Welcome everyone. Thank you for standing by for the Applebet first quarter 2026 earnings conference call. At this time, I’ll put this phone on listen only mode. After the speaker presentation, there will be a question and answer session. After questions in the session, you will need to press star one on your telephone. I will now hand the conference over to speaker today, Jim Friedman, head of investor relations. Please go ahead. Thank you. Good afternoon, everyone, and welcome to Applebet first quarter 2026 earnings conference call. With today’ our center, I’m Phil Spencer, and now Ashkan Azizi. Now, I’ll quickly cover the safe harbor. Some of the statements we make regarding our business operations and financial performance may be considered forward-looking. Such statements are based on expectations and assumptions that are subject to a number of risks and uncertainties, which could differ materially. Please refer to our forms 10K and 10Q including the risk factors. We undertake no obligation of any forward-looking statement. During this call, we’ll present both gap and non-gap financial measures. Our calculation of non-gap financial measures is quoted in today’s earnings press release, which is distributed at the Applebet public investor relations website located at abc. Xyz forward slash investor. Our comments will be on year-to-year comparisons unless stated otherwise. And now, I’ll turn the call over to Spencer. Thank you, hi everyone, and thanks for joining us today. It was a terrific quarter for Applebet. Our momentum from full display cloud last week and the month of May brings even more with AI brandcast and Gmail. I hope you’re tuning into our progress. It’s clear that our AI investments and full stack approach are driving performance across our business. In certain other revenue grew 19%. People love AI experiences like AI mode and AI overview and they coming back to search more. Cloud accelerated again this quarter due to strong demand for our AI products and infrastructure. Revenue grew 63% exceeding 20 billion dollars for the first time, and our backlog nearly doubled quarter on quarter to over 460 billion dollars. Gemini enterprises seeing tremendous momentum with 40% growth quarter over quarter in paid monthly active users. Subscriptions this was a strongest quarter ever for our consumer AI plans, primarily driven by our optional Gemini app. Overall, the number of paid subscriptions now reached 315 million, with YouTube and Google One being the key drivers. Our AI models have great momentum. Our first party models now process more than 16 billion tokens per minute via direct API use by customers, up from 10 billion last quarter. Today, our shared progress across AI full stack, then search and cloud, followed by YouTube and other apps, starting with our AI infrastructure. It’s the foundation for full stack approach to AI, driving customer growth and product adoption. Our custom APIs, actions, APIs, and the latest NVIDIA GPUs continue to form the industry’s widest variety of applications. NVIDIA GPUs are core part of our AI infrastructure and will be among the first offer NVIDIA Open and NVIDIA 2U in addition to Blackwell hardware bases and systems already available. At cloud next, we introduce our agent generation TPU’s, individually specialized for training and serving, and able to take on the most demanding agentic workloads. TPU8 provides high performance model training with three times the processing power of HiW and two times the performance. TPU8 delivers cost-effective, low-latency inference with 8% better performance per dollar than the prior generation. The exceptional infrastructure powers our world-class AI search that includes models and tools which continue to progress really well. Gemini 3.1 Pro continues to push the frontier, reasoning, multimodal understanding, and cost. We’ve quickly expanded the Gemini 3.1 series of models to offer more choices for developers, including our cost-efficient flash models. 3.1 flash light our latest audio model has improved precision and reasoning, making voice interaction more natural and intuitive. It’s now powering conversational features and search in the Gemini app. Speech text is now available in seven languages. And the 3.1 Pro are deep-featured and capable of creating MTPs and native visualizations. Our generative media models are incredibly popular, with three generations over 150 million songs since launching on the Gemini app. Gemini 2 reached 1 billion images nearly half the time of Gemini 1.1, and we’re 3.1 light is the most cost-efficient VLM today. On top of this, we launched Gemini 4, our most intelligent open model. It’s been downloaded over 50 million times in just a few weeks. In fact, our open models have now been downloaded over 500 million times. Looking ahead, we’re focused on pushing our next frontier of foundation models, including intelligence, agents, and agentic coding, and we’re using the latest technologies to transform how we work as a company. For example, with anti gravity, we’re shifting to truly agentic workflows. Our engineers are now orchestrating fully autonomous digital task forces and building faster velocity much more to come here. Next, we’re bringing helpful AI into the hands of billions of people every day through our product platforms. Earlier this year, we introduced personal intelligence, which helps people get more personalized and helpful responses. It’s now in the Gemini app, AI mode, and Gemini Chrome. Early traction has been good, and this month we integrated Gemini 2 to make personalized image creation possible in the Gemini app. Maps recently got its most significant upgrade in over decade with Gemini. Users can now have a conversation with Maps and get more personalized actions and intuitive actions. And the 610 launched to positive reviews, providing the best of Google AI features like Gemini Live and AI powered camera features. Turning to search, AI continues to drive search usage inquiries are now high. We continue to invest in improvements to AI overview, which are driving overall search growth. And we’re also seeing strong growth in both users and usage of AI mode globally. Personal intelligence expanded broadly in the U.S. and we’re seeing people ask more personal questions and getting responses that are uniquely relevant. We also shift agentic experiences like restaurant booking to new countries and new multimodal capabilities like search live globally. We are also continuing to improve efficiency and speed, even as we brought new AI features into our search page, we’ve reduced search latency by more than 35% over the past five years. And since upgrading AI overview and AI mode to Gemini 3, we’ve reduced the cost of core AI responses by more than 30%. Thanks to continued hardware and engineering breakthroughs, we are excited to share more about searchlio now over to group cloud. Group cloud’s differentiation because we’re the only provider of first-party solutions across entire enterprise AI stack. Our growth in revenue, operating margin, and backlog highlights the differentiation. Our enterprise AI solutions have become our primary growth driver for Applebet for the first time. In Q1, revenue from product built on our Gemini models grew nearly 80% year over year. We are winning new customers faster with new customer acquisition doubling compared to the same period last year. We’re seeing strong demand, doubling the number of 100 million to 1 billion dollars deals year on year, and signing multiple billion dollar plus deals. And we’re deepening relations with existing customers. Customers’ out-payer initial commitments by 45% accelerating over last quarter. At cloud next last week, we introduced hundreds of new capabilities across vertically optimized AI stack that are designed to work together for our enterprise customers. We introduced new Gemini enterprise platform that empowers users to build, orchestrate, govern, and optimize with the controls that enterprise customers need. Along with new capabilities in Gemini enterprise app, like project scans, long-running agents, skills, every employee can build agents. In Q1, Gemini enterprise paid monthly active users grew 40% quarter over quarter, that includes major global brands like Bosch, Cielo, Merck, and Mars Incorporated. Our partner ecosystem plays an increasingly critical role in driving Gemini enterprise.
Sales option. We saw nine zero-year growth, both in seed sold with partners and the number of partners operating internally. This moment is leading, accelerating use of models. Over the past twelve months, three hundred and thirty Google Cloud customers each processed over one trillion tokens. Thirty-five reached the ten trillion mark. To give agents business context from enterprise data, to help them reason intelligently, we introduce new agent data blocks. They include across cloud layers, knowledge catalogs, and deep research agents, which combine research and artificial intelligence. As an example, using our data cloud, American Express is enabling agent commerce at scale by moving enterprise data platform along with hundreds of production applications to BigQuery. We’re forming proactive, resolving outages, automating network planning, and precisely targeting capacity. Enterprise data is critical for agents to reason. Our strengthened query and term enterprise has led Gemini-powered workflows to grow over thirty x year over year. As cyber security threats from the use of AI models accelerate, our expertise in AI and cyber security is driving strong demand for our agent defense offering. In March, we closed acquisition of S, a leading cloud security AI platform, which is incredible for the moment we are. We’ve seen tremendous interest from customers in our unique cyber security and AI product services to protect their IT estate. The performance of S so far has exceeded our expectations. Together with Google’s third intelligence security operations and AI models, this is helping organizations detect, prevent, respond to threats. We introduce new Gemini-powered agents for threat detection, continuous learning, and automated remediation to protect software code and cloud systems. Customers like Deloitte, Price Langshell are using our agent defense to strengthen their security posture. All of this is powered by the AI infrastructure I mentioned earlier. Our deep, continually shifting performance cost and power efficiency for customers like Think Machines Labs, Accenture Trading, and Boston Dynamics, as deep demand grows from AI labs, capital markets funds, and high-performance computing applications, will begin to divert deep into select groups of customers in their own data centers. In a hardware configuration, expand our addressable market opportunity. Turning to YouTube, where momentum continues in the living room, viewers are watching over two hundred million hours of YouTube content daily, and as March reached new milestones, over ten million channels now publishing shorts each day. This level of daily activity is testament to how people enjoy the content and how we made it easier for creators. And Q one, our YouTube Music Premium offering saw largest quarterly increase in the total number of non-trial subscribers, both globally and in the US, since YouTube Premium launched in June twenty eighteen. I hope you’re tuning to brandcast on May thirty. Moving to ads, Vimeo’s on a great trajectory. It launched nationally week ago, that made six new cities so far in twenty twenty six, and operations eleven major US cities total. Vimeo also surpassed five hundred thousand full-year anonymous rights per week, doubling in less than a year. We continue to expand across US and partner with Walmart, DoorDash, and announced plans to operate in the area. In summary, a terrific start to the year with so many great opportunities ahead. We’re not slowing down. Huge thanks to all of our employees and our partners. See you at I/O on May nineteen. Salute, all of you. Thanks, Lord, and hello everyone. As usual, starting with performance of Google services and then covered progress with delivering across search, YouTube, and partners. Google services revenue nine billion for the quarter, up sixteen percent year on year, primarily driven by continued growth of search. Thanks for the call result. Search and other delivered nineteen percent growth, primarily driven by retail and finance. YouTube advertising revenue twelve percent, driven by direct response followed by brand and network advertising revenue around four percent year on year. Starting with search and other revenues, which delivered sixty billion revenue for the quarter, we’re accelerating the deployment of Gemini across our entire AI infrastructure, helping businesses reach more customers in more places than ever before. This is driving significant improvements across all areas of marketing and continues to fuel new performance breakthroughs across three areas critical for customers: S, advertising tools, and new AI user experience. First, S, AI is boosting our ability to deeply understand user intent, improve search quality, and find more relevant ads. Even with automated user queries, we make significant strides in improving relevance, discovering new algorithms, classifier driving higher relevance by better aligning ads with new users, and maps. We use Gemini to improve the pins, deeply relevant to users’ locations, interests, history, and intent. This work is improving ad relevance by nearly ten percent, leading to significant increase in engagement. We’re pairing the strength and prediction relevance with powerful conversation over the past year. We made over twenty improvements to search shopping strategies, smart bidding, and use Gemini to match user intent and advertise products and services more accurately and further drive performance. This level of granularity was previously possible with GPT. Second, on advertising tools, we Gemini help advertisers drive more efficient and effective campaigns. People more search in fragments, search conversationally, and share more context. We launched AI Max, help advertisers tap to the new way of searching and earlier this month, it moved a bit and proved performance quality, targeting and creativity. Take a look now. BigQuery one third more clicks for search spend, while ten is increasing the average value by fifty-five percent, and S saw ten percent search volume uplift with fifty percent of those queries net new to their business. We see significant opportunity as advertisers continue to make progress on AI readiness and the adoption of AI tools. For instance, more than thirty percent of our customers spend on users AI and will change AI Max performance max, and these advertisers are seeing more conversion for the same spend. Third, how we monetize new AI user experience search. We’re just bringing existing ads formats into AI experiences. We’re reinventing ads for this new era. Direct offers and AI more resonating with users and continued growth of positive customer feedback. Gary Allen and some of the latest partners we’ve now signed up to test this Google as pilot. We’re also exploring new formats for retailers. AI more ready surfaces organic product recommendations based on user’s query, and we’re testing new ad formats that display retailers’ sales relevant products. In addition, the retail industry is rapidly colliding around the open source universal commerce protocol or UCP, launched in January, partnership with the ecosystem. Last week, we welcomed Amazon Meta Microsoft Salesforce and Stripe as new members to the UCP council. They join founding members Shopify, Etsy, Target, Wix and Google to further accelerate transition towards a new future. Partners like Sephora and Macy’s have joined companies like Old Navy, more ready rolling out UCP and now redefine consumer journeys from discovery to checkout. Also, you just last week launched an AI commerce within AI more than search and Gemini app, shoppers can now review product recommendations, compare options, and complete three checkout for multiple purchases directly with AI and Gemini. Turning to YouTube, which now has led streaming watch time in the US for three consecutive years, we’re in unprecedented brand adoption and shareable in the moment they engage. We’re playing Gemini to better matching and discovering brands creators of all sizes. Gemini now powers YouTube creator partnerships, a centralized platform integrated directly to YouTube to help creators and Google as advertisers. We’ve also made it easier to buy premium ads space in popular podcasts by curating the most watched podcasts to popular genres. For example, Super Group partnered with YouTube creators, is actually on a multi-format short and long form TV campaign, resulting in ninety-three percent lift for their low screen products, fifty-five percent overall brand lift. Looking at monetization across YouTube, momentum continues in the living room, and demand continues to drive momentum in direct response, in particular with small advertisers. Brand to is benefiting from growth in the living room with continuous deal creator brands. YouTube subscriptions revenue.
继续推动发展纳斯，特别是YouTube Music和Premium。在Q1，YouTube Premium Live覆盖了23个国家，我们计划扩展到更多新兴国家。另外，我们的广告业务在全球的合作伙伴中，零售商、3C和Google，支持4D AI transformation。本季度，确保Target和Wayfair等领先的多渠道纳斯结合，与实施新的CPB合作伙伴将帮助我们实现AI专业知识和经验的扩展，从Discovery到Checkout，包括在Google Everywhere为他们的Country Business带来成功，以及所有客户和合作伙伴的持续信任。安，Over to you。Thank you, Philip. My comments will focus on year-over-year comparisons for the first quarter and lastly, otherwise. I will start with results at the Alphabet level and will then cover segment results. I’ll end with some commentary on outlook for the second quarter and full year 2026. We had an outstanding first quarter. The level 11 consecutive quarter of double-digit revenue growth. Consolidated revenue reached $109.9 billion, up 22%, or 19% in constant currency. Total cost of revenue was $41.3 billion, up 14%. Tax was $15.2 billion, up 11%. Other cost of revenue was $26 billion, up 15%, primarily driven by increases in depreciation, content creation costs, YouTube and compensation. Total operating expenses were 24% to $28.9 billion. R&D expenses increased 26%, driven by compensation, YouTube investment in talent, as well as depreciation. Sales and marketing expenses were up 23%, driven primarily by marketing investment to support the Gemini app and search, as well as compensation. R&D expenses increased 21%, primarily due to increases in compensation costs related to legal and other matters. Operating income increased 3% to $39.7 billion, and operating margin was 36.1%. Other income expenses was $37.7 billion, representing a meaningful increase from the prior year, primarily due to unrealized and non-marketable equity securities portfolio. Net income increased 81% to $62.6 billion, and earnings per share increased 82% to $5.11. We generated operating cash flow of $45.8 billion in the first quarter and $174.4 billion for the trailing twelve months. CapEx was $35.7 billion in the first quarter, with the overall majority of the spend in technical infrastructure to support the AI opportunities we see across the companies. Approximately 60% of our investment in infrastructure this quarter was in servers, and 40% was in data centers and network equipment. Free cash flow was $10.1 billion in the first quarter and $64.4 billion for the trailing twelve months. We ended the quarter with $126.8 billion in cash and marketable securities and $77.5 billion in long-term debt. And as we announced today, our board directors declared a 5% increase in the quarterly dividend. During the segment results, Google Services revenue increased 16% to $89.6 billion dollars, reflecting strong growth in search and subscription. Google Services revenue also benefited from strong effects telwin. Google Search and other advertising revenue increased by 19% to $6.4 billion dollars, driven by growth in the retail and financial services verticals. YouTube advertising revenue increased 11% to $9.9 billion dollars, driven by direct response advertising as well as network advertising revenue of $7 billion dollars, or down 4%. Subscription platform and device revenues increased 19% this quarter to $12.4 billion dollars, due to strong growth in both YouTube subscription, particularly YouTube Music and Premium, and Google One subscriptions, which benefited from increased demand for AI plans. Google Services operating income increased 24% to $40.6 billion dollars, and operating margin was 45.3%. The Google Cloud segment delivered outstanding results in the first quarter. Cloud revenues accelerated across all key areas and were up 63% to $20 billion dollars. Revenue growth was driven by strong performance in CPB, which continued to grow at a rate that was much higher than Cloud overall revenue growth rate. The largest contributor to Cloud growth this quarter was AI solutions, driven by strong demand for industry-leading models, including Gemini. In addition, we had strong growth in AI infrastructure to continue deployment of TPUs and GPUs, and core CPB continues to be sizable contributor, driven by demand for infrastructure and other services such as cybersecurity and data analytics. Worked together to deliver strong double-digit revenue growth, driven by increase in the number of seats and the average revenue per seat. Cloud operating income was $6.6 billion dollars, tripling year-over-year, and operating margin increased from 17.8% in the first quarter last year to 32.9%. Google Cloud backlog nearly doubled sequentially, reaching $462 billion dollars at the end of the first quarter. The increase was driven by strong demand for enterprise offerings and inclusion of TPU hardware sales that will reference earlier. The majority of the backlog is related to technical CP contracts, and we expect to recognize over 50% of the backlog as revenue over the next 24 months. In other bets, revenues were $411 million dollars, and operating loss was $2.1 billion dollars. For the past two years, we have been working to prioritize our first investment in the bets in Q1 of this year. We are completed external capital raise, the results in its consolidation for Alphabet. These five announcements combined with the announcement with results in its consolidation for Alphabet when the deal closes, which we expect to take place in Q4, and we continue to allocate significant resources to businesses where we see many opportunities to create value such as well. During our outlook, I would like to provide some commentary on factors that will impact our business performance in the second quarter and full year 2026. First, terms of revenues were pleased with the overall momentum of the business at current rates. We would expect to see a 6% of approximately 1% point of total revenue in Q2 compared to 3% points at 6% in the first quarter. In Google Cloud’s segment, we will begin to deliver TPU hardware to select groups of customers and their data centers. We expect to begin recognizing a small percent of the revenue from these agreements this year, with the vast majority of revenues to be realized in 2027. As important to mind, the revenue from TPU hardware sales will fluctuate from quarter to quarter depending on TPU’s shift to customers. And finally, we’re excited to welcome the world into Google Cloud with the closing of the acquisition March, and our fair pleased with the performance date. A couple items to highlight related to the acquisition first, we will be reporting the Google Cloud segment. Second, we expect those single-digit percentage point headline to Cloud operating margin for the remainder 2026 related to acquisition. Moving to investment, we are updating our full year 2026 capex guidance to $180-$190 billion, up from our previous estimate of $175-$185 billion to now include investment related to the acquisition in effect, which closes March. We are seeing unprecedented internal and external demand for AI computing resources. The investment we are making in AI is delivering strong growth, as evidenced by the record revenue and backlog growth in Google Cloud and strong performance in Google services. Looking ahead, the strong results in fourth quarter execution of the capital required to continue capture the AI opportunity, and the result we expect 2027 capex to significantly increase compared to 2026. In terms of expenses, as we discussed previously, the significant increase in investment in technical infrastructure will continue to put pressure on the P&L in the form of higher depreciation expense and related data center operations costs and energy. We also expect continued hiring in key investment areas such as AI Cloud and investing in marketing to support AI products. To conclude, Q1 was an outstanding quarter for Alphabet, and our team continues to execute with high level discipline and velocity, delivering amazing innovation. We look forward to sharing more in the coming weeks on our Google marketing life and brandcast. I want to take this opportunity to thank our employees for their contribution to our performance. So, our full
我来回答你的 questions。Thank you. As a manager, question. You will need to first of all tell us about any background noise we ask you to give your line. When your question is stated, your first question comes from Brian O’Wax with Morgan Stanley. Your line is now open. Thanks for your question. I ask you the first one. The number one, I recently asked you about how you were achieving certain key things. And making you focus on almost every week to make sure the plan is actually correctly. So let me ask you this: the third business, what is the area that you most excited about applying next generation compute to certain areas? The higher I see using compute power multiplier, workload will be. Thanks Brian. I’ll take the third one first. Obviously, you’ve seen we are taking advantage all investments building the German models and both these applying in certain German apps, driving innovation there. I’ll be using a more than they’re all contributing the increased product. I do think we have across across both these forces. You know, there is massive opportunity to go deeper. What we do for users, I think, you know, bringing agent flows, workload to consumers, you know, that is for further due, including the kind of search I see as huge opportunity ahead, and obviously we’re very, very leaning towards and putting ourselves in a good position to bring those experiences to search and create value. On the second question around around around TPU’s, you know, obviously, you know, we do think about it as you know, what are we doing to go cloud the help of customers, and you know, that’s the framework which we think about it. In that context, you know, there are situations where it makes sense. For example, you take something like capital markets where running the you know highly perform, you know, AI workloads, they wanted you know TPU’s in in their in their data centers. So there are you know and and those trends through across the world’s industries and certain cases frontier apps too. And so we are you know operation operation thinking about it, but I do think we stand back and think about it overall as operation for Google Cloud as the large providing infrastructure cloud. I am sure there are also TPU hardware to select for customers. Again, you know we we we do TAIERI approach and some for helps to get more economies of scale, scale in overall compute environment as well, and so helps us invest in the cutting edge which we need to do the next generation as well. Thank you. Your next question comes from Dagen with JPMorgan. Your line is now open. Thanks, Martin. Take your question. One for now, one for Philip. And is it 2027 capital little increase in TPU and qualifying? Are you thinking about current capital delivery delivery numbers? And what are you doing just last quarter and what will you do just last quarter? And will you talk more about the third queries and all time highs? And how are you thinking about how much revenue maybe can reach quarter third queries delivery as again the higher percentage queries than 20 percent? That’s exactly thanks. Thanks for the question, Mr. With your first question on capex and how we think about capex increase going to 2027. You’ve seen over the past several years increase capex every year, and we have done it very thoughtfully to meet the demand that we are seeing both from customers as well as demand across your organization. And you’re seeing the proof point the higher I see on that in terms of just the growth rate we’re seeing whether it’s growth rate within search or certainly the cloud business. And the opportunity we have within the cloud business. So as we’re seeing that robust demand across the business, we are looking at what can we do to support that growing demand, and the opportunity we have, and increasing capex to meet that demand will provide more clearly future call about what that number will be, but that’s the opportunity we’re seeing. Has it quite meaningful? And we want to make sure we capitalize that. We do it, and we’re responsible as we’ve done today. So on the second part of your question, first of all, just to be more clear, I mean we’re very pleased with the performance of our business here, and as I shared, Google services benefit from strong execution. That’s important to keep in mind. The strength we saw in search was not due to single driver, but was due to the result of many parts of our business showing strength and working very well together. Just the first thing to do very first is the retail finance that talked about how drove the greatest contribution. All all major very very close actually contributed, and we made hundreds of changes every quarter to improve user experience ever to experience. And so that’s really contributing to our performance here, and we’ve also been able to do very strong as performance while significantly involving the search results page. The course changing to grow as I mentioned there are more time high. We see overusing a more continuing to drive greater search users and growth overall. Queries including in commercial queries, use specific asking about the 20 percent coverage as I said before. I think with the ability to add on longer, more complex searches that were previously really difficult to monetize, and so an incredibly rewarding German models now across all four different structures driving improvements across the various areas highlighted in my prepared remarks. Thank you. My next question comes from Eric Sheridan with Goldman Sachs. Your line is now open. Thanks, Martin. Take your question. We’d like the first one just building on the search. So far, would you look the backlog you disclose today? So now what’s your team coming back to your comments on AI infrastructure and where you need compute how the position you either build capacity scale compute and do it the way that is not said sort of affected from a Morgan Stanley point as well as a compute standpoint just understand where you sit how do you plan to allocate other than be one and then Philip to bring in the conversation you refer to TPU and a lot of industry numbers around you TPU very quickly talk about what TPU means for the services business as a commerce scale in years ahead. Thanks, Martin. Thanks, Eric. Look, I do think part of me, I do think we’re genuinely different here. We’re unique in the market because we’re able to maintain the stack and the way we’ve developed the components from infrastructure models to platforms and tools, applications and needs, and the fact that we, you know, all frontier models, all the second, you know, really helps us stay ahead of the curve. And overall, the two breakthrough point on it, the deepness and in our security layers to keep everything safe. And I think we are only providing the market that offers all of these vertical stack. And so I, you know, so overall again, to my earlier comments to Brian, I think about it all as Google Cloud. We can we have many different ways to serve customers, so we can meet them, you know, a suit to their needs better than better than other other players here. And I do think, you know, I do think, you know, looking ahead, our ability to invest in this moment and stay at frontier, you know, I think puts us in a strong position. And I think we are doing based on tangible demand that we’re seeing, and and it’s not just on the revenue side, but you know, in terms of ROI, frame more.
And that’s what’s helping navigate this momentous one. And to the second part of your question, we’re in early stages of gener AI. Gener AI is more than just completing transactions; we’re on the sweet gener AI experiences, and it will really transform how we shop from discoveries to decisions, while helping our business differentiate themselves. We’ve been very intentional about creating the gener AI experiences for users, partners, for the entire ecosystem. And our goal is really to move the current world of shopping to consumers and focus on the enjoyable parts for their experience. Either shop faster, smarter, and think with gener AI. You no longer have to choose between speed and the vision to make commerce experiences more personal, more fluid, and we’re carefully designing space in gener AI to use the valuable components of shopping to be on just price, just customers, or brand loyalty, and more, while removing the friction of the process and just talking about the specific part of your question. And the universal commerce protocol and new understanding for gener AI actually across the shopping journey from the discoveries to the buying to the purchases, for the we just talk about, and it was really coupled with the industry here, including mentioned shopping and the rewards, and so on. And we received tremendous feedback from hundreds of top companies, payments partners, retailers, really interested in integrating, and it will help power new gener AI solutions for the general AI long shoppers to actually take out from the merchants right as they research and go and then go with the journey. So it’s very very exciting. Next question comes from Ross Evans with Barclays. Here, lines now. Thank you for the wonderful question. On the gener AI shopping experience, what’s the current market? The current market is really changing. How do you see the price and value coming through? How do you see the value coming through? And the understanding more between the core and the core. Look, our number one focus is obviously on the user experience here, and I think the most important part of this, what I mentioned before, carefully designing the space in gener AI to use actually the valuable components within the shopping journey to save the space of the usability, for interesting apps and advertising models. I think it’s also worth noting that beyond just the traditional agents, there’s a lot of additional ways we can use AI to improve shopping experience, and you can think about it like our apparel tools that are available in the US. You can think about Google Lens, so there’s a lot more to here, but I think keep our as we said before, we focus on the user experience here, and I think all else will follow if we pay attention to the point I mentioned. Next question comes from Mike Nelson with Moffat Nelson. Here, lines now. Thanks. Wonderful question. Next question. And go over higher. I want to ask you, how you designing how you how you repositioning products? Can you compare even your constraints? How do you decide between all the products you have and which products? What kind of things are you wanting to decide new? And then follow. I know we said some gener AI there’s more and more in that behind the shopping journey. You can get all the data, everything on that, and more data in the journey here. And yeah, on that, thanks. Thanks, Mike. I think great question. And on building bases, looking for the general AI helping me more and more, and thinking that look, I do think that the foundation we start with is what we need from our starting point to to develop models. The first, so what we need for you know training these models, and and so effectively compute needs for them because it’s a foundation for everything we do, and as the core principle, which we operate, and then obviously you know we we develop the plan ahead. We are we do you know we do long range plans on our on our core areas, be be search, be YouTube, and so on, as well as what we see in Google Cloud, and obviously in Google Cloud, you know we have we’re providing for price AI solutions, which you know which you know this quarter, you know had a 80 percent year-on-year increase from the prior year. So we’re seeing strong demand for general AI for price AI solutions. There, we see strong demand for infrastructure in Google Cloud, and several cases we’re seeing demand for people hardware, people hardware and others different sources. So, you know, we are we are more lead out than and working to allocate across across these areas. Obviously, we are compute constrained in in year, and as the cloud cloud revenue would be higher if we were able to meet demand. So, we are working through that moment, and you know we’re investing what we have robust, you know, long range planning for, and you know we we see strong operationally, and you know we are allocating that framework. And to the second part of your question, as said in my previous answer, we we obviously focus on the user first, and creating a really great user experience with all our product especially new products, and the significant monetization of gener AI. Our focus right now is on AI models, but it’s fair to say we really believe that more well AI models would transfer successfully to gener AI, and so today in the gener AI focus on free tier subscriptions or AI plans, which is more comfortable to our Google One new growth, but it’s also clear as always been the product scaling products for billions of people, and if done well, it can be really valuable and really helpful for commercial information, and at the right moment, we’ll share any plans as we said, but we’re not rushing anything here. Next question comes from Mark Schmallek with Bank of America. Here, lines now. Then, yes, thanks for the question. So, one more question for me, again. Yes, the future of advertising and consumer experience, and yes, the future of AI is very clear that consumers are using the AI tools to be more relevant, stream their purchasing journey, can be higher rates, and so it’s very interesting. What’s the future just being by that? Be changes again, faster than ever. Advertising tools that you’re launching, really, thank you. I think the way to think about this, really, to think about the exponential moment we see here for search, this the key part. AI is fundamentally changing how the world searches for and access information. Core search all time highest, and the traditional search really started with tablens, and now we have overviews and AI, and we have search more intelligent than ever, and a lot of far more complex questions, and we have lens, or search, search, and we have search lives, search lives now available to all countries and languages that support AI models, and show the exponential nature of it, and we have AI driven search campaigns, and we have now. And we can reach customers that’s the really wasn’t possible even years ago. You can add Google Translate, and so on, so feel the factor of this, and we’re we’re pretty good at placing our products where this is going. Next question comes from Ross Evans with Citi. Here, lines now. Then, thanks for the question. Maybe this one is for not you know we continue margins continue here. One of them is the integration of cross-border really the buyers and margins, particularly among cloud, the digital and the revenue, all margins, general, but we are seeing margins improve, more insights on the cloud business, more driving more expansion, obviously, you can see the pricing that would be helpful. Thank you. Let me help unpack the margin expansion. Obviously, we’re pleased to see that there are pushes and pulls across the business, including with sales, specifically. And with search as a top line, we see this robust, strong revenue growth, both in cloud Google services that provide leverage all the way down to the bottom line within engagement. And you know, we’ve been working hard to ensure we have we’re running a productive, efficient organization, and not just how we operate the business, but even.
And areas such as technical infrastructure, we are investing these significant capital investments in data centers and servers. We are looking at how we drive scientific process innovation within that organization, and that is reflected both in cloud services we allocate cost based on based on consumption. In the past, I talked about the appreciation associated with these investments that is in both Google Cloud and Google services. Google Cloud expanded margin quite significantly from a year ago, as you’ve seen in numbers that we just previewed. And a lot of it is is the top line growth that Google Cloud is providing producing, as well as incredible efficiency within the business. I will give Thomas and the team a lot of credit for running a very productive organization and making sure that we are supporting our customers and providing the services and products that they want and benefit from, continue to drive top line growth and do this well within the middle of the investment, all the way from very efficient technical infrastructure, thinking through how we leverage AI across business, as I mentioned, the use of cutting internally, how Gemini helps us there optimize our real estate footprint, and we’re going to continue to do this. This is not we’re not going to stop here. We’re going to continue to push for more efficiency. Knowing that we’re going to have the headwind associated with with the appreciation coming with higher capital. And very helpful. Our next question comes from Ken Gross with Wells Fargo. You’re line is now open. Thank you very much, two of three, please. First on the cloud capacity, could you speak about how your verticals capabilities enable you to navigate the supply chain, especially with increasing inflation constraints? Are you facing any supply chain price inflation constraints in 2026 and 2027 capital markets? And as part of that, maybe now could you talk? Could you update us on the allocation of two capacity, internal versus external cloud? And one more, please. Would you think about search query volume growth, where we’re seeing increasing use cases historically? You know, it’s always been free to the consumer, and and completely supported. Do you see future use cases where where certain consumer use cases are more likely to be a subscription, and and maybe different mix of the consumer quantity of search the new search opportunity? Thank you. Okay, maybe a few parts to maybe I’ll touch on it, and you know on on overall compute, you know I think it’s probably around how we think about allocation, compute across our our our businesses, and you know I think again the long-range planning that our voice frame works, you know gives a good view plan ahead. I do think we obviously we are you know working to complicate the supply chain and are more and more pointing out and factoring that into the incoming revenue. We give, but I think the scale with which we’re operating and and are able to do work across all layers, both you know our supply chain partners, strength of our diversified businesses, and the demand we drive, and are are frontier technology and and the investments, all through the fact, I think, I think they helps get into deeper partnerships all across the supply chain. I think that and I mentioned earlier, economy scale point as well, so all that factors in, you know, part of the way there I think in terms of in terms of search, looking, we are we’re proud to build models, all you know we are the frontier across the frontier, we do think about capability and the cost frontier deeply, so that we can serve users scale, but at the same time, we can bring in the most powerful models, the most demanding queries. But you know the future, as you are right, that you know you know valuable, as we see more and more valuable use cases, there there are going to be use cases where people will want want to use the most powerful models, and you know there may be different ways to accomplish that. So we’re going to put the users first, support them when they they want to use the product, and we’re already you know provide you know various tiers of our subscription plans, in which you can get access to more powerful models, and that ties across your Google user experience, and and including including search, and you know we’ve seen the momentum, you know we saw very robust growth in terms of our AI subscription growth, you know you know driven by interest in getting access to better Gemini models. So I think that sets us well. So the type of use cases people want, you know, are basically in search. Thank you. And our last question comes from Justin Post with Bank of America. You’re line is now open. Thank you for taking my question. I expect a lot of interest in your TPUs. So can you talk about the how you think about the opportunity there, and maybe how much bank on the backlog growth, the little bit of TPUs filed, and then second question, I’m just thinking about the margins on each general AI deals. How do you think about you know the hundred billion dollars coming in, and and the margins associated with those? It can be somewhere here, about 270. Thank you. Look, you know, overall, I would say we we tremendous interest in the tremendous demand for both AI solutions, so there infrastructure including you know massive interest in our you know GPU offerings as well as TPUs, and and so we are you know we are we are you know proud that we can provide customers with the very diverse you know breadth of our offerings, and and you know let them begin meet them in terms of their needs, and maybe I’ll I’ll pass on our to some color on the backlog growth. Yes. So the backlog, the TPU hardware agreements that Thunderbird is prepared for marks, are reflecting our our backlog of the 462 billion dollars. Although the majority of the backlog is still GPU agreements. Now, do you think about the total backlog just over half of it will convert to revenue in the next 24 months, and the TPU hardware sales, more specifically, we expect a small percent of them to see coming through revenue later this year, and then the majority to be realized revenue in 2027. And then anything on the big ID margin with the general AI companies? Look, anything to comment on any specific contracts? But overall, there was a lot of questions about how we allocate and remember in in a constrained environment, and we’re choosing the allocation across all these opportunities. We’re working for robust results. Thank you. Thank you, and that concludes our question and answers session for today. I’d like to turn the conference back over to Jim Friedland for any further remarks. Thanks everyone for joining us today. We look forward to speaking with you again on our next 2026 call. Thank you and have a good evening. Thank you everyone. This concludes today’s conference call. Thank you for participating. You may now disconnect.
🎧 收听原语音文件
本文由AI自动语音转录生成，内容仅供参考。