Appian Corporation (NASDAQ:APPN) Q1 2025 Earnings Call Transcript

Appian Corporation (NASDAQ:APPN) Q1 2025 Earnings Call Transcript May 8, 2025

Operator: Good day, and welcome to Appian’s First Quarter 2025 Earnings Conference Call. All participants will be in the listen-only mode. [Operator Instructions] After today’s presentation, there will be an opportunity to ask questions. [Operator Instructions] Please note this event is being recorded. I would now like to turn the conference over to Jack Andrews, Vice President of Investor Relations. Please go ahead.

Jack Andrews: Good morning and thank you for joining us. Today, we’ll review Appian’s first quarter 2025 financial results. With me are Matt Calkins, Chairman and Chief Executive Officer; and Mark Lynch, Interim 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 2025, 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 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?

Matt Calkins: Thanks Jack, and thanks everyone for joining us today. In the first quarter 2025, Appian’s cloud subscription revenue grew 15% year-over-year to $99.8 million. Subscriptions revenue grew 14% to $134.4 million. Total revenue grew 11% year-over-year to $166.4 million. Our cloud subscription revenue retention rate was 112% as of March 31. Adjusted EBITDA was $16.8 million, a strong follow up to the prior quarter’s adjusted EBITDA of $21.2 million and a continued demonstration of our inherent earnings potential. We held our annual conference last week, Appian World. Our focus was squarely on AI and AI agents and how AI can be deployed inside a process to deliver practical value. I appreciate the many customers who spoke about their experiences with Appian, the value they created using Appian AI and the success they achieved.

Speakers from Aeon, NASA and MagMutual shared stories of how their organizations optimized processes with Appian. Neuberger Berman revealed it onboards tens of billions of dollars in funds faster with Appian. Hitachi reported reducing operating expenses by 20% using Appian. Acclaim Autism uses Appian to ingest medical documents, accelerating its patient intake process by 83%. My keynote was about bringing AI to work. By that I mean finding the place in your enterprise where work is heaviest and most important, and deploying AI there. We focus on AI the worker, not AI the helper. In order to make AI a worker, you must integrate AI into a business process, because that’s how the most critical work is done, by teams taking coordinated action. We don’t believe in asking AI to make staggering leaps of creativity, not in 2025 anyway.

Instead, AI is for doing regular work with superhuman efficiency, things like document intake and response, which AI can do faster and better than anyone else. My favorite conference session was called Saving Millions with Boring AI because it pretty much sums up our approach to AI. Straightforward, even boring, and immensely productive. We focus on practical results over hype. But don’t let our use of the word boring fool you. We’re getting incredible results. 70% of our cloud customers have adopted AI. We grew year-over-year production AI usage last quarter by 7.9x, not 7.9%, 7.9 times. We had more AI usage in Q1 than in all 2024 put together. It’s natural that the focus of the AI revolution would shift to supporting technologies like processes.

The major AI models are convergent. The most important decision in AI applications may be not which AI you use, but how you deploy it. Our belief, as you know, if you’ve heard me before, is that AI should be deployed in a process. In an Appian process, AI is easier to deploy, safer and more powerful. Appian makes AI easy to adopt. For example, a leading Australian insurer deployed an application to ingest documents and automate underwriting processes using Appian AI. Before Appian, hundreds of underwriting specialists spent days manually processing quotes with limited accuracy. Now, in minutes, our AI classifies documents and extracts data with over 96% accuracy so the insurer can quickly open and progress cases. Customer expects to run these processes 50% faster and generate millions more dollars in revenue annually.

Last year, Appian launched a multi-tiered pricing model that allows us to monetize AI and other exclusive features. Since then, nearly half of our new logos have purchased the AI inclusive upper tiers. Revenue from these AI inclusive tiers more than doubled in Q1 relative to Q4, rising to $9 million. This is not yet a large share of our quarterly subscriptions revenue, but it demonstrates our early moves to monetize AI and our customers willingness to pay for it. Our customers become more efficient when they use our platform. An association of U.S. financial regulators is one example. This group is an existing Appian customer. Its state regulators process thousands of product filings annually, 50% faster when using our platform. This was even without AI.

In Q1 it expanded its use with a seven figure software deal to upgrade its existing licenses to our new pricing model and deploy Appian AI. Our AI classifies each document and extracts pertinent data from each filing. Now the group expects to eliminate manual verifications and save tens of thousands of additional labor hours annually. The central message of my keynote involved AI agents. I explained the three primary behaviors of an agent. It thinks, it acts and it learns. And I explained why Appian agents have an edge in all three behaviors. I’m going to walk through them right now briefly. First of those three behaviors is thinking. Thinking refers to exploring data with repeated queries of disparate sources to decide on the best course of action.

The more data an agent can explore, the better it will think. Appian’s data fabric allows the agent to roam the entire enterprise of data not limited to a single silo or data source. Our data fabric is industry leading functionality adopted by 97% of our incoming cloud users. Our data fabric gives agents more than universal access. It also grants them speed because our queries are automatically performance tuned and security because we run those queries with the appropriate user’s credentials. Due to a surge in AI related usage, data fabric queries are up 166% year-over-year to nearly 7 billion queries in Q1. Second part of my behavior list is acting. Acting is the second thing that these agents do and it refers to an agent implementing its decision.

Appian’s agents act exclusively through processes. That’s all they can do is launch processes. No surprise there, as we are a process company. Processes are a great way to take action. They are complex and compound actions, potentially triggering dozens of separate work items by dozens of different workers. So they are powerful, but they are also safe. Processes are auditable and predictable. They provide guardrails. If processes are the best way for agents to take action, Appian has a distinct Advantage. We run 16 billion transactions per day on our processes. Finally, there’s think, there’s act, and there’s learn. So last one is learning. Learning means that an agent benefits from the knowledge of past results. If you want to learn from past results, you must start by remembering them and Appian monitors everything that happens in our processes.

How much time did it take? How much did it cost? Was it successful? We track all these things. Our process mining capability gives us an edge in collecting data for the benefit of our agents. The more you know, the more you can learn. For example, a large U.S. healthcare system will use Appian to simplify operations for hundreds of medical facilities. It will start by analyzing a series of patient focused processes like medical procedure pre-authorizations and denials to reduce overhead costs by 20%. Appian Data Fabric will consolidate data from a dozen systems so the group can use our process mining tools to identify key bottlenecks. The group will use these insights to prioritize an IT roadmap of workflows to automate with our platform. Appian does business in the United States public sector.

We have a large presence in the federal space and are thus exposed to whatever disruption DOGE may create. But we are also tightly associated with DOGE’s primary virtues, efficiency and modernization. We remain cautiously optimistic about the evolving opportunity. In Q1, our Federal Government bookings, including both the net new software and services, grew 59% compared to the same period last year. Appian has a long history of delivering value within the government. The Department of Labor, for example, saves tens of millions of dollars annually using Appian. Appian applications are mission critical. The government procures $464 billion in annual budget on the Appian platform. We offer a solution called Government Acquisition Management or GAM.

GAM helps agencies automate highly regulated processes for procuring goods and services. Last year Appian launched ProcureSight to complement the suite. ProcureSight is an AI driven website. It applies AI to several major public data sets so government professionals can glean insights from past procurements to help generate new ones. Over 80 federal agencies and sub-agencies use the service today to make their procurements more cost effective. We continue to sign new customers and win big expansions in our key verticals. Here are some examples. First, a U.S. civilian agency purchased a seven figure software deal and became a new customer this quarter. It selected our platform to manage investigations for tens of thousands of mail related crimes annually.

Before Appian, the Group manually consolidated case files because its legacy system was disjointed and incomplete. Now Appian Data Fabric will seamlessly integrate data from dozens of systems so federal agents can focus on advancing investigations. We won this competitive deal because we were the only vendor to meet all the customer’s requirements during our custom demo. Next, a U.S. Agency supporting the Department of Defense catalogs and manages nuclear inventory using Appian. This quarter it chose to modernize its procurement office and purchased our GAM solution before contracting officers manually tracked requirements on spreadsheets and custom tools. Now they’ll process hundreds of millions of dollars of annual procurement budget on Appian.

We won this deal because the customers peer organizations recommended our solution. My final story is about a top Australian bank that became a new Appian customer this quarter. It will use our platform to modernize customer service processes like credit card disputes and customer account updates. Appian AI will ingest nearly 75 million document pages annually and Appian Data Fabric will consolidate data from all related systems into a single workflow tool so service agents can reduce their SLAs from hours to minutes. It’s important to me that Appian’s investors know Appian’s intentions, so I’ll share with you now two essential internal metrics which we’ll report on quarterly going forward. The first is what we call weighted rule of 40. This is the most important number that we manage the company towards.

It’s a combination of growth and margin, like a typical rule of 40, but we weight growth twice as much as margin. In the current quarter our weighted rule of 40 score is 27, which is the sum of 4/3 cloud subscription growth plus 2/3 adjusted EBITDA margin. I explained the math so you can see that the factors add up to 2 just like in a regular rule of 40 metric. Some Appian executives have weighted rule of 40 targets today and all of them will over the next few quarters. Appian’s other top objective is to increase sales and marketing efficiency. This became my primary objective in 2023 and after much work we’re seeing some results. This Q1 our net new bookings per sales rep rose more than 30% compared to the same period last year. We want to share our progress with you using a new metric.

See Slide 4 in the presentation called GTM Productivity, that’s go-to-market Productivity. It measures the bang for our buck in sales and marketing. The numerator is the sum of total revenue and the quarterly changes in short term deferred revenue over trailing twelve months. The denominator is trailing twelve months non GAAP sales and marketing expenses as you’ll see on the chart, we’re showing steady progress. Appian hired Serge Tanjga as our new Chief Financial Officer starting later this month. Serge has over 20 years of financial experience, most recently as Senior Vice President of finance at MongoDB, where he led financial planning, strategic finance, business operations and analytics, and then as their Interim CFO. I’m excited to welcome him to Appian’s executive team.

I thank Mark lynch for serving as our interim CFO during this search. He’ll remain on Appian’s Board of Directors. With that, I’ll hand the call over to Mark for a deeper discussion of our financials. Mark?

Mark Lynch: Thanks Matt and thank you everyone joining us today. I’ll review the financial highlights for the quarter and then we’ll provide guidance for Q2 and the full year 2025. Appian exceeded the guidance ranges we provided on our key metrics of cloud revenue, total revenue, and adjusted EBITDA. Cloud subscriptions revenue was And adjusted EBITDA cloud subscriptions revenue was $99.8 million, an increase of 15% year-over-year. Total subscriptions revenue was $134.4 million, an increase of 14% year-over-year. On a constant currency basis, total subscriptions revenue grew 15% year-over-year. Professional services revenue was $32.1 million, flat growth compared to the first quarter of 2024. As a reminder, services revenue can be volatile quarter-to-quarter.

We continue to expect professional services revenue to decline as a percentage of total revenue over the long-term. Subscriptions revenue represented 81% of total revenue compared to 79% in the year ago period and 82% in the prior quarter. Total revenue is $166.4 million, an increase of 11% year-over-year. On a constant currency basis total revenue grew 12% year-over-year. Our cloud subscriptions revenue retention rate was 112% as of March 31, 2025 compared to 120% a year ago and 116% in the prior quarter. We continue to target a cloud subscriptions revenue retention rate of 110% to 120% on a quarterly basis. Our international operations contributed 36% of total revenue compared to 37% in the year ago period. Cloud net new ACV bookings were approximately 82% of total net new software bookings in Q1 consistent with the prior year.

Let’s turn to profitability metrics. Non-GAAP Gross margin was 78% compared to 76% in the year ago period and 80% in the prior quarter. Our subscriptions non-GAAP gross profit margin was 89% compared to 90% in both the year ago period and prior quarter. This margin remains best-in-class in enterprise software. Professional services non-GAAP Gross margin was 30% compared to 25% a year ago period and 31% in the prior quarter. Total non-GAAP operating expenses were $114.8 million down 2% from $117.3 million in the year ago period. Adjusted EBITDA was positive $16.8 million versus our guidance of positive $8 million to $10 million and compared to an adjusted EBITDA loss of $1.3 million in the year ago period. This outperformance relative to our guide was largely driven by taking a measured approach to hiring, prioritizing low cost regions for hiring and by greater than expected term license and services revenue.

Non-GAAP net income was $9.8 million or $0.13 per diluted share compared to a non-GAAP net loss of $4.9 million, or $0.07 per share for the first quarter of 2024. This is based on 74.1 million diluted shares outstanding for the first quarter of 2025 and 73.3 million diluted shares outstanding for the first Quarter of 2024. Turning to our balance sheet, as of March 31, 2025, cash and cash equivalents and investments were $199.7 million, compared with $159.9 million at the end of last year. For the first quarter, cash provided by operations was $45 million, compared to $18.9 million for the same period last year. Total deferred revenue was $262.5 million as of March 31, 2025, an increase of 16% from the year ago period. As we stated on past calls, the majority of our customers are invoiced on an annual upfront basis.

We also have large customers that are billed quarterly or monthly. Due to the variability of our billing terms, changes in our quarterly deferred revenue are generally not indicative of our business momentum. We continue to believe cloud subscriptions revenue is a better indicator of our business momentum than billings or remaining performance obligations RPO. The latter metrics can fluctuate based on the timing of invoicing, seasonality of self-managed license revenue, and the duration of customer contracts. The true scale of the business is represented by subscriptions revenue, which includes support and all software subscriptions revenue regardless of whether the customer deploys to the Appian cloud, their private cloud or on-prem. Before discussing guidance, I’ll share a few observations about macroeconomic and business conditions.

The U.S. dollar has weakened since we last provided guidance which now gives Appian a currency tailwind. Appian exceeded the high end of our Q1 guidance for cloud revenue and toll revenue, and at this point in the year we have not seen any material changes in our sales pipeline or the cadence of our business. Given the macroeconomic uncertainty, changes within the Federal Government and thus a wider range of potential outcomes, we’re taking a prudent approach to guidance for the remainder of 2025. For the second quarter of 2025, cloud subscriptions revenue is expected to be between $101 million and $103 million, representing year-over-year growth between 14% and 16%. Total revenue is expected to be between $158 million and $162 million, representing year-over-year growth between 8% and 11%.

Adjusted EBITDA for the second quarter of 2025 is expected to be between negative $5 million and negative $2 million. Non-GAAP earnings per share is expected to be between negative $0.15 and negative $0.11. This assumes 74.8 million fully diluted weighted average shares outstanding. For the full year 2025 we are increasing the high end of our previously stated guidance range regarding cloud subscriptions revenue and total revenue, while maintaining the original low end of those guidance ranges. We’re also increasing our overall adjusted EBITDA range for the year. For the full year 2025, cloud subscriptions revenue is expected to be between $419 million and $423 million, representing year-over-year growth of between 14% and 15%. Total revenue is expected to be between $680 million and $688 million, representing year-over-year growth of 10% to 12%.

Adjusted EBITDA is now expected to range between positive $40 million and $46 million. Non-GAAP earnings per share is expected to be between $0.18 and $0.26. This assumes 75.1 million fully diluted weighted average shares outstanding. Our guidance assumes the following. First, we expect Q2 professional services revenue will be flat compared to a year ago. For the full year we expect professional services revenue to be approximately flat or increase by a low single digit range compared to a year ago. Second, we anticipate term license revenue will decrease by low double digit percentage on a year over year basis as we anniversary a difficult comparison from a strong Q2 2024. Third, we expect Q2 adjusted EBITDA to be lost due to the combination of term license seasonality and the cost of running our annual user conference Appian World.

Fourth, total other income and interest expense will be approximately $3.5 million in Q2 and $14 million for the full year 2025. Fifth, capital expenditures will be between $1 million and $1.5 million in Q2 and between $3 million and $4 million for the full year 2025. Finally, our guidance assumes FX rates as of May 2, 2025. Now we’ll turn the call over for questions. Operator?

Q&A Session

Operator: Certainly. [Operator Instructions] The first question comes from Sanjit Singh with Morgan Stanley. Please go ahead.

Sanjit Singh: Thank you for taking the questions and congrats on the continued progress on the profitability front. That’s really nice to see. I wanted to ask about the good government performance this quarter. To what degree was there any sort of potential pull forward into Q1 ahead of some of the uncertainty around ordering patterns due to DOGE? And then as we think out into Q3, the Federal Government and the fiscal year spend, what sort of the baseline assumptions that you guys are making with respect to the UN Federal budget spending periods?

Matt Calkins: All right, thank you for the question. First of all, I don’t believe pull forwards to have been a meaningful factor in Q1. I’m not aware of any pull forwards. So I hesitate to say I’m sure it was zero, but I don’t believe it to be meaningful. With regards to Q3, we understand that there’s a higher variance this year on the federal business than there have been in previous years. But so far we’re on the good side of that variance, and I think that we’re keeping possibilities open. We’re cautiously optimistic about how Q3 will be.

Sanjit Singh: Awesome. That’s great to hear. And then just as a follow up, if I look at sort of the cloud net retention rate certainly within the range that you guys have talked about historically, 110% to 120%. It did dip down more meaningfully in Q1 and doesn’t sound like that’s coming from the government side of the House. Any sort of spending hesitation you’re seeing on the enterprise commercial side of the business that drove that that net retention rate down 4 points quarter-over-quarter?

Mark Lynch: Not really. First of all, it’s a reminder that this is a trailing metric. It’s basically 12 months over 12 months. So it’s backward looking. Basically a couple of things happen. There were some down sells in Q1 of 2024 that are working their way through the calculation now and they’re predominantly unrelated downsells and also we had some revenue growth rates and some of the customers level off during the recent 12-month period. So those kind of conspired to lower the rate a little bit.

Sanjit Singh: I appreciate the color. Thanks, Mark.

Operator: Our next question comes from Raimo Lenschow with Barclays. Please go ahead.

Raimo Lenschow: Perfect. Thanks for all the clarity on federal and congrats on the quarter. Matt, I wanted to ask on AI and the new agentic world, how do you like, and I appreciate you as a founder, you always think more bigger picture than a lot of other guys, how do you think this new world is going to play out? I mean you clearly have a lot of success, but there’s obviously a lot of noise, marketing noise in the market of people. Everyone is doing agents now and agentic, et cetera. Like how do you think like what’s ultimately the big thing for a customer and how you fit in there? And then a follow up for Mark.

Matt Calkins: Yes, this agent’s topic, it’s both the most important application of AI and as such an exceptionally worthy topic for conversation and development. And at the same time it’s overstated and the market is still dominated by more hype than results. And so we’re at pains to differentiate ourselves from that and the fact that we rely mostly on customer stories to make our point and that we use words like boring, that this is all an intentional sort of disassociation that we’re trying to make between our approach, which is results centric and customer focused, and using AI to practical effect versus the sky high hyperbole that we’re hearing from some vendors. I keep figuring that now is the moment when the hyperbole is going to melt away and people are going to care about actual results.

And I think that we stand to benefit when that change happens. When people start allocating, sorry, people start paying attention to agents for their impact. Agents are actors. They’re the actors of the AI world. AI should be taking action. We believe in AI the worker. This is exactly what we’re here for, is to use AI to do work. But that work has to be regulated and audited and guardrailed and provisioned with information and tracked. And so you need all that structure. You need all the structure around AI. You can’t just make an AI agent and let it loop loose in the enterprise. And therefore I view the process infrastructure that we provide as a prerequisite for productive application of AI agents. Simply a prerequisite. And to the degree that anyone else is going to make value with their agents, it’s going to be because they approximate the functionality, even if they don’t achieve the functionality that we’re providing with our process infrastructure.

Raimo Lenschow: Okay, perfect. And then one quick one from Mark. Was there anything on the, you know, like, I know billings is not really a measure that you focus on, but, like, some of the investors are still kind of paying attention here. Was there anything in Q1 that kind of impacted billings in terms of timing, et cetera? Thank you.

Mark Lynch: Nothing really to call out.

Raimo Lenschow: That’s clear. Thank you.

Operator: The next question comes from Steve Enders with Citi. Please go ahead.

Steve Enders: Okay, great. Thanks for taking the questions this morning. I guess to start, I mean, good to hear the – on the AI side, good to hear the solid usage expansion year-over-year. And I think it was pretty clear coming from the conference what that was looking like. But I guess I just want to ask on, how you’re feeling about incremental kind of monetization. I think you called out $9 million or so in the quarter coming from the AI tiers that you have available, but just how do you feel about that usage that you’re seeing driving incremental revenue opportunities and adoption of those plans moving forward?

Matt Calkins: Yes, I am pleased with the willingness of customers to spend on AI. I think there’s a recognition that this is creating great value, and so that’s moving along nicely. Partly you could make a case for not even trying to monetize at this point in the life cycle of a feature as powerful as AI. I think we’re moving toward monetization a little sooner than I might otherwise planned, just to try to create a demonstration of the tangibility of the results we’re creating, because I feel like we need that contrast with the market. We want to show that this is real and that our customers appreciate it. So while I could understand not trying to monetize it, I also think that it’s a good idea for us to demonstrate that in order to just make a statement.

And yes, the value is there for sure. It’s wonderful value. As I estimated last quarter, I feel like our TAM has doubled in the wake of AI, which is the best thing that’s ever happened to the process automation industry.

Steve Enders: Right. No, that’s very clear. Great to hear. And then just on new, with Serge coming on board and new CFO starting later this month, I guess what’s kind of the mandate or the key area of focus for him as he starts to get ramped up in the role? And I guess it’s kind of a piece of that? How are you kind of viewing the ability to drive margin or kind of the levers to drive margin moving forward here?

Matt Calkins: Yeah, let me say I’m really excited to have Serge coming on board. He’s an exceptional addition to our team. I don’t want to preempt our strategy by talking about it right now. I think there’s a lot of great opportunities where we’re going to make substantial progress and I see him as a contributor across the board. Yes, let me just stop at that.

Steve Enders: Okay, perfect. Thanks for taking the questions here.

Operator: Our next question comes from Jake Roberge with William Blair. Please go ahead.

Jake Roberge: Yes, thanks for taking the questions, and yes, great to hear that those AI SKUs hit $9 million in the quarter. Can you talk about the use cases or areas of the platform that are driving the most demand on that front? And then is there any sense of how large of a pricing uplift you can see for those solutions on just a per customer basis?

Matt Calkins: Yes, that’s right. Well, we’ve got it priced at 25% uplift and that may fluctuate, but right now that’s our easy. We’re just asking 25% to add AI. As for the primary use cases, well, they’re, as I said in the comments, they’re regular work. They’re regular work that otherwise could be done in a rote manner. But AI is just so terrifically good at it. It’s processing documents and gathering information and making simple decisions that you might have otherwise tried to delegate to a person or a business rule set intake, it’s just terrific at document intake, it can read anything at this point. It can read ripped receipts or handwritten notes or emails or faxes or whatever you’ve got coming into your organization. It can respond, it can sort, it can extract data.

The theme here is that these are route jobs, these are straightforward, simple jobs done at high volumes with exceptional efficiency. As opposed to a lot of the stories you hear about how AI is supposedly supposed to be used towards out thinking people. I couldn’t disagree more with that. Right now. AI is a fantastic worker to place in the middle of the heaviest work and the most important work that your organization does. That’s where we want to put it.

Jake Roberge: Okay, that’s helpful. And then data fabric queries, I think we’re up 166%. I think you start monetizing that solution when customers connect it to multiple data sources. So can you talk about how that’s progressing? And then there’s also some other players in the market that are obviously talking about other data fabric solutions. So can you help us understand how your data fabric compares and contrasts to those?

Matt Calkins: It is so important to emphasize how our data fabric is different, because the need for a data fabric has become so important. Now, everyone is using the term, but what they have is not in general what I would have called a data fabric. We are talking about a semantic layer, similar to a virtual database that allows you to interact with data objects across the enterprise as if they were local objects. The semantic layer makes them local effectively. They can be viewed and queried and manipulated and combined in a local manner. It’s not just a layer of integration, it is far more than that. It’s a semantic layer that makes everything you integrate into a local addressable object. Secondly, it’s read and write. Third, it’s performance tuned.

Fourth, there’s a security layer, so you’re running queries under variable credentials depending on who’s answering the question. This is probably our best feature, along with process itself and the integration of AI with process. Let’s put this in some kind of a hall of fame top three features. It’s an extraordinary piece of functionality and it is strictly differentiated from anything on the market today that goes by the name of data fabric that I’m aware of.

Jake Roberge: That’s helpful. Thanks for taking the questions.

Operator: Our next question comes from Nick Altmann with Scotiabank. Please go ahead.

Nick Altmann: Awesome. Thank you, guys. I wanted to circle back to the $9 million of AI revenue. How are you guys thinking about contribution from AI in 2025? And can you just maybe talk about the net new ACV that’s being driven by AI just to kind of help us think about where that can shake out in 2025?

Matt Calkins: Yes, that’s right. Well, we’re going to continue our push to bring customers to the higher tiers, the AI-laden tiers. We’ve done that mostly focusing on new customers over the past year. We’re broadening that into a campaign to bring existing customers to higher tiers as well. Though, as you saw from my notes, a few have already made that jump. We are also going to transition and our whole industry is going to transition away from per seat pricing. That’s my prediction. Because per seat pricing is going to move in the opposite direction with AI success. So we’re going to need to price by something else. It could be nodes, it could be cases, it could be consumption of some sort. And within a solution or a highly understood context, it could be value or value correlates.

So we’re all going to be adopting different pricing mechanisms in order to capture AI as an upside instead of effectively having it as a downside as it removes necessary seats. So there’s going to be a little bit of a pricing transition across this industry this year. And we’re thinking a lot and carefully and we’re on the way to making that careful transition.

Nick Altmann: Okay, great. That’s helpful. And then the net new bookings per sales rep up more than 30%. That’s encouraging. And we’re starting to see some of those efficiencies show up in the margins. I guess my question is like, how durable do you think some of those productivity gains are through the rest of the year? Because on one side they’re very encouraging and can help out that weighted rule of 40 target you outlined. On the flip side, you guys are relatively early in kind of running a leaner go-to-market motion. Maybe some of that pipeline was generated when you had a larger sales force. So any color you can provide on kind of how durable those sales productivity gains are as we get through the rest of the year, I think that’d be really interesting. Thanks.

Matt Calkins: Great. Well, I don’t wish to quote any targets on the metrics that we’ve recently revealed, including the ones that we will be reporting on next quarter as designated. I would sooner classify them as durable than nondurable according to your terms. I don’t believe that they are dependent upon a larger pipeline gathering force. I believe that they instead stem from recent innovations. Superior efficiency, better account targeting, larger accounts, selling higher conveying value first. I think that they’re the new habits and the new seriousness and tension that we have brought to the sales organization, the terrific professionalism that we are bringing, these are the real factors and these are enduring factors.

Nick Altmann: Great, thank you.

Operator: We have our next question from Derrick Wood with TD Cowen. Please go ahead.

Unidentified Analyst: Great. Thanks guys. This is Cole on for Derrick. I just want to start off on the go-to-market. I mean, it sounds like you’ve made some good progress in efficiencies. I’m just wondering how much of that is coming from this renewed channel focus and narrowing the scope of channel partners versus direct reps. Thanks.

Matt Calkins: Okay. The narrowing of partners is an example of something that was very successful. Demonstrably, measurably successful last year. We motivated a small group of our most trusted partners to seek business with us and it dramatically expanded the partner generated pipeline in 2024. We continue that because it has worked so well. I saw more evidence of how well it was working last week at Appian World. Our partners are enthusiastic. Those that are focus partners are working hard to maintain that designation. Those that are not are working hard to gain it. We also have another category called champion partners that lead us into a new market. And I see a boom of interest for partners, especially if they’re not focused partners on becoming champion partners so that they can receive our attention in at least one market. This has been a great motivational tool, a great alignment tool with our partners. We will certainly keep it up.

Unidentified Analyst: Great, thanks. And then just to follow-up on the GAM Suite, could you just remind us, is there any sort of an ACV uplift that comes with that and if so, what would that be? Thanks.

Matt Calkins: Yes, well, the GAM Suite has a price. It isn’t so much an uplift, it’s a separate product and the GAM Suite has a price. I don’t know if it’s published, it might be on GSA, but it’s substantial. If you want the GAM Suite, it’s going to be a seven figure for sure, a seven figure a year proposition, no matter how small your organization. So it’s a meaningful sale when we place it.

Unidentified Analyst: Appreciate it. Thanks.

Operator: The next question comes from Devin Au with KeyBanc Capital Markets. Please go ahead.

Devin Au: Great. Good morning, Matt. Good morning, Mark. Thanks for taking my questions here. I want to first off, maybe just start with some of the exciting product announcements that came out of Appian World this year. When I talked to the customers at the conference, seems like Intelligent Document Processing and Extraction, that has been a really widely adopted product among your customers. Could you maybe share more on what’s been driving success in adoption there? Any learnings you can kind of port over to some of the new AI agent offerings that you can maybe replicate the success you’ve seen at IDP?

Matt Calkins: I’m glad to hear you enjoyed the product announcements at Appian World. I was incredibly excited. I felt like all four of the major features that I announced could have been the headline feature at a typical annual conference. Of course, they were all AI related, most of them were agent related. But there was also the one composer that allows you to create a new application through the use of AI, having AI be the author of the application. And that was exceptionally well received and I can tell you that early users absolutely love that. That’s been receiving some of the best feedback I’ve ever seen with regards to IDP or Intelligent Document Processing. This has long been our number one AI use case. Like literally for years this has been number one and we made it sharply better in this latest round of advancements.

IDP used to be a feature that you trained per document. So if you had a certain format of document coming in, you would train the AI to recognize it and know where to extract different pieces of information. The new version, you don’t have to train on any format of document. It just figures it out so you can give it something in handwriting or in a novel format or an email or whatever it is. It could be in the wrong language and AI is just going to, going to figure it out. And the level of accuracy with which it does that is astonishing. It’s both more adaptive and more accurate than anything we’ve been able to offer in the past. And customers really love it. I build it in the conference as Read Anything I said. You call it IDP, but you could also just call it read anything.

Devin Au: I appreciate the context. They’re really helpful. And then just a quick follow-up. I – do you want to dive a little bit deeper into your comments around public sector? It seems like things are still going well and you were cautiously optimistic and you mentioned bookings growth of 59% in the quarter. I mean how did kind of that bookings performance compare to your internal expectations in the quarter? And any color on how that figure kind of compared last quarter, maybe last year’s. Anything you can share would be helpful. Thank you.

Matt Calkins: Yes, well it is a year-over-year comparison of course, and I would say that that exceeded my expectations. But I’m sticking with cautious optimism. That’s what we said word for word last quarter and I think it’s the right position to take right now and I’m glad that the numbers are bearing us out. But I don’t want to get out ahead of them. I want to just let this story tell itself.

Mark Lynch: Another factoid out there is that the federal revenue, Federal Government revenue grew year-over-year 21% versus the total revenue for Appian during the quarter was 11%. So that strong revenue growth as well.

Devin Au: Got it. Really appreciate the color. Thank you.

Operator: Thank you. We have no further questions at this time. The conference has now concluded. Thank you for attending today’s presentation. You may now disconnect.