Doximity, Inc. (DOCS) Q1 2027 Earnings Report, Transcript and Summary

Ladies and gentlemen, thank you for standing by. My name is Abby, and I will be your conference operator today. At this time, I would like to welcome everyone to the Doximity First Quarter 2027 Earnings Conference Call. [Operator Instructions] And I would now like to turn the conference over to Perry Gold, Senior Vice President, Investor Relations. You may begin.

Thank you, operator. Hello, and welcome to Doximity's Fiscal 2027 First Quarter Earnings Call. With me on the call today are Jeff Tangney, Co-Founder and CEO of Doximity; and Matt Sonefeldt, CFO. A complete disclosure of our results can be found in our press release issued earlier today as well as in our related Form 8-K along with a copy of our prepared remarks, all available on our website at investors.doximity.com. As a reminder, today's call is being recorded, and a replay will be available on our website. As part of our comments today, we will be making forward-looking statements. These statements are based on management's current views, expectations and assumptions and are subject to various risks and uncertainties. Actual results may differ materially and we disclaim any obligation to update any forward-looking statements or outlook. Please refer to the risk factors in our annual report on Form 10-K and any subsequent Form 10-Qs and other reports and filings with the SEC that may be filed from time to time, including our upcoming filing on Form 10-Q. Our forward-looking statements are based on assumptions that we believe to be reasonable as of today's date, August 6, 2026. Of note, it is Doximity's policy to neither reiterate nor adjust the financial guidance provided on today's call unless it is also done through a public disclosure such as a press release or through the filing of a Form 8-K. Today, we will discuss certain non-GAAP metrics that we believe aid in the understanding of our financial results. A historical reconciliation to comparable GAAP metrics can be found in today's earnings release. Finally, during the call, we may offer incremental metrics to provide greater insights into the dynamics of our business. These details may be onetime in nature, and we may or may not provide updates on those metrics in the future. I would now like to turn the call over to our CEO and Co-Founder, Jeff Tangney. Jeff?

Thanks, Perry, and thanks, everyone, for joining our first quarter earnings call. Today, I'll cover 4 things: our financials, AI study results, usage growth and commercial AI progress. First, our financials. Revenue growth reaccelerated to $157 million in Q1, up 7% year-on-year. Adjusted EBITDA was $75 million or a margin of 48%. Respectively, these were both beats of 3% and 8% versus the high end of our guidance. As you'll hear again shortly from our CFO Matt, this is our AI investment year. We're proving you can still post best-in-class software margins while investing heavily in clinical AI. We're leaning in as we see a once-in-a-generation opportunity to build the new AI age of medicine. To that end, I'm proud to report that we're seeing record AI usage while topping the first large-scale independent head-to-head trial of clinical AI vendors. A few weeks ago, a team of 57 researchers led by 29 physicians from Stanford and Harvard published NOHARM, the first-ever independent study of 24 clinical AI models and how they perform in 1,100 real-world patient cases. It's the kind of rigorous independent physician-led research that we need more of. Our Doximity Ask product led among U.S. models with the lowest clinical error rates and the highest safety ratings or as Fortune Magazine put it, "Doximity Ask came out on top." Clinical AI is rapidly improving. Our winning model demonstrated a 4.8% error rate, while others like Anthropic's best model, Fable 5, finished with a 13.6% error rate. We believe our outperformance is due mainly to 2 things: one, our unique built-in drug reference, a model within the model, which is 100% expert verified to ensure accurate drug doses and interactions; and two, our over 12,000 physician PeerCheck editors who are continuously reviewing and refining our AI outputs. These safeguards and quality checks are critical for hospital AI steering committees who could be held liable for their outputs and therefore, care deeply about their accuracy. We continue to lead the way in the enterprise now with 165 signed health system AI clients, including 8 of the nation's top Honor Roll hospitals. Our recent wins include Northwestern, Penn Medicine and the University of Michigan. As this market migrates from AI Wild West to privacy and risk management, we're well positioned to win as we did in telehealth. Okay. Now to our usage growth. Quarterly active workflow prescribers grew more than 30% year-on-year to record highs with nearly half using our AI tools in Q1. AI prompt volume was up more than 25% quarter-on-quarter, while our AI Scribe note-taking users grew a whopping 10x this July over prior. With these gains, we believe we're now the only clinical AI company who is top 3 in both the AI search and scribe markets. Finally, our commercial AI products. Our AI search monetization is off to a strong start, and the higher-level conversations it's generating with clients are fueling new business across our broader pharma portfolio. New search contracts are driving our revenue raise for the year, and we're just getting started. 15 years ago, we carved out a niche as the leading online resume book for physicians. We've grown a lot since then by keeping clinicians first and adapting the latest tech to their needs. Today, we believe we're the #1 most used clinical service in at least 5 categories: networking, news, scheduling, fax and telehealth. We're the doctor's digital platform and AI is just the next chapter in our growth. As always, I'd like to end by thanking my Doximity teammates who continue to work incredibly hard to care for those who care for us. With that, I'll hand it over to our CFO, Matt Sonefeldt, to walk through our financials and guidance. Matt?

Thanks, Jeff. Q1 '27 was a strong quarter for Doximity with robust revenue growth and clinicians adopting our AI suite faster than anticipated. Higher-than-expected AI usage creates a good problem for Doximity, and we'll expand our AI investment in fiscal '27 to capture the significant long-term opportunity ahead. Turning to our top line. Q1 '27 revenue of $157 million outperformed the high end of our guidance, with growth improving to 7% year-over-year. Revenue growth rebounded with solid performance across both pharma and hospital customers. Continued strong demand from large customers highlights our growing opportunity to work with pharma and hospital CXOs. Our largest customers continued to drive our growth. We now have 127 pharma and hospital customers who generate more than $500,000 in annual subscription revenue on a trailing 12-month basis, representing 7% growth year-over-year. They contributed 83% of total revenue, a level consistent with prior quarters. The top 20 customers produced net revenue retention, or NRR, of 112% with overall NRR at 107% in Q1 on a trailing 12-month basis. Q1 outperformance was driven by 2 factors specific to pharma customers. First, our new AI search product drove higher overall client engagement. As a reminder, we launched AI search in late April, leading to an increased velocity of pharma customer interactions. These conversations supported overall demand even as we did not recognize any AI revenue in Q1. We have onboarded our first cohort of AI search customers across more than 2 dozen programs. We're also building a healthy pipeline for the remainder of FY '27 and beyond with robust demand for our trusted brand and rigorously verified NPI-level engagement. We expect the majority of AI search revenue contracted to date to be recognized during Q3. The second factor was unlocking additional budget from several customers that only committed to shorter-term buys during last year's upfront. For example, we saw a meaningful rebound in spend from one of our large top 20 pharma customers that spent less in Q3 of last year. While the overall pharma spending environment remains tight, we're starting to win innovation budget with the launch of AI search. Turning to profitability. Adjusted EBITDA in Q1 '27 was $75 million, representing a 48% margin. The flow-through of incremental revenue growth drove the Q1 outperformance versus our outlook. In Q1, non-GAAP gross margin was 88% versus 91% last year. We increased AI compute spend during the quarter to support higher-than-expected clinician AI usage. We expect to maintain this trend throughout fiscal '27 as we doubled down on AI investments to further scale Ask engagement. During Q1, we also saw higher costs in our other OpEx lines driven by annual merit increases, greater internal AI usage and brand marketing. On a GAAP basis, stock-based compensation, or SBC, was $37 million in the quarter or 23% of revenue. This is consistent with the low 20% SBC guidance provided last quarter. As a reminder, this year's SBC increase is primarily related to the fiscal '26 grant made to our AI-focused R&D team. Excluding the grant, SBC would have been approximately 19% of revenue in Q1. We also saw a small impact from the hiring of new executives. Our GAAP effective tax rate was approximately 40% in the first quarter compared to 17% in the prior year, driven by the tax treatment of equity compensation. Our non-GAAP effective tax rate remained at 21%. GAAP EPS was $0.13 per share and non-GAAP EPS was $0.29 per share in Q1. Fully diluted shares declined by 10 million year-over-year or 5% to 191 million shares outstanding. Our balance sheet and cash flow generation remains strong and create a solid foundation for our growth and AI investment. We ended Q1 '27 with $688 million in cash, cash equivalents and marketable securities and we remain debt-free. In Q1, we generated free cash flow of $40 million. The decrease versus the prior year was driven by normal fluctuations in collections, which have variability based on program and delivery timing. We expect collections to normalize throughout the remainder of the year. During the first quarter, we repurchased $92 million worth of shares. We believe share repurchases remain an attractive opportunistic use of capital. As of June 30, we had approximately $400 million remaining in our existing repurchase program. Let's turn to our outlook. For Q2 '27 revenue, we expect a range of $170 million to $171 million, representing a midpoint of 1% year-over-year. For the full year, we have revised our guidance range up by $6 million to between $671 million and $681 million, representing 5% growth at the midpoint. This increase represents the flow-through from Q1 outperformance plus a modest incremental raise. The stronger fiscal '27 outlook reflects a more stable pharma budget environment, a higher velocity of customer interactions and the nascent but growing AI commercial pipeline. Our Q2 '27 growth outlook is impacted by the tough comparison against last year's elevated 23% growth. In addition, we expect only modest revenue from AI search in Q2. In Q3 '27, we expect stronger year-over-year growth as AI search revenue builds, we have a more normal growth comparison to the prior year. To date, we've taken a deliberate approach to scaling AI search by protecting the Ask user experience while iterating on the product based on customer feedback. At launch, AI search programs had conservative inventory caps with shorter 3- to 4-month commitments. As we move into the upfront, the focus shifts towards larger, longer customer contracts with greater inventory available across more therapeutic categories. For adjusted EBITDA in Q2 '27, we expect a range of $80.5 million to $81.5 million, representing a 48% adjusted EBITDA margin at the midpoint. For fiscal '27, we now expect a revised range of $309 million to $329 million, representing a 47% adjusted EBITDA margin at the midpoint. This continues to be our AI investment year as we respond to stronger-than-expected clinician usage and our growing commercial AI pipeline. This is the right long-term decision for our members in our business. This additional spend allows us to further invest in our AI competitive advantages, increased safety and accuracy through PeerCheck AI integration across our platform and our growing presence in U.S. hospitals. Approximately 90% of AI expenses will focus on responding to increased demand for our clinical AI suite, this will be recognized in cost of revenue, and we expect gross margins to trend in the mid- to high 80% range throughout the year. In summary, we're leaning in from a position of strength during one of the most important technology shifts in medical history. We will leverage our best-in-class margins and lean culture to continue delivering leading AI experience for U.S. clinicians. We believe this puts us one big step closer to realizing our mission, to help doctors be more productive so they can provide better care for their patients. Lastly, this quarter, we've begun to include a Modeling Considerations appendix, where you can see more detailed financial commentary. With that, I will turn it over to the operator for questions.

[Operator Instructions] And our first question comes from the line of Brian Peterson with Raymond James.

Congrats on the quarter. Jeff, I wanted to start on the NOHARM study that got released a few weeks ago. I know you mentioned that in the prepared remarks. What do you think that means from a competitive perspective? And how do you ultimately think that you can influence trust and usage for physicians on the platform?

Brian, thanks for the question. So first, I'll just say, we're really pleased with the team's efforts. It's really a testament to the hard work of our 800-person team here that they've really leaned into our Pathway acquisition of almost exactly 1 year ago, built a unique built-in drug reference, which is really key to answering clinical questions well, and then brought on board 12,000 cited authors, physician PeerCheck editors who are continuously reviewing and improving our AI outputs. There's actually been a couple of studies that have been published now. One was done by NYU and published in Nature and then the Stanford-Harvard study, the NOHARM study. Really groundbreaking studies that are important for clinical AI because at the end of the day, we're treating lots and lots of people, hundreds of millions of people with AI these days, and we want to make sure that they're getting the most accurate, safest answers. And so the NOHARM study was the first all model comparison done sort of on a secret shopper basis, where they went out and asked questions without the models knowing. Truly independent 1,100 real-world patient cases that they had seen at Stanford and then they went and they graded each of those answers in a consistent format. And again, we're very pleased to have come out on top of that overall approach. And I'll just say, it's the kind of rigorous independent physician-led research that we need much more of. And I hope that folks keep doing it because competition is good for the patient. It's how we all get better. And we are certainly in favor of honest competition here to have the best results, the best answers. I'll say where I think this really plays out in the marketplace is with hospitals. Every hospital has an AI steering committee these days. And they are very much in tune with what's a high-quality output and what is not because they are ultimately liable for some of these outputs. So we're really pleased we continue to lead the way in the enterprise with 165 signed health system clients. I would liken this maybe to what's happened in the frontier or coding assistant AI space with Claude and Anthropic over the last year. We saw a shift somewhere early this year where it wasn't just individual decision to go choose whatever AI I want to use. It was -- it became an enterprise decision and we think the same thing will happen here in the health care space as more of these studies start to point the enterprise to the right direction. But also as these enterprises get, I think, rightfully concerned about the leakage of patient data and what's called PHI, protected health information out to the broader Internet. I can share that we see -- it's almost 30% of the questions or prompts include some form of PHI or patient identifiable information. And again, as a health system or a hospital, you don't want that spraying out across 8 different websites. You need to make sure that's with someone that you have a privacy agreement in place with and it's a privacy agreement that is closely followed. So we believe that this will shift the market to more of an enterprise motion. And again, we're proud to be leading the way there with our recent wins at Northwestern, Penn and Michigan. We look forward to leaning into this market like we did in the telehealth market. And over the course of the next couple of years, really winning as the best, most accurate clinical AI, but also the safest, most private clinical AI because both will be needed for doctors and patients.

I appreciate all the color. And I noticed you guys did raise the outlook by a bit more than the beat this quarter. I'm curious on what you're thinking about the overall budget growth for calendar year '26. I know you mentioned maybe some innovation budgets are opening up to you, but how would you frame the overall buying environment?

Brian, this is Matt. I think the overall buying environment still feels tight, but certainly more stable. And I think for us, especially as we come into market with the AI search product, we're increasingly playing now in the AI innovation budget. We're playing now in kind of more of an insights and analytics budget and we're playing -- starting to play. It's early days, but in the search market overall as well, it opens up a lot of opportunity for us. I'll manage your expectations and say it's still pretty early in the ramp. But like we've talked about in the prepared remarks, we have a couple of dozen preliminary customers under contract, and we're building out a pretty strong pipeline. So I think that helps us have a little bit more confidence in the market outlook overall.

And our next question comes from the line of Craig Hettenbach with Morgan Stanley.

Just following up on kind of the year of AI investment as you guys lean in here, and you've talked previously in terms of a little bit of a mismatch where you're investing in the AI search will come. I'm not asking for fiscal '28 guidance, but how do you think about just kind of the spend that you have now? And then ultimately, the operating leverage that you might see down the line as AI search ramps up?

Craig, this is Jeff. I'll take a crack at that. So first, I'll highlight what was in Matt's prepared remarks, which is 90% -- over 90% of our AI spend is in the service of doctors, right, helping them get the very best answer. And so it's not a matter of us internally token maxing or doing lots of internal tools. It really is serving the broader medical marketplace and again, seeing better-than-expected volume and usage there. In terms of the economics of the usage, it's early days on our AI search product. But I can tell you, we're earning more than 10x per search in revenue than it cost us to run that today. And again, over time, we probably expect the overall AI cost, if anything, go down as models get more efficient. So we feel good about the unit economics there being in line with our broader gross margins or maybe even slightly better. And frankly, the TAM that this unlocks for us within pharma has been a real surprise and upside for us. I mean, I'll make the joke, I've been at this for 15 years here at Doximity. I'm getting into conference rooms. I never got into before, right up on high-level floors, with C-suite officers because this really is a C-level decision and C-level opportunity and focus for our pharma clients, because AI is so important to how the future of AI will work and how medical decisions will fundamentally be made. So we're excited to have those discussions, and it's really up-leveling our business across the board. So in general, we're excited about the margin opportunity that AI search has for us in fiscal '28 and beyond.

That's helpful. And then just a follow-up from that. Understanding it's a very short period of time you're in the seat. But what has surprised you most compared to the view you had externally before you joined? And I say that, particularly at a time where we're talking a lot about technology and its AI transition. So there's a lot of things in the marketplace that people are trying to digest and anything you would call out in terms of -- again, surprised you the most about how Doximity is positioned and where you guys are going?

Yes. Great question, Craig. I think one of the things that I have remarked on, especially from some of my consumer web days, especially at LinkedIn, is just how strong our relationship is with our users and members. The engagement that we have with each member on Doximity would have made LinkedIn blush. And I think what's really exciting is to see just the rapid increase, both in terms of the number of users that are starting to use the clinical AI search tool as well as how they're using it, right? I think we talked about prompts increasing by 25% quarter-over-quarter. That's a big engagement change from the base of physicians that are already highly engaged. And I think when you put the LinkedIn lesson up against Doximity, you realize that the larger and the more engaged your base of users is, the larger your monetization opportunities over a long period of time. That base is growing. It's growing rapidly. And we're just getting started on the monetization front, and I think we feel pretty excited about what's to come.

And our next question comes from the line of Michael Cherny with Leerink Partners.

Congrats on the quarter. Maybe I want to take a step back on all things AI, but dive around the broader AI strategy beyond just AI search. And one area I've been thinking about is the work that you've done so far with Scribe. I know it's still an early launch. I know you're still early in the monetization efforts. But can you give us a sense now on what you're seeing on Scribe either as a entry point, as a connective tool or -- and if there's something else beyond Scribe, I'm not asking about, but some other areas where pieces you have in place can help bring the totality of the search function together to clients?

Yes. Thanks, Michael. This is Jeff. I'll say we're very proud of our tenant Scribe growth and actually been our fastest grower in terms of number of doctors per month picking it up. And a big part of that enterprise hospital motion. It sits right between our telehealth, our dialer and our clinical decision support, ask in a really nice way. It is the connected glue. I believe that 5 years from now, every physician will have, in effect, a doctor's digital assistant. And the core of that doctor's digital assistant will be us, and it will be the combination of Scribe and Ask, our note-taking tool that then leads to a lit search or a clinical decision support tool. And that just makes sense. At the end of the day, when you want to ask questions after seeing a patient wondering what the treatment options might be or what might I have missed in the differential, it's easiest to do that, of course, when you have the whole visit and the pre charting all there. And of course, that's easiest to do when you're flowing out of the telehealth tool that you're using, that's already right there to take the notes and have that available for you. And it all leverages the enterprise relationships we built up over the years again, with all of the HIPAA security SOC 2 reviews, we're really a platform for our health system clients. We're not a point solution. And that's really important. Actually, health systems don't like buying point solutions. Those tend to be security vulnerabilities for them and more overhead, honestly, than it's worth. But again, being a platform for them that can be the doctor's digital assistant, I think, is a really powerful place to be. If you look at the leaders in the scribe market today, it's Microsoft. If you look at the leaders in clinical decision support, it's UpToDate. Again, I think telehealth is the biggest connector between the 2 of those. And I think we're in a strong position here to, again, be that combined doctor's digital system. No one else is top 3 in both note-taking, Scribe and top 3 in clinical decision support. We are.

And our next question comes from the line of Ryan Daniels with Blair.

Matt, I wanted to go back to something you said in the prepared comments, I thought was interesting. I think you indicated that the AI programs had shorter inventory counts, maybe just a quarter and as you're moving into the upfront, you're seeing longer contract terms. Is that you guys changing the terms to kind of push them longer given the innovations you're seeing? Or is that just the market being more receptive to longer contract terms?

Yes, I can start, and then I'll have Perry jump in with some extra detail. I think for us, it's a pretty conscious decision. We wanted to -- I think we talked about in the prepared remarks, both protect the user experience and also iterate on the product and the go-to-market on what what's a new product, not just for us but for our customers. And so we had more conservative inventory caps. We had shorter-term contracts in place for the first preliminary couple of tranches of customers that we've onboarded. As we go into the upfront, we'll open that up more towards larger and longer contracts. And there's some really great signs and signals that we're seeing around demand. Perry, maybe you want to talk about keywords and how that's evolving.

Yes, absolutely. Ryan. So just to clarify there, too. Yes, I mean I think for next year -- this has proven to be a good test ground ahead of the upfronts, right? And I think as you go into upfront-s, the focus shifts towards like Matt said, longer contracts, larger contracts. You kind of organically have, as the product grows, more inventory per therapeutic area to offer. And as you feel more comfortable with the user experience, you can kind of get a little less conservative with ad load or caps. So that's kind of what the natural progression is. Also, as we've been in market and we've taken in feedback, it's clear that there are many other therapeutic areas we hadn't even kind of come to market with that people want. And I think with my RevOps hat on, it's been really encouraging in my seat to see hundreds and hundreds of salesperson requests to price out new categories to kind of work in new ways to do deals, whether it be category-specific or specific keywords or specific target lists. There's just a lot of engagement and activity and buzz, and quite frankly, kind of the velocity of the business that we haven't felt in a few quarters. So I think it's a good time to kind of get the product down and get the experience down to then kind of sell the larger contracts ahead of upfront. And so then the focus will shift a little bit.

And the only other thing I'd add is, I think it's just really smart to take a deliberate approach and build in a measured way to start and then ramp it up more as you learn. Again, new products for us, but also new products for our customers. And I think we're really starting to find a nice product market fit there.

Got it. Super helpful. And then, Jeff, my follow-up is for you. You mentioned that just having the AI solutions is opening up new opportunities for you to present to leaders in the industry, and it sounds like it's really helping the broader base. I'm curious if you're actually seeing an accretive effect outside of that with kind of your core legacy offerings where they want to kind of bundle AI search and the efforts there with more of the core programs or initiatives to kind of do a 1 plus 1 equals 3 type of HCP marketing initiatives? Any color there would be great.

Thanks, Ryan. Yes. Actually, you put your finger right on it. Once you start talking about AI search and how it's great to see that this group of doctors has concerns about your side effect profile or about how to convert your dosing from a competitive drug to your drug that actually creates an opportunity for us to then have additional use of our telehealth platform to remind them of the dosing changes or the side effect studies that have been done. So it actually adds more utility and greater signal for the rest of the platform. But you really need both. At the end of the day, having signal is useless unless you have reach and having reach isn't as effective if you don't have good signal. And so bringing the 2 together has been a real unlock for us across our core business and across the new AI business.

And our next question comes from the line of Ryan MacDonald with Needham & Company.

Just maybe to start with you. You talked about 165 signed health system clients and that there's more of a sort of maturation and top-down approach within these health systems to sort of have something that's secure and sort of a top-down policy in terms of usage on clinical evidence. Can you just talk about where we're at in terms of what percent of those 165 health systems are live? And what the sort of maturation process looks like in terms of kind of if you want to call it, policing rogue clinical evidence use amongst the physicians within those systems?

Yes, it's a great question and it's actually right in the middle of what's afoot right now. So I'll begin by saying, we're live at all of those 165. And insofar as we have a privacy agreement in place and their doctors know that they're able to use our AI tools. We're in various stages of implementation of getting into their electronic health records and having the links and making all those things work. And that's a big effort for our team, but it's again another area where we're going to invest heavily because we know from our telehealth experience that once you're into these systems, it's a very sticky place to be, and you're really part of the workflow. In terms of where they're at from just a legal perspective and looking at all this I would say the concern is slowly ramping. I mean you're seeing a few lawsuits here and there that start to play out. The most recent one was against OpenAI with an individual patient who had shortness of breath, and it told him to wait it out, sit in his recliner chair for 2 days back and forth. And again, we'll see how this lawsuit plays out, but this patient had a pulmonary embolism, which should have brought him to the emergency room right away. And so those types of stories, I think, rightfully raise the hair on the necks of the AI steering committees and the med-mal committees. And so when you're making high-stakes decisions like this, it's really important to have the right experts there, and it's hard to do. So I'll say this. When it comes to high stakes things, we have pilots that are landing planes in this country. We have doctors that treat patients. I think we'll continue to see both those things continue to happen. Pilot land planes, doctors treat patients. And when the doctors treat patients at the hospitals, they're going to want to make sure that their patient data is safe and not being put out to some unauthorized AI. So on that front, I can tell you, the largest health system in the country, I know has blocked a bunch of AI players, not us. We're working with them. We're seeing I'd say, half a dozen others who've done similar. We haven't really done a survey of them per se, but I think you'll see, as the year progresses here, we're moving from this kind of age of AI adoption to AI accountability. And I think by this time next year, we'll definitely be looking at a place where the enterprise will be saying, no, this should be the AI you use. And again, I liken this back to coding assistance and Anthropic and OpenAI. A year ago, it was really try out whatever helps you, Cursor and Claude Code and Codex and all of them. And then really somewhere around the beginning of this calendar year, you started to see enterprises saying, no, this is the one we prefer, and this is the one we're going to have a security agreement with and volume pricing with again, I think you'll see that similar shift to the enterprise happen as health care AI use becomes more than norm.

Ryan, I'll just add one thing really quickly. Again, kind of coming in much more recently. I think this is where the NOHARM study is very validating for the approach that we've taken over the last year in that it shows that Doximity is the most accurate and safest clinical AI tool in the market today. And that's certainly what our kind of health systems customers are looking for. Our team should be really proud here of the work that they've done over the last year to kind of take what I think Doximity is calling card in a physicians first approach in developing the product. So I think that it's worth calling out because it's really relevant to the question you asked.

That's really helpful color there. And as we think about sort of the next layer on to that and sort of monetizing AI search. Will there be some sort of unlocking factor in terms of the revenue opportunity on AI search as sort of we get -- make progress with these health systems sort of rolling out Doximity Ask more broadly and then seeing sort of that maybe more material ramp in usage or continuing material ramp in usage? Is there sort of a knock-on benefit here as we think about sort of the AI search product and ability to sell it?

I mean fundamentally, the AI search product is going to be based on the number of doctors who are using it. And so yes, that unlock will certainly happen.

And our next question comes from the line of Elizabeth Anderson with Evercore ISI.

Appreciate all the color as you talk about the new opportunities that your -- the new AI launch has afforded you guys. I wanted to just think, if you think about your sort of pharma side of the customers, do you have any sense on how big those AI budgets are this year, for example, versus their traditional pharma ad budgets? Is it something that they're just maybe it's an extra 5% to 10% of the size? Or -- and then sort of have you had any preliminary conversations with customers about how they're growing that? Because obviously, that should increase over time, one would think, in terms of like TAM expansion of opportunity. But I just want to kind of hear, like where we are today and where you guys think that we might be, say, next year?

It's a great question. Honestly, I wish I had a better crystal ball to give you an answer. I think if you asked the Board of Directors of the top 20 pharma companies, they wouldn't know exactly where their AI budgets are landing this year because it is such a dynamic space. I'll share that one of the analysts who covers us did do a survey of 35 top pharma buyers and did ask them what percent of their overall budgets they expected to spend on AI and it was around 10% or less than 10%. And then when asked who they would spend that AI budget with, we were the #1 choice. And I was really proud of that given that, that survey was done only 1.5 months or so after we first came out with an AI search product. So here, it is just a couple of months into being out in market, we are already the #1 choice by a pretty wide margin in terms of where they would spend their AI this year. And I think that just boils down to us having built a trusted relationship with them over time, having proven our ROI and having a team that knows how to work within the regulatory framework that exists but also knows how to innovate. So I wish I had a better answer though. I can say the overall Google paid search spend by pharma is in the $14 billion range. I mean it's a very big number, but that does include direct-to-consumer and some other categories that we probably won't play in. But at the same time, I also think the ability to be more ingrained in the medical decision-making is a bigger opportunity that strips well beyond what people are using a Google search for today. So we think the TAM is very large. It's certainly as large as the market we're in to get into AI search.

Got it. And maybe as a follow-up, like many of your other products, you sort of launch at a particular gross margin. And I appreciate this one might be slightly different. But do you see anything that would necessarily like inhibit the gross margin line of this new offering from starting to trend up over the longer term? I realize that's a long-term question. I realize it's the future of AI, but thank you for trying.

No, all good. I think the short answer is no. I think in terms of our margins this year, it's really an intentional time sequencing, where we wanted to invest and support the kind of user engagement experience of clinical AI and scribe as we grow them. And then I think the revenue opportunity is there to offset that investment as we begin to ramp it up over time. Actually, I think we're pleased that we're starting to see some kind of opportunities to cost optimize even as we make a much larger investment. Some of it's around how we service the product to our users. Some of it's around how we're running our operations, preserving capacity, better forecasting. Some of it is just how we're tuning and optimizing different AI models as well as building our own first-party AI tooling around the products. All of those, I think, will help us get more efficient over time. But at the end of the day, it's really about sequencing our revenue and ramping that up, which will, I think, help improve the margin profile.

And our next question comes from the line of Steven Valiquette with Mizuho Securities.

I think I was also trying to hope here to dig in a little bit deeper on the reacceleration of your capture on the pharma digital marketing spend. So maybe more from just a numerical standpoint. I know it's hard to put numbers on it, but historically, you've obviously talked about the market for pharma digital marketing spend towards practitioners growing in that 5% to 7% range. And then Doximity in a normal environment would maybe grow double that market rate. Obviously, a lot of that was pushed to the side over for the past year or so, but with things reaccelerating again, maybe just framed numerically, where you think market growth is right now, I know it's hard to predict next year, so I won't ask that. Or said another way with your 7% revenue growth this quarter, do you think you're gaining share -- gaining market share at that number or just growing in line with the reexpanding market? Hopefully, that all makes sense.

Steven, yes, I think the -- relative to last quarter, I don't think our expectations for the HCP market growth have materially changed, stable in the mid-single digits. Obviously, we grew better than that in Q1. Our guidance is to grow kind of at 5% which is kind of in line with that for the rest of the year. A lot of our revenue for this year kind of dates back to last year, when we didn't have an AI monetization product in the upfront cycle, and we will this year. So obviously, we'll see how that goes. We're excited for the building pipeline there and the demand that we're seeing from customers. And I think that should portend well to us being able to outgrow the market again over time. I think the growth rate that we have this year feels probably like more of a blip of kind of timing more than anything else.

And our next question comes from the line of Jessica Tassan with Piper Sandler.

Congratulations on a really strong print and Matt on a really strong first quarter as CFO. So I guess, maybe, Jeff, I think you mentioned the strength in both hospital and pharma customers on AI. Just maybe any color on -- or directional commentary on kind of hospitals versus pharma? Are deployments able to monetize AI search in both of those avenues? Or is it kind of one or the other? If you could just help us understand the hospital versus pharma split on AI search would be helpful.

Yes. We're doing well with both. So I'd say both are doing equally well in the hospital and pharma side of the business. I will say the budget source are slightly different on each. In the pharma side, this is generally creating a new budget. And so there is a bit of searching around for this new budget that didn't exist a year or 2 ago. But again, it's good ROI. It's good upside, and it's the sort of innovation that I know has the attention of the C-suite. Within hospitals, it's actually sometimes a cost savings because they have been spending a lot of money on clinical decision support and on scribe services from other vendors and we're coming in with an offering that's lower cost than what they may have been using historically. And so there's an opportunity for them to save some money. And so that it becomes more of a budget opportunity for them to choose to work with us. And we're pleased to help them make that change. And again, our margins, as Matt described earlier, I think, can support that quite well. So on both fronts, on both hospital and pharma, we're seeing, again, high interest and growth on the AI products.

Jessica, one other thing I'd add, which kind of connects back to an earlier part of this conversation, which is a lot of talk about unlocking AI budget with pharma customers in particular, and I think that's true. I would also say that across a lot of the conversations that we're having, Jeff talked about, sitting in new boardrooms than the ones we've sat in, in the past. There's a diversity of funding sources, I think, for marketing and AI search, right? Part of it's AI innovation and that's new and sometimes that feels sexy. I think there's also kind of an age old insights and analytics budget that we haven't had opportunity to serve before that we're now able to, with some of the relevance that we can generate in the ad product. And then also search, which Jeff talked about, right? Again, not as much a budget that's been available to us that I think will be more so going forward. And that's exciting. It's exciting to have, I think, a diversity of ways that we can grow going forward rather than just be dependent on kind of one kind of one new spending area that is moving very quickly.

That's really helpful. And then my follow-up, you all have highlighted the drug reference component of your AI model. And I know, Jeff, you've got a long history with these types of products. So it seems like the drug reference is a really important differentiator within Doximity Ask. So can you just give us some color on what is so proprietary or important here, what should investors know about the drug reference tool? And is it uniquely well positioned to kind of to host sponsored content or just any detail or color that you'd like investors to understand about the drug reference component of the model?

Well, thanks, Jessica. Yes, certainly, I spent 11 years working on a drug reference company. So I can say that drug reference is a big part of clinical decision support, it's no mistake at all that UpToDate really didn't take off in the marketplace until they acquired Lexicomp, which was a drug reference and put those 2 together. And I think in a similar way, our Doximity Ask product, again, having a built-in drug reference is a key thing. And having it available as discrete data elements. So basically, the AI can work fluently with the drug reference to have the right dose, appear with the right indication to do the drug-drug interaction check. So being able to do all that is one of the things that leads to more accurate results. And again, one of the reasons why we believe we won the NOHARM study. The other thing I'll highlight again, which plays into all of this is we're the only company in the industry that we're aware of that has really leaned into physician oversight to have these 12,000 physicians cited authors who are reviewing the AI outputs on a consistent basis and even layering on their expert views on top of what might be out in the published PubMed evidence world. You really do need to have some of that in some situations because let's face it, there isn't an RCT, a randomized controlled trial that is done on every type of morbidity in question. And so we're able to see what questions are being asked most frequently and being able to provide answers to questions even if there isn't a clear question or clear answer available on the Internet or in published journals. So anyway, we're really proud of how this has come together in the fusion of PeerCheck, drug reference and AI evidence. And we think this is the reason why we're going to continue to win these independent studies looking at what's the highest clinical accuracy.

And our next question comes from the line of Sean Dodge with BMO Capital Markets.

Maybe just going back to the HCP marketing. You talked about the dynamics in large pharma and change in buying behaviors there. It sounds like that's getting better in places. But just curious on the SMB side. I know you've been able to drive a lot of share gains or growth in that part of the market with the portal. What percent of revenue now comes from like SMB pharmas now? And have you seen kind of similar dynamics in buying play out in that part of the market, too?

Yes, it's Perry. I'm happy to take the question. So SMB has been really strong for us. I think traditionally, if you look at the investor deck, our penetration with the top 20 is much higher than with SMBs. I think with all of the brands that are under $100 million, I think the last stat we put out, we're at around 10% of them we work with. There's a huge opportunity there, but it's been turbocharged by some of these kind of independent agency partnerships we've had in the portal. I can tell you that team that did really well this past quarter, they grew over 100%. So they're doing really well. I think AI search is also kind of providing more opportunity for that team to get in with certain companies that may not have already gravitated towards other products in the past that are really interested in this. So it's kind of expanding their aperture. And so I think that part of the business is doing really well. It's something we're super excited about. And it's diversifying our base of business in a way that we haven't seen historically.

Our next question comes from the line of Alexei Gogolev with JPMorgan.

Jeff, I was wondering if you could maybe comment on how you're packaging AI search today? Is it category bundles versus keyword-specific or maybe target list based? And what do you expect to change in the upfront versus initial couple of dozen programs cohort?

Thanks, Alexei, this is Jeff. Actually, Perry is the expert here. I'll let him answer.

Alexei, great question. So I think what I can say is when we started this was a therapeutic category based, and there's a share of voice model. I think as time has gone on, we're trying to make it as easy to buy as possible. We want to broaden the customer base. And a lot of folks kind of jumped right on for share of voice in therapeutic category. But as we learn and we have more folks kind of inquire, I think there's opportunities to kind of layer in some target list buys. There are opportunities to let people adjust some of the therapeutic areas and I think kind of add or take out keywords. Some of them are forced to, we call it suppress some keywords for med-legal review. So I think we are allowing for more and more options to kind of interact with the platform, and that is opening up more deal opportunity and driving more business. So I think we very much want to find the right product market fit and we are expanding the ways in which people can buy from us. I think one of the other neat things about the product as it exists today that will continue to iterate and experiment with is that there's a, I guess, we call it retargeting, but really an ancillary buy that you can do back into the core platform in parallel with the purchase that you do in AI search. So that, I think, can be really powerful as an incremental and larger purchase that really supports the core business above and beyond the new product.

And to double click on that, so how do you set and monitor AI search inventory caps and ad load to protect the clinical experience and what quantitative signals tell you it's safe to open more inventory?

Carefully. I mean I think this is honestly one of the things I love about coming to Doximity is the amount of care that's put into kind of protecting and creating a really high-quality user experience. And so that doesn't even -- I think we're really conscious about inventory caps, yes, but we're also conscious about the quality of the ad. And is it helpful to doctors as it comes into the user experience. So yes, carefully to Jeff's point. But there's a lot of thoughtfulness and a lot of, I think, rules and analysis that goes into getting that balance just right.

Alexei, I'll give you the quick parallel. In the early days of telehealth, we had very, very conservative inventory caps. Even if a doctor that was on the product all day, all week, we'd still only show them one ad every 4 or 5 days. As time goes on, you realize they love the product. It feels the ad feels native to the experience, therapeutic value ad for them, there's a little bit more room to loosen those caps a bit. But yes, to Matt's point, very carefully. But as time goes on, I think there'll be even more inventory, not just from ad loads that's a little bit less restrictive, but also just more inventory with therapeutic areas.

And our next question comes from the line of Scott Schoenhaus with KeyBanc.

Just wondering how AI monetization will impact sort of traditionally, you're not -- I don't want to call it lumpiness, but you used to see a lot of upfront and then renewals, and then you'd see midyear budget unlock. I mean, does this sort of smooth out the budget throughout the year? Can you just walk me through how this changes sort of any seasonality from your legacy platform?

Scott, this is Matt. Actually a really good question. The -- I think a couple of thoughts. I mean, as it sits now, the buying mechanics aren't drastically different than the business has historically been, which is you buy on contract I think this will be sold. I think AI search will be sold considerably during the upfront season, the contracts last different periods over time. If I -- we've talked a lot about my LinkedIn experience. And I think one of the most powerful pieces of it was that LinkedIn evolved and went into a more kind of biddable auction-based world over a long period of time. It didn't happen overnight. And by doing that, it unlocked a massive business that kind of grew from a few hundred million dollars and $1 billion to $10 billion. I think that potential and opportunity is in front of us, it's not something that will evolve and change overnight. A different way of buying is not something that we're unveiling this year necessarily. But it is out there as an opportunity set for us. And I think that's a good thing. It's a good thing for our customers. And I think it would be potentially a very good thing for our business as well to kind of continue to evolve that buying model.

Ladies and gentlemen, that concludes our question-and-answer session. I will now turn the conference back over to Mr. Jeff Tangney for closing remarks.

Thanks. I'd just like to end by thanking the entire Doximity team for the hard work serving more doctors every day than ever before. So thank you, everyone, for joining. Bye now.

And ladies and gentlemen, this concludes today's call, and we thank you for your participation. You may now disconnect.