Pinterest, Inc.

Thank you so much for joining us today. Over 96% of text-based searches on our platform are unbranded. For instance, cool running shoes or new fall wardrobe ideas. This is a great moment for marketers to meet prospective customers when they have clear commercial intent but haven't yet decided what to buy. As users move from inspiration to a more specific decision, their needs evolve from discovery to research with questions like, do these shoes run true to size? Or can you compare these two brands? To handle this part of the commercial journey, we're bringing AI further into the foreground of the user experience with our AI conversational layer, Pinterest Assistant. This intelligence layer, which we made available to the vast majority of US users as of the end of July, helps our users answer those later stage research questions, enabling them to move from an idea to a finished plan or purchase entirely on Pinterest. Pinterest Assistant is now woven throughout the user experience. Users can engage with it where they already explore and plan with contextual entry points and prompt suggestions across the experience, and will be able to generate product comparisons, step-by-step instructions, and visual forward guidance. For example, someone planning a living room refresh can ask what styles work in their space, get help finding the right rug, and explore ways to pull it all together within their budget, all without leaving Pinterest. What makes Pinterest's intelligence differentiated is that it's built on our taste graph. Years of visual curation signals from user searches, saves, and boards, giving a deep understanding of products and style that is highly relevant to how people shop and to each individual's taste and interests. Notably, it's also visual first, consistent with the experience users expect from Pinterest. We are also beginning to introduce memory and conversational history, creating an even more personalized experience. Importantly, We are building this capability in a highly differentiated, effective, and cost efficient way. Our approach to model deployment includes our own compact fit for purpose models built for Pinterest specific use cases and suitable open source models post trained in our own environment within our secure cloud infrastructure. When we leverage open source models, such as with Pinterest Assistant, we are seeing superior performance for our use cases when compared to closed third party models because we are able to post-train open models on our highly unique data. With open models, we are achieving cost per transaction at less than 8% of the cost of comparable closed proprietary models. This gives us substantial headroom to deepen and extend these capabilities over time in a way that is differentiated, highly effective, and cost efficient. Stepping back, this is the next iteration of work we've been doing for years. taking the discovery and intent that already exists on Pinterest and making it even more actionable for users, helping them move seamlessly from dreaming to deciding, doing, and buying. With the launch of our AI conversational layer, we are taking the next step to enhance that actionability even further and making it even more seamless for our users to move through their entire commercial journey on Pinterest. This is what sets up the monetization story I'll turn to next. On the monetization side, AI is helping us improve advertiser performance across the funnel, from better targeting and bidding to more automated, creative, and stronger measurement. As we shared last quarter, advertisers using Pinterest Performance Plus campaigns see meaningfully better ROAS and grow spend faster than those who haven't adopted it yet. That uplift comes from automating more of the campaign setup, bidding, budgeting, targeting, and creative optimization that advertisers historically had to manage manually. While still giving them clear controls. As part of our efforts to serve a broader group of advertisers with Pinterest Performance Plus campaigns, this quarter we launched Smart Assembly to help more advertisers benefit from creative optimization tools. This is a new Pinterest Performance Plus creative capability for advertisers promoting brands, services, or content who do not have existing shopping product catalogs. Advertisers can upload multiple images and Pinterest automatically builds and serves the best performing ad for each impression. In early alpha testing, Smart Assembly delivered a 6% improvement in click-through rate on average, demonstrating that creative testing and diversification can meaningfully improve performance. Over time, our goal is for nearly every lower funnel campaign on Pinterest to start in an AI-powered best practice setup. with added controls for more complex buyers who need them. Our near-term roadmap, including a simpler campaign creation flow, more sophisticated bidding and more automated creative is designed to drive the next leg of Pinterest Performance Plus adoption, including among advertisers that require both performance and increased control. We're also investing in Business Assistant, our conversational AI collaborator for advertisers, which is currently in beta. Business Assistant combines an advertiser's business context with Pinterest platform insights to surface actionable recommendations, including relevant trends, top performing pins, and optimization opportunities. The goal is to help advertisers understand what is resonating on Pinterest, decide where to put the next dollar, and make Pinterest easier to use and scale, especially for advertisers that do not have large dedicated teams. At the same time, we are upgrading our bidding and measurement systems So we can do two things better. Help advertisers find the highest value impressions on Pinterest and prove that value through the metrics and measurement systems advertisers already use. With a small initial group of some of our largest and most sophisticated advertisers, we are continuing to pilot integration between their in-house measurement systems and our AI bidding systems, allowing us to optimize bidding toward their unique set of desired outcomes. That initial group is seeing strong performance partially contributing to our strong Q2 results. We are now expanding testing to a small number of additional advertisers over the course of the third quarter. The learnings are also informing broader bidding enhancements across the platform that can scale to many more advertisers. We are always working on making our core ad delivery engine better through adapting new and better signals and driving enhancements in our AI modeling work. This quarter, We have made our shopping ad delivery systems better at deciding which products to show, when to show them, and how to allocate budgets against the highest value advertiser opportunities. That includes improving product selection for advertisers with large catalogs and increasing the variety of relevant products users see. This package of changes are designed to improve lower funnel performance across both large enterprises and smaller advertisers. The early results are encouraging, helping drive stronger, more consistent ROAS. Finally, we are continuing to extend Pinterest's unique consumer intent signal and audience to connected TV through TV Scientific, and early advertiser reception continues to be strong. In 2027, we expect to fully integrate TV Scientific capabilities directly into Pinterest Performance Plus, turning Pinterest into a full-funnel search, social, and CTV platform performance solution and opening access to larger and incremental budget pools. We're pairing this progress across our ad platform with a more disciplined, performance-oriented sales and go-to-market motion, helping us better monetize the strong engagement and commercial intent on Pinterest. Early progress on sales and go-to-market transformation was reflected in our strong Q2 results, particularly in UCAN. Our focus on clear seller accountability, better packaging of commercial moments, and a tighter connection between product performance and advertiser conversations are supporting strong UCAN demand. We're also making progress on our mid-market and managed SMB go-to-market efforts, including restructuring account coverage teams and realigning incentives to better serve this cohort over time. We're now applying our UCAN playbook internationally, where we see significant opportunity to close the gap between engagement and revenue. We're earlier in this work, but our progress in UCAN gives us confidence in the opportunity. With new international leadership We're sharpening our global go-to-market approach and bringing more global discipline to how we drive performance selling internationally. We're also testing the expansion of third-party demand into Europe. Taken together, the product-led improvements across our ad platform and a more disciplined go-to-market engine are strengthening monetization and helping revenue better reflect the value of the engagement we're seeing on Pinterest. In closing, Q2 shows that we are making progress on the priorities that matter most. We are building an even more differentiated visual search discovery and shopping experience. AI is improving both the user experience and advertiser performance, and stronger go-to-market and measurement capabilities are helping revenue better reflect the engagement we see on Pinterest. We are still early on many of these initiatives, but the initial results indicate we are on the right path. As we build for the long term, we remain focused on making Pinterest a positive platform centered on time well spent. As the global conversation around online safety and youth well-being continues to grow, we believe that foundation matters more than ever. We will keep making deliberate choices that put user trust and well-being at the center of the experience, and we remain confident that building a positive platform and building a strong business reinforce each other. With that, I'll turn it over to Julia to walk through the Q2 financials and our outlook in more detail.

Thanks, Bill, and good afternoon, everyone. Today I'll be discussing our second quarter 2026 financial results and provide an update on our third quarter 2026 outlook. All financial metrics, except for revenue, will be discussed in non-GAAP terms unless otherwise specified, and all comparisons will be discussed on a year-over-year basis unless otherwise noted. Q2 is a strong quarter. We've transformed Pinterest into a scaled, AI-powered shopping destination for 106 million users in the U.S. and Canada and 640 million users globally. Importantly, we have a direct relationship with our users. 100% of our reported users are logged in and 85% come to Pinterest directly through our mobile app, meaning we are not heavily reliant on third parties for traffic. Revenue exceeded $1 billion for the fourth consecutive quarter, growing 18% year-over-year. This growth was led by strength in UCAN, our core market, where revenue growth accelerated to 18% year over year. This performance reflects a number of our initiatives coming together. First, our ongoing ad platform enhancements to improve return on ad spend and to advance our bidding and measurement capabilities are driving advertiser performance and spend. In addition, we are seeing the early results of our sales and go-to-market transformation take hold in UCAN, We're increased rigor and discipline in how we go to market are beginning to show up in our results. As we discussed entering 2026, we have more work to do so our revenue consistently reflects the strength of our user activity. While this will take some time to fully take hold, particularly internationally, our results in UCAN give us confidence that we are moving in the right direction. Now I'll move to the details of our second quarter results. We ended the quarter with 640 million global monthly active users, or MAUs, growing 11% and reaching another record high. We continue to demonstrate user growth across all of our geographic regions. In Q2, our US and Canada region had 106 million MAUs, growing 4%. Our Europe region had 157 million MAUs, growing 8%. And in the rest of world markets, we had 377 million MAUs, growing 15%. Shifting to revenue. In Q2, our global revenue was $1,180,000,000, up 18% or up 17% on a constant currency basis, with strength led by our conversion and consideration objectives. Across verticals, we continue to see strength in retail, as well as smaller but faster-growing emerging verticals on our platform, including financial services, travel, and health. Turning to our geographical breakouts for Q2, revenue in the U.S. and Canada was $880,000,000, growing 18%. Growth came from retail and emerging verticals, including financial services, travel, and health. In Europe, revenue was $213 million, growing 12% on a reported basis or 7% on a constant currency basis. Growth in Europe was driven by retail. Revenue from rest of world was $87 million, growing 38% on a reported basis or 32% on a constant currency basis. In Q2, overall ad impressions grew 16%. Moving to expenses. In Q2, cost of revenue was $245 million, up 25% year-over-year and up 6% versus Q1, driven by the full quarter impact from TV Scientific and our investment in additional GPU capacity. Our non-GAAP operating expense was $629 million, up 13%. The increase was primarily driven by sales and marketing due to our brand campaign and sales headcount investments, as well as R&D to support our AI and product initiatives. In Q2, we delivered $311 million in adjusted EBITDA with an adjusted EBITDA margin of 26%, up 130 basis points versus Q2 last year. The higher than expected adjusted EBITDA was driven by flow-through from higher revenue. We also delivered Q2 free cash flow of $270 million. On a trailing 12-month basis, we've generated nearly $1.3 billion of free cash flow, representing 94% free cash flow conversions. In Q2, we allocated $58 million towards share repurchases. Separately, we entered into a capped call transaction for a total consideration of $99 million, which protects against dilution from our previously issued convertible notes up to a price of $30.59 per share. As a reminder, year-to-date, we've repurchased over $2 billion of stock, retiring nearly 111 million shares. We ended the quarter with cash, cash equivalents, and marketable securities of $1.3 billion. Now I'll discuss our guidance for the third quarter. We expect Q3 revenue to be in the range of $1,190,000,000 to $1,210,000,000, representing 13% to 15% growth year over year. As we move from Q2 to Q3, there are a few sequential factors to keep in mind. First, based on current spot rates, we expect foreign exchange to be a modest headwind in Q3 after providing a one-point tailwind in Q2. Second, the shift of Prime Day from Q3 last year into Q2 this year resulted in an approximately half-point benefit to Q2 and will represent a roughly half-point headwind to Q3 as multiple brands and retailers increase their advertising spend around that moment. Lastly, in Q2, we saw a nearly one-point benefit from World Cup-related spend that will not repeat in Q3. Moving down the P&L, we expect Q3 adjusted EBITDA to be in the range of $335 million to $355 million. We anticipate Q3 non-GAAP cost of revenue expense to be roughly flat versus Q2 2026 due to the accelerated recognition of certain contractual benefits in Q3 associated with our recently executed multi-year infrastructure agreement. In Q3, within non-GAAP operating expense, our primary area of year-over-year investment will be sales and marketing and R&D to support our AI and product initiatives. As we saw in the first half of 2026, we continue to expect modest headwinds from cost of revenue as a percentage of revenue in the second half as a result of the investments in areas such as additional GPU capacity as well as the impact from the inclusion of TV Scientific. Given our first half revenue outperformance, we now expect full year 2026 adjusted EBITDA margins of approximately 30% versus our prior expectation of approximately 29%. In closing, I'm proud of our teams for yet another strong quarter of results as we execute against our strategic priorities. I'm encouraged by our performance in the first half of the year as we continue to deliver for our users and advertisers. With that, I'll hand it over to Bill for some final words.

Thanks, Julia. I want to thank our teams at Pinterest, Our advertising partners and all the people that come to Pinterest to find inspiration and take action. And with that, we can open up the call for questions.

Thank you. We will now begin the question and answer session. Please limit yourself to one question. If you would like to ask a question, please press star 1 to raise your hand. To withdraw your question, press star 1 again. We ask that you pick up your handset when asking a question to allow for optimum sound quality. If you are muted locally, please remember to unmute your device. Your first question comes from the line of Mark Shmulek with Bernstein. Mark, your line is open. Please go ahead.

Yes, thanks for taking the question. Julie, you shared a little bit of color on that kind of revenue guide puts and takes, but hoping to get a little bit more color on perhaps some of the regional differences you might be seeing. Notice a little bit of a slowdown in Europe. Is that just kind of tougher compares? Thanks.

Sure. Thanks, Mark. So, yeah, overall, we're really pleased with a very strong Q2. And on a global basis for Q3, the high end of our Q3 guidance range is consistent with what we just delivered in Q2. When you adjust for the three-point sequential impact I called out in my prepared remarks from foreign currency, Prime Day, and World Cup spend, at the core of our Q2 outperformance is our ongoing strength in users and engagement. Thank you so much for joining us. So let's start with UCAN since that was the biggest revenue driver in Q2. We drove a five-point acceleration sequentially to 18% year-over-year in UCAN. And this reflects a few different things coming together. So first, as a result of our ad platform improvements, we began to see pockets of large retailer spend accelerate, with certain retailers leaning in as a result of our ongoing ROAS enhancements and AI-driven bidding optimizations, as well as Asia-based cross-border retailer spend into UCAN. Second, in UCAN and Q2, the strong year-over-year growth outside of our largest retailers continued across mid-market, managed SMB, and emerging verticals, as many of these advertisers are benefiting from our ad platform improvements, including Pinterest Performance Plus campaigns specifically. Lastly, UCAN and Q2 also benefited from Prime Day, shifting from Q3 to Q2, World Cup spend, and a full quarter contribution from TV Scientific. So overall, as we look to Q3, we expect strong growth in UCAN to continue. For Europe and rest of the world, we noted on the last earnings call that we expected growth to moderate in Q2 as a result of the deliberate leadership and structural changes we're making to our go-to-market organization and more difficult last year comparisons in certain markets. So in Q2, we were lapping the ramp of resellers and rest of world last year and lapping a significant influx of cross-border spend into Europe last year following changes in the U.S. tariff environment. That moderation was generally consistent with our expectations. In addition, we faced incremental pressure mid-quarter from Asia-based cross-border retailers impacted by regulatory actions, particularly in Europe, and that pressure is continuing in the third quarter. We have more work to do to fully realize the benefits of our go-to-market transformation in Europe and rest of the world, and we expect some level of disruption to continue in Q3. As we look to the third quarter, it's also worth noting that Q3 represents the most difficult comparison of the year for our Europe region in particular. So stepping back, the underlying trends in our business remain healthy. We're pleased with a strong Q2 overall led by growth in our core UCAN market in particular. which continues to be underpinned by our durable user and engagement strength that we can continue to see.

Your next question comes from the line of Colin Sebastian with Baird. Colin, your line is open. Please go ahead.

Great, thanks, and good afternoon. Bill, you talked about the evolution of the Pinterest Assistant and updates there as usage takes hold. And I guess as the competitive landscape continues to evolve, What are you seeing in terms of early engagement signals there, and how are you innovating on the broader Pinterest user experience side? Thank you.

Thanks for the question, Colin. Over the last three years, we've effectively turned Pinterest into an AI-driven shopping assistant. So even today, every pin you see on Pinterest is personalized and served by our AI. And that's been really at the core of the significant acceleration in our user growth over that three-ish year time period. And what we're doing now is we're bringing more of those AI capabilities into the foreground of the experience for users to interact with directly. So I'll give you a little bit more detail about how we're doing that. We're leveraging AI to make Pinterest more personalized, more actionable, and more valuable to users. And that advantage continues to compound, particularly The human curation on the platform. So we've been applying AI at scale for years. We completed our migration to GPU serving over two years ago. And as I mentioned, every NUC on Pinterest is effectively served by AI. But it's really that human curation that 640 million plus users on our platform that are creating hundreds of billions of unique connections across our taste graph. that really gives us proprietary signal that we can use to train our AI and personalize the experience with every interaction. And that feedback loop has accelerated over the past three years. As consumers are responding, that's what's led to the 12 consecutive quarters of record users, 11 straight quarters of double-digit user growth. And on the competitive landscape, we've long believed search will continue to fragment with the A small number of horizontal general purpose platforms, but more vertical specific experiences that solve distinct consumer needs. And that trend of the search market fragmenting has actually been happening for more than two decades. Think of how many product searches start on large retailers or travel searches at online travel companies versus a general purpose search engine. So as AI becomes more widely available and open source models continue to improve, we believe there can be many winners. Thank you so much for joining us. We're very focused on visual search, particularly around shopping, and we're using AI to make the experience more actionable across the shopping journey. People already come to Pinterest to discover products, ideas, and aesthetics they love, and research shows that shoppers find AI chatbots most valuable when researching and comparing products and narrowing their choices. The Pinterest Assistant, our AI conversational layer that we've now made available for the vast majority of US users, It brings those LLM capabilities into our visual, personalized, and proactive experience. So it helps users move from inspiration through consideration and decision-making and allows them to complete more of their shopping journey on Pinterest. By combining our proprietary signals with cost-efficient open source models, that really allows us to run those securely in our own environment. So we're able to keep improving the experience, scale those innovations with strong ROI, And the result is a better product today and compounding advantage as more people use Pinterest. And lastly, I'll just say it has been really, really exciting to see just how much the open source ecosystem is expanding. We've been very early on that. It's been woven into our experience as core to what we're doing, part of how we're doing that very effectively. But it's great to see that momentum building. And this is one good example of how we're using that. But I think you're going to see more of that across the ecosystem as well.

Your next question comes from the line of Brian Novak with Morgan Stanley. Brian, your line is open. Please go ahead.

What are the next sort of sources of innovation or unlock that you're looking for to even drive faster and more durable growth out of the UCAN business?

Yeah, thanks for the question, Brian. First thing I'd say is just, you know, we've talked about this previously. We're still a long way from having fully monetized all the commercial intent that already exists on our platform. So while user growth and engagement continue to be one of the highlights of our platform, especially as you look across sort of the social media landscape where you're seeing platforms You know, they're generally having a harder time growing, 11 straight quarters of double-digit user growth. That user growth and the fact that more than half of them are here to shop continues to be the strongest part of that. But as we shared before, you know, we shared on the last call, you know, we 5x the number of clicks to advertisers over that last three-year period, but we certainly didn't 5x the revenue. So the things that we've talked about in terms of, you know, aligning our AI bidding systems with measurement systems, which I talked about in my remarks, Thank you for joining us. You know, both in the users engagement, the fact that users and the engagement there is coming in the way that we want it with high intent, with search, with actionability, and that advertisers are leaning in more and more as we give them better ability to access that commercial intent.

Your next question comes from the line of Ross Sandler with Barclays. Ross, your line is open. Please go ahead.

Hey, guys. Bill, you mentioned the integrations with first-party measurement and the AI-optimized bidding as a growth driver at some of these larger accounts. Could you elaborate on where we are on that progression and what you're seeing thus far? Thanks a lot.

Definitely. Thanks for the question, Ross. So we're still early in the work, but the initial results from the pilot are very encouraging. and contributed to our outperformance in Q2. The small number of advertisers that were participating in the pilot, they're seeing meaningful performance improvements, which is giving them greater confidence to increase their spend on Pinterest. And so we're expanding this work to a limited number of additional advertisers in Q3. And by integrating with advertisers' measurement sources of truth, we're able to align our AI bidding systems to optimize for the hyper-specific outcomes each advertiser values most, whether that's customer lifetime value, incremental ROAS, or another metric they use internally to evaluate performance. So the more we're able to line up precisely with what they're looking for, the more we can make sure the AI is delivering their exact outcome. And then so they see more value captured from Pinterest, and they're seeing that across the funnel, upper, mid, and lower. and while we started this work with some of our most sophisticated advertisers because they have the data and the measurement infrastructure and the technical resources required to deploy that you know our most customized solutions will remain focused on that relatively smaller number with that level of sophistication but as we move beyond that initial group of advertisers it's reasonable to expect the full adoption curve you know will take place across the rest of our advertisers but it will take some time to play out you know you're seeing a few things here Thank you so much for joining us. Other advertisers through third-party measurement platforms. And so as those capabilities become easier to deploy through third-party measurement systems, we're making sure that we tie in closely to those things. So again, that adoption cycle takes time. Advertisers always have cycles they go through in terms of how they adjust their measurement, and they're cautious. and very methodical about that. But we absolutely see that happening across the industry, not just with us, but with other platforms. And we think that general trend bodes quite well for us. So as I mentioned already, the pay clicks average has been up well over five times over the last three years. So all of these things help us to capture more of that value that we're already creating. And the feedback that we're getting is encouraging. Simply stated, When advertisers can see the full picture and we can tune our bidding to what matters most to them, they have more confidence and they increase their investment in Pinterest.

Your next question comes from the line of John Blackledge with TD Cowen. John, your line is open. Please go ahead.

Great. Thank you. As you expand your AI product offerings, how are you managing token spend usage and AI compute costs And what KPIs are you tracking to make sure those choices translate into real productivity gains for your teams? Thank you.

Thanks, John. I can take that one. So in 2026, we've expanded our AI capabilities across our product, both for users and advertisers and also for internal productivity related use cases. We also just raised our margin outlook for the year, so I think that demonstrates our ability to invest in these capabilities while continuing to improve profitability by managing AI and compute costs efficiently. We've discussed our incremental investment in GPU capacity throughout 2026, which is reflected in our cost of revenue line item. We're already seeing returns through ROAS gains for advertisers and improvements to our user-facing experiences, as Bill just noted. Thank you for joining us. We evaluate models across the ecosystem constantly and leverage our centralized model routing layer to optimize production traffic for the right balance of quality, cost, latency, and reliability. And this allows us to reserve more capable higher cost models for complex work while using lighter lower cost options for routine tasks. In the second half, we're expanding this model routing infrastructure to even more internal use cases, including tools to increase productivity across engineering, sales, and other functions. These costs appear in our OpEx line item. And here we're tracking adoption, developer throughput, cycle time, incident rates, and service uptime to ensure the greater speed does not come at the expense of reliability. For example, in July, weekly pull requests per engineer increased 45% versus last year, while incident rates and service uptime remained relatively consistent. So that gives us confidence that we're improving velocity without compromising reliability. As AI adoption continues to grow, we expect both AI-related compute and token spend to grow over time. We see that these investments are ROI positive, and that investment growth is planned and included in our outlook that we've provided. So we're scaling AI deliberately, expanding user capabilities, driving advertiser outcomes, and improving employee productivity, all while maintaining a disciplined approach to profitability as well.

Thank you.

Your next question comes from the line of Justin Patterson with KeyBank. Justin, your line is open. Please go ahead.

Great. Thank you. Good afternoon. You've talked about broadening your revenue base beyond your largest retailers. Can you update us on that progress, particularly with the SMBs, and discuss how Performance Plus adoption and the product roadmap supporting this effort? Thank you.

Certainly. Thanks for the question. So we're really pleased with our continued progress in broadening the revenue base. As Julia noted in Q2 and UCAN, we saw strong growth outside our largest retailers across mid-market, managed SMB, and emerging verticals. And we've got ongoing ad platform improvements, notably Pinch of Performance Plus, that's been a key driver of this strength across those. Performance Plus gives advertisers an automated best practice setup across bidding, budgeting, targeting, and creative. And so that's especially valuable for smaller advertisers that don't have large teams. So we're also adding the controls that more sophisticated advertisers need so they can take advantage of these things as well. As we shared last quarter, approximately 30% of our lower funnel revenue was running through Performance Plus campaigns as of Q1. Adopters also grew their lower funnel spend more than twice as fast as non-adopters. So we're really seeing that be effective for our advertisers. And then I'd say more recently, the updates to our ad delivery models drove a 28% improvement in ROAS during testing for SMB advertisers using Performance Plus with ROAS bidding. So these improvements continue to help smaller advertisers achieve better outcomes with less manual work and As we look ahead, we continue to make our best performing automation the default for lower funnel campaigns, doing more and more of that while also improving bidding, creative and measurement, and adding controls for more complex buyers. So, you know, simpler campaign flow targeted for Thank you for joining us. And part of that is managing customers through not only their adoption, but how they think about leveraging these tools. But we continue to release new functionality every quarter, and we see good adoption happening across our user base. And other platforms that have deployed AI-driven automation suites saw adoption play out over several years. In fact, even some of the earliest to have done this are still ongoing. working through their adoption cycle. And we expect a similar dynamic for ours as well, where we've created a lot of capability, but there's a lot more in front of us than behind us. And then lastly, just on the go-to-market aspect of this, we're also evolving how we go to market for mid-market and SMB advertisers. We talked about how we're restructuring account coverage, realigning incentives, so we can provide direct support where it can unlock growth and scale support where that is a better fit. And so broadening our revenue base, including internationally, it's a multi-year journey and we're still relatively early, but we're building the product foundation, coverage model, and go-to-market discipline required to serve a much broader range of advertisers. And again, we believe there's significantly more opportunity ahead of us.

Your next question comes from the line of Nitin Bansal with Bank of America. Nitin, your line is open. Please go ahead.

Thank you for taking questions. Julia, can you provide some color on the increase in SBC expenses quarter? And as we continue to invest in AI talent, how should we think about the trajectory of SBC for the second half and next year? Thank you.

Sure. So we don't guide stock-based compensation expense specifically, but it's certainly an area we're focused on. Q2 had some unique factors, and as a result, should be the highest quarter for stock-based comp expense in 2026. Thank you for joining us. While stock-based comp will remain elevated in 2026, starting in Q3, we do expect both stock-based compensation expense dollars and the year-over-year growth in stock-based compensation to step down versus Q2. As in recent years, we also expect to be profitable on a full-year gap net income basis. I'll also note that we've leaned in opportunistically to manage dilution, particularly this year at a moment of dislocation in our stock price. We've repurchased over $2 billion of stock at an average price of $18 per share. As a result, net dilution for Q2 was down 12% year over year, leading to growth in Q2 non-gap EPS of 30%. So we have a growing, highly profitable, and cash-generative business, and we'll continue to be thoughtful in balancing employee retention and incentive alignment with opportunistic capital return and ongoing dilution management going forward, just as we've done in the past. Thank you.

Your next question comes from the line of Jason Halfstein with Oppenheimer. Jason, your line is open. Please go ahead.

Thanks. First question for Bill. You touched on the capabilities of open source AI models. Maybe how does PINS leverage that today and how does that fit into your broader AI strategy? And then second, just Julia, a quick one. Is MAU really the best KPI for UCAN or is there another metric that you could share with us over time to help us better understand what's going on in the business around engagement. Thanks.

Thanks for the question, Jason. So on open source, you know, it's open source AI. It's an area that we're really, really excited about. I've been talking with you all about this since right after the deep seek moment, you know, what, a year and a half or so ago. And as we've discussed before, we take a model agnostic approach. We use the right model for the task, whether that's one of our in-house compact fit for purpose models, Thank you for joining us. So starting with costs, for our use cases with open models, we're achieving cost per transaction at less than 8% of the cost of comparable closed proprietary models. And that's a substantial advantage, and it becomes even more compelling as open source models, including those from US-based labs, continue to improve. Our early adoption of open source has enabled us to scale AI efficiently to serve our 640 million users while also expanding margins and generating significant free cash flow. But it's the combination of those, you know, our in-house compact models and leveraging open source really effectively. And I would also just say, you know, with the open source, not only is it much lower cost, The fact that we can post-train on our own data makes it more effective. So as you're looking at what's happening in the open source ecosystem, those models continue to get better and better. It's not just how they do on the benchmarks. It's how are they going to work in your own environment. And when you can post-train on your own data, that makes them much more effective. So then you're looking at something that is more effective than the way you get from the closed models and at less than a tenth of the cost. You know, that really makes it so that at this point, any CEO that's not taking advantage of open source models is almost certainly wasting a lot of their shareholders' money. And especially that's true now that you have hyperscalers making it really easy to take advantage of that open source in their secure environment so that you can leverage the open source in your own cloud environment so that it's safe, it's secure. You don't have to worry that it's phoning home. And, you know, as others have called out, you don't have to worry that you're giving your company's most important data over to somebody that's going to potentially use it against you. So, again, we're very, very excited about the progress in open source that pairs with our own work on our own compact models that serve our use cases. But we're quite encouraged by what we're seeing in the advancement of the ecosystem there. And I think there's going to be a lot more of that to come. And it's, I think, a great democratizing agent. Most of Silicon Valley, you know, most of the web, most of mobile was built on top of open source software. You know, U.S. tech needs a thriving open source ecosystem. And I think with the hyperscalers showing up, with U.S. labs showing up, We're getting exactly that. And again, we've been one of the largest practitioners of it, but we think it's a really great thing for the industry.

And maybe just to take the second part of the question on UCAN and mouths and engagement. I'd say we always internally look at sort of various baskets of metrics to measure engagement across the platform. We continue to see, you know, we're adding new users and we're continuing to maintain strong engagement with those users that we're adding. So, for example, in UCAN, for instance, you know, searches and boards created continue to grow faster than users in Q2. But I'd say just sort of across the platform as we're looking at strength overall, we're seeing across a number of those basket of metrics Your next question comes from the line of Eric Sheridan with Goldman Sachs. Eric, your line is open. Please go ahead.

Thanks so much for taking the question. Julia, maybe building on some of the commentary you've given so far with respect to EBITDA margins and given the performance of EBITDA in the quarter, maybe just put a finer point on two questions. One, how are you thinking about what the highest return areas are for incremental growth investments when you look out over the next couple of years? And when you think about flexing the EBITDA margin beyond 2026, How do you think about the scope for both headcount reductions, productivity gains, and or increased growth investments in the ad platform as different variables that could play into how margin evolves going forward? Thanks so much.

Sure. Thanks, Eric. I'd say in general, we're internally just becoming ever more AI-native company over time, and we're continuing to move further in that direction. AI is embedded now in how we build every single product, operate the business, and allocate resources internally. So the restructuring actions we took in Q1 were really about aligning the organization with our highest priority opportunities and creating capacity to invest in the areas where we see the greatest potential returns, including AI. And so you're seeing that reflected in how we're rebalancing our cost structure a bit in 2026, where we're Directing more investment capacity towards GPUs and internal AI tools while being thoughtful and disciplined about where we add headcount. Reported headcount was up 3% year-over-year in Q2, which includes employees who joined Pinterest through the TV Scientific acquisition. So if you exclude that acquisition, headcount was down year-over-year in Q2 and is down 6% since the end of 2025. So to be clear, we'll continue to invest in specialized talent where we see a clear and compelling ROI, but an ongoing focus for us is finding the right mix of talent, infrastructure, and AI-enabled productivity tooling to produce durable growth and expand margins over time. So for 2026, as I noted in my preferred remarks, we are increasing our full-year 2026 projection for EBITDA margin to 30% given the strong performance Thank you for joining us. Thanks.

Your next question comes from the line of Michael Morris with Guggenheim Securities. Michael, your line is open. Please go ahead.

Thank you. Good afternoon. I wanted to follow up on the Pinterest assistant comments and hoping you can expand a bit more on the path to monetization of the product. I understand how it further strengthens the user experience. It's very clear. But are all the pieces in place from advertisers to be on that monetization journey, or do you need more there? And if I could ask one more on just a follow-up on the comments on the deceleration and non-U.S. international growth that's driven by decisions that have been made by the new leadership team, can you expand a little bit on what's changing in that go-to-market and when we will see the sort of fruit of that labor? Thank you.

Yeah, so on the monetization for our assistant, one of the things I talked about on the call is that we've actually woven it throughout our existing app. And so that means it has monetization built in right from the start. So we don't think of this as a build it now and then later monetize type of thing with our assistant capabilities that are woven throughout the app. It's woven throughout the app right alongside of the monetization that is already baked in there. And I would just say, As you look at our journey over the last few years as we made Pinterest an AI-driven shopping assistant, you've seen us do that while having a pretty consistent margin expansion through that time, which has been twofold. It's been one about us using that AI for highly commercial moments where monetization, again, is sort of baked in right from the start as well as all the cost efficiency that we've talked about with compact models and using open source or open weight models Those are the things that we've been doing to make sure that we've got not only the monetization, but the margin profile that we want from leveraging AI. That's exactly what we've been doing for the last several years in the background. Now, to bring it to the foreground, the same type of approach that it's woven right in with the monetization there. Of course, there's always things that we'll do to keep adding to that. We've talked about our business assistant for advertisers, things like that, where we're bringing more assistive capabilities to advertisers. all those things that will continue to enhance that but we think about monetization from the beginning of our product design and then on the second point in terms of the go-to-market changes of monetization there so you know these you know we expect we talked about these last quarter you know it tends to take you know you know it can be a multi-quarter journey on these things but the thing I point you to is We had work to do in UCAN as well. And when you look at the reacceleration of UCAN, the things that we did to reaccelerate in UCAN, particularly around our go-to-market and sales approach, you saw those reflected in Q2. And that's what we're deploying. Those similar strategies we're deploying internationally. So while it can take a little bit of time to take hold, you're already seeing that happen for us in UCAN, and that's what gives us really good confidence there. on that for Europe. And while there's still a little bit more of that for us to do, and it can be a multi-quarter journey, we feel quite confident in the approach. I don't know, Julia, is there anything you want to add to that?

Yeah, I think that's spot on. I think just to add a little more color, our new head of international sales is in place now, focused on improving kind of market prioritization and coverage, deepening senior relationships with advertisers and agencies in the region, and bringing just greater consistency overall to measurement and cross-functional support across regions. We're also testing the expansion of third-party demand into Europe as we work to broaden demand. So just a little bit more color there. And again, as Bill said, I think seeing nice results here from the UCAM playbook and looking to extend those to international over time.

Our last question comes from the line of Shweta Kajuria with Wolf Research. Shweta, your line is open. Please go ahead.

Okay, thanks for taking my question. I have one on engagement. What is, specifically, what is driving engagement strength to continue to remain strong, particularly among Gen Z, and I guess what gives you confidence in these trends being durable? Thank you.

Yeah, thanks for the question. Well, you know, the durability of these trends is 12 straight quarters of record high users, and through all 12 of those quarters, It's been the same things that we've been talking about in terms of really making Pinterest a highly shoppable platform with great personalization and with AI powering great recommendations, but not the AI alone. It's the AI powered on human taste and curation, that unique signal that we get. Stated very simply, the AI by itself doesn't have style or taste. People have style and taste. The 640 million people that come to our platform really create a flywheel effect that we get really unique signal that we can train our AI or post-train open models on that then let us give better and better results to users. And as I mentioned in my prepared remarks, we see that flywheel continuing to accelerate. And when we think about how differentiated that is, I shared this on prior calls. that when we look at our latest multimodal models and the relevancy of the shopping recommendations we make, we talk about how we saw those outperforming closed models by 30 full percentage points on the relevancy of shopping recommendations. Not on anything that it could do, but on the relevancy of shopping recommendations. So those are things that give us confidence in the durability, but I'd also just point to what's been happening over the last three years where several years into AI chatbots, Thank you for joining us. And you see that not just in our user growth and engagement. You see it in third-party research as well. We previously cited Adobe did a study independent of us that 39% of Gen Z now thinks of Pinterest as a first place to go search. And the reason for that is more than 70% of Gen Z sees Pinterest as more personalized. So I think those are places where you can look and see that flywheel really taking effect. And as models commoditize, which they clearly are with open source, were able to take those capabilities, train on our totally unique signal, and give really great recommendations to users. We've got great distribution to those users and have become really a beloved platform for those users, which is why, as Julia noted in some of her earlier comments, 85% plus of our users come to our mobile app directly. We're not dependent on others for that traffic. Pinterest is a destination that's beloved by its users, and I think that has proven out to be quite durable as well.

We have reached the end of the Q&A session. I will now turn the call back to Bill Ready for closing remarks.

Thanks again to all of you for joining the call and for your questions. We look forward to keeping this dialogue going and we hope you all enjoy the rest of your day.

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