and why that would be the case relative to some of your competitors and your peers?

Absolutely. For us, it's all about the portfolio. We've got so many ways to make a decision, so many ways to automate a job. You don't need to rely exclusively on AI, which obviously has 2 huge faults. One is that AI is not the right tool for every job. And the other is AI is the most expensive of your portfolio in many cases. So for efficiency and for accuracy sake, you want a portfolio of tools at your disposal and our approach to process does that.

Sanjit, I would just add one more thing. The portfolio applies even in the case of AI. We have customers sometimes coming to us and saying, "I want an agentic use case." And then when we unpack it, we realized that, that would not be efficient. And instead, what we have them apply is more narrow uses of AI and better control in the process that results in at least as good of accuracy and much better performance and ROI.

The next question comes from Devin with KeyBanc Capital Markets.

Matt, you briefly mentioned it in your remarks, but would love for you to just talk a little bit more and give a few highlights coming out of your Appian World Conference. What were some of the major product updates? How are customers doing those updates? And maybe just speak to how the conference has been for you guys?

Yes. Well, for me, the conference is sitting in the back room with one major customer after another rotating through. And I hear after the fact what happens on the main stage. But I do pick up a lot of enthusiasm in the hallways. I love the fact that people are talking about constructive numbers. ROI is everywhere, enthusiasm around what they're building is everywhere. We've got a very confident group of users, and they're making value. So that's all terrific. I love how it's becoming clear how they benefit from AI. In years past, I don't just mean for us, I think even more broadly around the industry, there's been enthusiasm, but on the lack of specifics, a lack of certainty around AI. And I feel like that has come into a sharp focus, and now we have dependable lines, how to use it. We know just what we're doing. DocCenter is an example, everybody can follow and the use cases are becoming crystal clear. I think it's also clear that a deterministic framework must be part of the AI stack. By the AI stack, I mean technologies that are necessary for AI to grow and succeed. Some people think there is no AI stack if there's only AI, but I disagree with that. I think that we're capable of offering something here that AI truly needs. We're not going to be the only ones offering a process orchestration deterministic framework. There will be others. There'll probably be a lot of lightweight options, but we've got a heavy weight. And it's ideal for complex and mission-critical work. I love the kind of maturing understanding of the technologies that it will be necessary to deploy AI successfully and to expand with it. And that's another thing that we have a lot to say to and that we're going to benefit from in concert with our customers as we grow.

I appreciate the highlight there. Really great to hear. And then maybe just one quick one for Serge. Really strong start to the year here with 25% cloud subscription revenue in the quarter. When I look at kind of the implied second half cloud guide, it seems like you're expecting a bit of a deceleration there. Can you walk through some puts and takes there? Why couldn't we see the strong high teens, 20% plus growth kind of sustaining into the second half year, just given the strong pipeline commentary you guys have been talking about?

Yes. So I would say 2 things. One, we're happy to be able to raise guidance for the full year this early on, and we raised it from 16% to 18% at the midpoint after the first quarter here. And then as I think about sort of the shape of that growth, maybe the most helpful way to think about it is we did just do 25%, but on a constant currency basis it's 20% and we're very happy with that number. It's the fastest in 2 years for us. But we don't see very much currency benefit for the rest of the year. So I think of comparing that 20% for the -- in the first quarter compared to 18% for the full year, and that hopefully gives you a little bit of a better sense in terms of the linearity, if you will.

[Operator Instructions] The next question comes from Derrick Wood with TD Cowen.

This is Cole Erskine on for Derrick. Matt, you talked about MCP access to the platform and how customers can use Appian and the data fabric without ever going directly into the platform. I mean, can you just talk about how this -- how you're seeing this change to usage patterns so far? And then on the economic side, is there any different puts and takes on monetization if you're -- if a customer is using Appian through Claude interface versus your first-party?

Yes. Okay. Well, let me start with just how the ecosystem is shifting in the AI era. I see a enterprise future with fewer rigid predefined lines of communication and more fluid, unpredictable -- It's like we're going to take all of our kind of boxes and institutions and blend them up or make a primordial soup out of all of these entities across the enterprise. Therefore, I think every object has the responsibility to be ready to field questions or ask questions as part of improvised networks of communication. So that's our intent with Appian to be very open and transparent and always extremely secure using credentials, et cetera. So we're a full participant in that kind of economy. And it is extraordinary now that you can develop an entire Appian application from front to back without ever opening an Appian interface. That may not be the best way. I would say that is not the best way to develop an Appian application, but it is possible. And the fact that it's possible is a demonstration of just how open we've made this product. I also want to point out just how valuable data fabric will be as a means to survey the entire enterprise worth of data for future agents. As agents get more savvy about where they can find data and where they can get it in a performant manner and interact with data, they'll focus in on those data providers that can give them more than one silo at a time, and they can give something with a fast response time. So we're well positioned to be part of that emerging ecosystem. So that -- we're excited about that. As for how you monetize it, well, I think it's important you just put a charge on all external inbound requests. So that's how we do it.

Thank you. As I'm showing no further questions, this does conclude the question-and-answer session. Thank you for your participation in today's conference. This concludes the program, and you may now disconnect.