AI Semis Bounce Back: Was the AI Capex Panic Overdone?
Alphabet Q1 2026 earnings conference call
Key Takeaways (AI-Generated)
Financial Performance
- Consolidated revenue reached $109.9 billion, up 22% year-over-year (19% in constant currency)
- Google Cloud revenue accelerated 63% to $20 billion, exceeding this milestone for the first time
- Operating income increased 30% to $39.7 billion with operating margin of 36.1%
- Net income increased 81% to $62.6 billion and earnings per share increased 82% to $5.11
Business Highlights
- Google Cloud backlog nearly doubled quarter-on-quarter to over $460 billion
- Gemini Enterprise paid monthly active users grew 40% quarter-on-quarter
- Revenue from products built on Gen AI models grew nearly 800% year-over-year
- Waymo surpassed 500,000 fully autonomous rides per week, doubling in less than a year
Financial Guidance
- Updated full year 2026 CapEx guidance range to $180-190 billion, up from previous $175-185 billion
- Expect 2027 CapEx to significantly increase compared to 2026 due to unprecedented AI compute demand
- Expect to recognize just over 50% of cloud backlog as revenue over next 24 months
- Low single digit percentage point headwind to Cloud's operating margin for remainder of 2026
Opportunities
- Market Expansion: Expanding Waymo to 6 new cities in 2026, operating in 11 major US cities
- Product Innovation: Launching next generation TPUs with significant performance improvements
- Strategic Partnerships: Universal Commerce Protocol adoption with major tech companies joining as new members
- Unprecedented internal and external demand for AI compute resources driving growth potential
Risks
- Compute constraints limiting ability to meet demand - 'cloud revenue would have been higher'
- Operating in a complicated supply chain environment experiencing inflation and constraints
Full Transcript (AI-Generated)
Operator
Welcome everyone. Thank you for standing by for the Alphabet First Quarter 2026 Earnings Conference Call. At this time, all participants are in a listen-only mode. After the speaker presentation, there will be a question-and-answer session. To ask a question during the session, you will need to press *1 on your telephone. I would now like to hand the conference over to your speaker today, Jim Friedland, Head of Investor Relations. Please go ahead.
Jim Friedland
Thank you. Good afternoon everyone and welcome to Alphabet's first quarter 2026 earnings conference call. With us today are Sundar Pichai, Philip Schindler, and Anat Ashkenazi. Now I'll quickly cover the safe harbor. Some of the statements that we make today regarding our business, operations, and financial performance may be considered forward-looking. Such statements are based on current expectations and assumptions that are subject to a number of risks and uncertainties. Actual results could differ materially. Please refer to our Forms 10-K and 10-Q, including the risk factors. We undertake no obligation to update any forward-looking statement.
During this call, we will present both GAAP and non-GAAP financial measures. A reconciliation of non-GAAP to GAAP measures is included in today's earnings press release, which is distributed and available to the public through our Investor Relations website located at ABC dot XYZ / Investor. Our comments will be on year-over-year comparisons unless we state otherwise. And now I'll turn the call over to Sundar.
Sundar Pichai
Thanks, Jim. Hi everyone and thanks for joining us today. It was a terrific quarter for Alphabet. Our momentum was on full display at Cloud Next last week, and the month of May brings even more with I/O, Brandcast, and Google Marketing Live. I hope you'll tune in to see our progress. It's clear that our AI investments and full-stack approach are driving performance across our business. Search and Other revenue grew 19%. People love our AI experiences like AI Mode and AI Overviews, and they're 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 for the first time, and our backlog nearly doubled quarter-over-quarter to over $46 billion. Gemini Enterprise is seeing tremendous momentum, with 40% growth quarter-over-quarter in paid monthly active users for subscriptions. This was our strongest quarter ever for our consumer AI plans, primarily driven by adoption of the Gemini app. Overall, the number of paid subscriptions has now reached 350 million, with YouTube and Google One being the key drivers.
And our AI models have great momentum. Our first-party models now process more than 16 billion tokens per minute—up from 10 billion last quarter—as directly used by our customers via API. Today, I’ll share our progress across the AI full stack, then Search and Cloud, followed by YouTube and Other Bets. Starting with our AI infrastructure—it’s the foundation of our full-stack approach to AI, driving customer growth and product adoption. Our custom TPUs, Axion CPUs, and the latest NVIDIA GPUs continue to form the industry’s widest variety of compute options.
NVIDIA GPUs are a core part of our AI accelerator portfolio and will be among the first to offer NVIDIA Vera Rubin NVL72, in addition to the Blackwell- and Hopper-based instances already available on Cloud. Next, we introduced our A-series TPUs—individually specialized for training and serving—and able to take on the most demanding agentic workloads. TPU v5e provides high-performance model training with three times the processing power of Ironwood, and TPU v5i delivers cost-effective, low-latency inference with 80% better performance per dollar than the prior generation.
This exceptional infrastructure powers our world-class AI research, which includes models and tooling that continue to progress remarkably well. Gemini 1.5 Pro continues to push the frontier in reasoning, multimodal understanding, and cost efficiency. We have quickly expanded the Gemini 1.5 series of models to offer more choices for developers, including our cost-efficient Flash models. Gemini 1.5 Flash Live—our latest audio model—has improved precision and reasoning, making voice interactions more natural and intuitive. It’s now powering conversational features in Search and the Gemini app. Speech-to-Text is now available in 70 languages.
And with 1.5 Pro, our Deep Research agent received a major upgrade, including MCP support and native visualizations. Our generative media models are incredibly popular. Lyria 3 has generated over 150 million songs since launching on the Gemini app. Nano Banana 2 reached 1 billion images in nearly half the time of Nano Banana 1, and Veo 1.5 Lite is the most cost-efficient video model to date. On top of this, we launched Gemma 2, 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 are focused on pushing the next frontiers of foundation models, including intelligence agents and agent decoding. And we’re using the latest technologies to transform how we work as a company. For example, with Anti-Gravity, we are shifting to truly agentic workflows. Our engineers are now orchestrating fully autonomous digital task forces and building at a faster velocity. Much more to come here. Next, we are bringing helpful AI into the hands of billions of people every day through our products and 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 in Chrome. Early traction has been good, and this month we integrated Nano Banana 2 to make personalized image creation possible in the Gemini app. Maps recently got its most significant upgrade in over a decade. With Gemini, users can now have a conversation with Maps and get more personalized suggestions and intuitive directions. And the Pixel 9a launched to positive reviews, providing the best of Google’s AI features like Gemini Live and AI-powered camera capabilities.
Turning to Search, AI continues to drive Search usage, and queries are at an all-time high. We continue to invest in improvements to AI Overviews, 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 are seeing people ask more personal questions and receive responses that are uniquely relevant to them. We also rolled out agent-like experiences such as restaurant booking to new countries and launched new multimodal capabilities like Search Live globally.
We are also continuing to improve efficiency and speed, even as we've brought new AI features into our results page. We've reduced search latency by more than 35% over the past five years. And since upgrading AIO views 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 search at IO. Now over to Google Cloud. Google Cloud is differentiated because we are the only provided to offer first party solutions across the entire enterprise AI stack.
Our growth in revenue, operating margin and backlog highlights this differentiation. Our enterprise AI solutions have become our primary growth driver for cloud. For the first time in Q1, revenue from products built on our Gen. AI models grew nearly 800% year over year. We are winning new customers faster with new customer acquisition doubling compared to the same period last year. We are seeing strong deal momentum doubling the number of 100 million to $1 billion deals year on year and signing multiple billion dollar plus deals. And we are deepening relationships with existing customers. Customers outpace their initial commitments by 45%, accelerating over last quarter.
At Cloud Next last week, we introduced hundreds of new capabilities across our vertically optimized AI stack that are designed to work together for our enterprise customers. We introduced a new Gemini Enterprise Agent platform that empowers users to build, orchestrate, govern and optimize agents with the controls that enterprise customers need along with new capabilities in Gemini Enterprise app like projects, canvas, long running agents and 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, Citywelt, Merck and Mars Incorporated.
Our partner ecosystem plays an increasingly critical role in driving Gemini enterprise adoption, we saw NYNEX year over year growth both in seeds sold with partners and in the number of partners adopting it for internal use. This momentum is leading to accelerating usage of our models. Over the past 12 months, 330 Google Cloud customers each processed over 1 trillion tokens. 35 reached the 10 trillion token milestone To give agents business context from enterprise data to help them reason intelligently, we introduced a new agentic Data Cloud.
It includes across cloud, lake house, knowledge catalog and deep research agents, which combine research and analytical skills. As an example, using our Data Cloud, American Express is enabling Asian tech commerce at scale by moving an enterprise data platform along with hundreds of productions applications to Bigquery. Vodafone is proactively resolving outages, automating network planning, and precisely targeting capacity. Enterprise data has become critical for agents to reason our strength with Bigquery and Gemini. Enterprise has LED Gemini powered workflows in Bigquery to grow over 30X year over year as cybersecurity threats from the use of AI models accelerate.
Our expertise in AI and cybersecurity is driving strong demand for our agenting defense offerings. In March, we closed the acquisition of this, a leading cloud and security AI platform, which is an incredible fit for the moment we are in. We have seen tremendous interest from customers in our unique cybersecurity and AI products and services to protect their IT estate. The performance of this so far has exceeded our expectations. Together with Google's strict intelligence, security operations and AI models, this is helping organizations detect, prevent and respond to threats.
We introduced new Gemini powered agents for threat detection, continuous threat teaming and automated remediation to protect software code and cloud systems. Customers like Deloitte, Priceline and Shell are using our agentic defence to strengthen their security posture. All of this is powered by the AI infrastructure I mentioned earlier. Our TP US continue our leadership in performance, cost and power efficiency for customers like Thinking Machines Lab, Hudson River Trading and Boston Dynamics. As TPU demand grows from AI labs, capital markets firms and high performance computing applications will begin to deliver TP US to a select group of customers in their own data centers in the hardware configuration to expand our addressable market opportunity.
Turning to YouTube, where our momentum continues in the living room. US viewers are watching over 200 million hours of YouTube content daily. And as of March, we have reached a new milestone with over 10 million channels now publishing shorts each day. This level of daily activity is a testament to how people enjoy this content and how we have made it easier for creators. And in Q1, our YouTube Music and Premium offering saw its largest quarterly increase in the total number of non trial subscribers both globally and in the US since YouTube Premium launched in June 2018. I hope you'll TuneIn to brand cast on May 13th.
Moving to other bets, Waymo's on a great trajectory. It launched in Nashville a few weeks ago. That makes 6 new cities so far in 2026 and operations in 11 major U.S. cities in total. Waymo also surpassed 500,000 fully autonomous rights per week, doubling in less than a year. Wing continues to expand across the US in partnership at Walmart and DoorDash and announced plans to operate in the Bay Area. In summary, a terrific start of the year with so many great opportunities ahead. We are not slowing down. Huge thanks to all of our employees and our partners. See you at IO on May 19th. Philip, over to you.
Philip Schindler
Thanks, Ondor, and hello, everyone. As usual, I’ll start with the performance of Google Services and then cover the progress we’re delivering across Search, YouTube, and partnerships. Google Services revenue was $90 billion for the quarter, up 16% year-over-year, primarily driven by the continued growth of Search. Adding some further color to our results, Search and other delivered 19% growth, primarily driven by retail and finance. YouTube advertising revenue grew 11%, driven by direct response followed by brand and network. Advertising revenue was down 4% year-over-year initially.
With Search and other revenue, which delivered $60 billion in revenue for the quarter, we are accelerating the deployment of Gemini across our entire ads infrastructure to help 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 to our customers’ success: ad quality, advertiser tools, and new AI user experiences. First, on ad quality: AI is boosting our ability to deeply understand user intent for a given search query and to find the most relevant ad—even when we don’t have a direct user query.
We’re making significant strides in improving relevance in Discover. New AI models and classifiers are driving higher relevance by better aligning ads with unique user interests. In Maps, we’re using Gemini to ensure promoted pins are deeply relevant to a user’s surroundings, location of interest, history, and intent. This work is improving ad relevance by nearly 10%, leading to a significant increase in user engagement. We’re pairing the strength of prediction-driven relevance with bottom-of-funnel precision. Over the past year, we’ve made over 20 improvements to Search and Shopping bid strategies.
Smart Bidding now uses Gemini to match user intent to an advertiser’s products and services more accurately and further drive performance. This level of granularity was previously impossible to achieve at scale. Second, on advertiser tools: Gemini helps advertisers run more efficient and effective campaigns. People no longer search in fragments—they search conversationally and share more context. We launched AI Max to help advertisers adapt to this new way of searching. And earlier this month, it moved out of beta with improved performance and quality across targeting and creative capabilities.
Take Hilton EMEA: they captured one-third more clicks for one-fifth of the spend while simultaneously increasing the average booking value by 55%. And Etsy saw a 10% search volume uplift, with 15% of those queries being net new to their business. We see significant opportunity as advertisers continue to make good progress on AI readiness and adoption of AI tools. For instance, more than 30% of our customers’ Search spend now uses AI-enabled campaigns—AI Max or Performance Max—and these advertisers are seeing more conversions for the same spend.
Third, how we monetize new AI user experiences in Search. We aren’t just bringing existing ad formats into AI experiences—we’re reinventing ads for this new era. Direct offers in AI mode are resonating with users and continue to receive positive customer feedback. Gap, L’Oréal, and Chewy are just some of the latest partners who have now signed up to test this Google Ads pilot. We’re also exploring new formats for retailers. AI mode already surfaces organic product recommendations based on the user’s query, and we’re now testing a new ad format that displays retailers who sell those recommended products.
In addition, the retail industry is rapidly coalescing around the open-source Universal Commerce Protocol (UCP). We launched it in January in partnership with the ecosystem. Last week, we welcomed Amazon, Meta, Microsoft, Salesforce, and Stripe as new members to the UCP Tech Council. They joined founding members Shopify, Etsy, Target, Wayfair, and Google to further accelerate the transition toward an agentic future. Partners like Sephora and Macy’s have joined companies like Ulta Beauty, which are already rolling out UCP, and can now redefine consumer journeys from discovery to checkout.
Ulta Beauty just last week launched Agentic Commerce within AI mode and Search, and the Gemini app. Shoppers can now review product recommendations, compare options, and complete Streamline Checkout for eligible purchases directly within AI mode and Gemini. Turning to YouTube, which now has led streaming watch time in the U.S. for three consecutive years, we’re in an unmatched position to connect brands with the audiences they care about at the moment they engage. We’re applying Gemini to drive better matching and discovery between brands and creators of all sizes.
And Gemini now powers YouTube Creator Partnerships—a centralized platform integrated directly into YouTube Studio for creators and Google Ads for advertisers. We’ve also made it easier to buy premium ad space in top-tier podcast shows by curating the most-watched podcasts into popular genres. For example, Supergroup partnered with YouTube creator Lisa Koshi on a multi-format Shorts and long-form CTV campaign, resulting in a 93% lift for their Glow Screen product and a 55% overall brand lift. Looking at monetization across YouTube, momentum continues in Shorts and the living room, and demand gen continues to drive momentum—particularly in direct response—with smaller advertisers.
Brand is benefiting from growth in the living room, where we continue to scale creator brand deals and YouTube subscriptions. Revenue continues to grow faster than ads, particularly from YouTube Music and Premium. By the end of Q1, the YouTube Premium lineup was fully launched in 23 countries, and we plan to launch in more than a dozen new countries in Q2. As always, I’ll wrap with the progress we’re seeing across partnerships. Retailers are increasingly looking to Google to support their AI transformation. This quarter, Kingfisher, Target, and Wayfair closed significant multi-year cloud and ads deals.
Combined with the implementation of UCP, these partnerships will help deliver personalized AI driven A genetic experiences from discovery to check out. In closing, I'd like to thank Googlers everywhere for their contributions to our success and as always our customers and partners for the continued trust. Anat over to you.
Anat Ashkenazi
Thank you, Philip. My comments will focus on year over year comparisons for the first quarter, unless I state otherwise. I will start with results at the Alphabet level and we'll then cover our segment results. I'll end with some commentary on our outlook for the second quarter and full year 2026. We had an outstanding first quarter delivering our 11th 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%. Tech was 15.2 billion, up 11%.
Other cost of revenues was 26 billion, up 15%, primarily driven by increases in depreciation, content acquisition costs largely for YouTube, and compensation. Total operating expenses were up 24% to $28.9 billion. R&D expenses increased by 26%, driven by compensation due to investment in AI talent as well as depreciation. Sales and marketing expenses were up 23% driven primarily by marketing investments to support the Gemini app and search as well as compensation and G and A Expenses increased 21% primarily due to an increase in compensation and costs related to legal and other matters.
Operating income increased 30% to $39.7 billion and operating margin was 36.1%. Other income and expenses was $37.7 billion representing A meaningful increase from the prior year, primarily due to unrealized gains in our non marketable equity securities portfolio. Net income increased 81% to $62.6 billion and earnings per share increase 82% to $5.11. We generate operating cash flow of $45.8 billion in the first quarter and 174.4 billion for the Trail in 12 months. CapEx was 35.7 billion in the first quarter with the overwhelming majority of the spend in technical infrastructure to support the AI opportunities we see across the company.
Approximately 60% of our investment in technical infrastructure this quarter was in servers and 40% was in data centers and networking equipment. Free cash flow was 10.1 billion in the first quarter and 64.4 billion for the Trail in 12 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 of Directors declared a 5% increase in the quarterly dividend. Turning to segment results, Google Services revenues increased 16% to $89.6 billion, reflecting strong growth in search and subscriptions. Google Services revenues also benefited from a strong FX tailwind.
Google Search and other advertising revenues increased by 19% to $60.4 billion, driven by growth in the retail and financial services verticals. YouTube advertising revenues increased 11% to $9.9 billion, driven by direct response advertising as well as brand network advertising revenues of $7 billion were down 4%. Subscription platforms and devices revenues increased 19% this quarter to $12.4 billion due to strong growth in both YouTube subscriptions, particularly in 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 and operating margin was 45.3%. The Google Cloud segment deliver outstanding results in the first quarter cloud revenue. Accelerate across all key areas and we're up 63% to $20 billion. Revenue growth was driven by strong performance in GCP, which continued to grow at a rate that was much higher than Clouds overall revenue growth rate. The largest contributor to Clouds growth this quarter was AI solutions driven by strong demand for industry leading models including Gemini 3.
In addition, we had strong growth in a infrastructure due to continued deployment of TP US and GP US and core. GCP continues to be a sizable contributor driven by demand for infrastructure and other services such as cybersecurity and data analytics. Workspace again delivers strong double digit revenue growth driven by an increase in the number of seats and the average revenue per seat. Cloud operating income was $6.6 billion, tripling year over year and operating margin increased from 17.8% in the first quarter of last year to 32.9%.
Google Cloud's backlog nearly double sequentially, reaching $462 billion at the end of the first quarter. The increase was driven by strong demand for enterprise AI offerings and the inclusion of TPU hardware sales that Sundar referenced earlier. The majority of the backlog is related to typical GCP contracts and we expect to recognize just over 50% of the backlog as revenue over the next 24 months. In Other bets, revenues were $411 million and operating loss was $2.1 billion. For the past few years, we have been working to prioritize our efforts and investments in the other bets.
In Q1 of this year, Verily completed an external capital raise that resulted in its deconsolidation from Alphabet. G Fiber announced plans to combine with Astound Broadband, which will result in its deconsolidation from 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 meaningful opportunities to create value, such as Waymo. Turning to our outlook, I would like to provide some commentary and factors that will impact our business performance in the second quarter and full year 2026.
First, in terms of revenues, we're pleased with the overall momentum of the business. At current spot rates, we would expect to see an FX tailwind of approximately 1 percentage point to our consolidated revenue in Q2 compared to a three percentage point FX tailwind in the first quarter. In Google Cloud, as Sundar mentioned, we will begin to deliver TPU hardware to a select group of customers in their own data centers. We expect to begin recognizing a small percent of the revenues from these agreements later this year, with the vast majority of revenues to be realized in 2027.
It is important to keep in mind that revenues from TPU hardware sales will fluctuate from quarter to quarter depending on when TPUs are shipped to customers. And finally, we're excited to welcome the Wiz team to Google Cloud with the closing of the acquisition in March and are very pleased with the performance to date. A couple of items to highlight related to the acquisition: first, Wiz will be reported in the Google Cloud segment; and second, we expect a low single-digit percentage point headwind to Cloud's operating margin for the remainder of 2026 related to the acquisition.
Moving to investment, we are updating our full-year 2026 CapEx guidance range to $18–19 billion, up from our previous estimate of $17.5–18.5 billion, to now include investment related to the acquisition of Intersect, which closed in March. We are seeing unprecedented internal and external demand for AI compute resources. The investments we're making in AI are 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 reinforce our conviction to invest the capital required to continue to capture the AI opportunity and the resulting returns.
We expect our 2027 CapEx to significantly increase compared to 2026. In terms of expenses, as we've discussed previously, the significant increase in our 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 such as energy. We also expect to continue hiring in key investment areas such as AI and Cloud and are investing in marketing to support our AI products. To conclude, Q1 was an outstanding quarter for Alphabet, and our teams continue to execute with a high level of discipline and velocity, delivering amazing innovation.
We look forward to sharing more in the coming weeks at I/O, Google Marketing Live, and Brandcast. I want to take this opportunity to thank our employees for their contributions to our performance. Sundar, Philip, and I will now take your questions.
Operator
Thank you. As a reminder, to ask a question, you will need to press *1 on your telephone to prevent any background noise. We ask that you please mute your line once your question has been stated. Your first question comes from Brian Nowak with Morgan Stanley. Your line is now open.
Brian Nowak
Thanks for taking my questions. I have two. First, Sundar, on a recent podcast, you talked about how you were acutely constrained by compute—something you focus on almost every week to make sure you're deploying capacity correctly. So let me ask you this: as you look at the search business, what are the areas you are most excited about applying next-generation compute toward to generate an ROIC on that return in search over the next 12 months? And the second question is on the sale of TPUs to third parties. Can you help us philosophically understand the strategy around pricing them, given the high ROIC of using TPUs to power multi-year Google Cloud workloads?
Sundar Pichai
Thanks, Brian. I'll take the search one first. You know, obviously you've seen we are taking advantage of all our investments in building the Gemini models and both obviously applying it in search and the Gemini app, driving innovations in AIO views and AI mode, and they're all contributing to the increased usage of the product. I do think looking ahead across both these surfaces, there is a massive opportunity to go deeper in what we do for our users. I think bringing agentic flows and workflows to consumers in a way that’s easy for them to use—including in the context of search—is a huge opportunity ahead.
And obviously, we are in very, very early innings of all that. But our investments in our full-stack AI approach, I think, put us in a good position to bring those experiences to search, and I'm pretty excited about it. On the second question around TPUs, you know, obviously, we do think about it as: what are we doing through Google Cloud to help our customers? And that's the framework with which we think about it in that context. There are situations where it makes sense—for example, take customers like capital markets, where they’re running highly performant AI workloads and wanted TPUs in their data centers.
So there are—and those trends hold true across a diverse set of industries and, in certain cases, Frontier AI labs too. And so we are opportunistic about it. But I do think we step back and think about it overall as the opportunity for Google Cloud. A lot of it is providing infrastructure through the cloud. At times, it is direct sales of TPU hardware to a select group of customers. But again, we do take our OIC approach, and some of it helps us achieve greater economies of scale in our overall compute environment as well, which helps us invest in the cutting edge—something we need to do for the next generation too.
Operator
Your next question comes from Doug Anmuth with J.P. Morgan. Your line is now open.
Doug Anout
Thanks so much for taking my questions. One for Ruth and one for Philipp. Ruth, you talked about 2027 CapEx increasing significantly. I know you didn’t quantify it, but how do you think about the current CapEx trajectory and your ability to service this massive backlog you’ve built up just last quarter—and what will no doubt continue to grow going forward? And then, Philipp, could you elaborate on the drivers behind search queries reaching an all-time high? And how are you thinking about the potential to increase coverage of search queries—specifically, the ability to show ads against a higher percentage of queries than the roughly 20% you’ve historically monetized?
Anat Ashkenazi
Thanks, Doug, for the question. Let me start with your first question on CapEx and how we think about the CapEx increase heading into 2027. Over the past several years, you’ve seen us increase CapEx every year, and we’ve done so very thoughtfully to meet the demand we’re seeing from both external customers and internal needs across the organization. And you’re seeing the proof point—the ROI—on that in terms of growth rates, whether it’s within Search or certainly the Cloud business and the opportunity we have within the Cloud backlog.
So as we're seeing that robust demand across the business, we are looking at what we can do to support that growth and demand and the opportunity ahead of us, and increasing CapEx to meet that demand will provide more clarity in future earnings calls about what that number will be. But that's the opportunity we're seeing ahead of us. It's quite meaningful, and we want to make sure we capitalize on it, and we do it in a way that's responsible, as we've done to date.
Philip Schindler
So on the second part of your question, first of all, just to zoom out for a second—I mean, we're very pleased with the performance of our ads business here. And as I noted earlier, Google Services benefited from a strong FX tailwind, which is important to keep in mind. The strength we saw in search was not due to a single driver, but was really the result of many parts of our business showing strength and working very well together. If I just deep dive from a vertical perspective, retail, finance—I talked about it—and health drove the greatest contribution, although all major verticals actually contributed. We make hundreds of changes every quarter to improve the user experience and the advertiser experience.
And so that's really contributing to our performance here. And we've also been able to generate very strong ads performance while significantly evolving the search results page. Queries continue to grow, and as Sundar mentioned, they are at an all-time high. We see AI Overviews and AI Mode continuing to drive greater search usage and growth in overall queries, including commercial queries. You specifically asked about the 20% on the coverage side. And as I said before, I think with AI’s ability to better understand intent and many other related factors, there is upside in that coverage number.
And overall, the understanding we now have with Gemini around user intent has significantly expanded our ability to deliver ads on longer, more complex searches that were previously very difficult to monetize. As I shared earlier, we're now deploying our Gemini models across all of our ads infrastructure, and it's really driving improvements across the three key areas highlighted in my prepared remarks.
Doug Anmuth
Thank you both.
Operator
Our next question comes from Eric Sheridan with Goldman Sachs. Your line is now open.
Eric Sheridan
Thanks so much for taking the questions. Maybe two, if I could. The first one, just building on the answer so far when you look at the backlog you disclosed today. So now we'd love to know if you can come back to your comments on AI infrastructure and your unique approach and how that positions you to either build capacity, scale compute, and do it in a way that is—as was not said—effective from both a margin standpoint as well as a compute standpoint. Just to understand where you sit competitively in your mind relative to others. That’d be number one. And then Phillip, to bring you into the conversation, you referenced UCP and there’s been a lot of industry inertia around UCP. Very quickly talk to us a little bit about what UCP means for this services business as agentic commerce scales in the years ahead. Thanks so much.
Sundar Pichai
Thanks, Eric. Look, I do think part of—I mean, I genuinely believe we are differentiated. We are unique in the market because of our vertically optimized AI stack and the way we co-developed the components—from our infrastructure and models to platforms and the tools to applications and agents. And the fact that we own frontier models and our own silicon really helps us stay ahead of the curve. And on top of it all, just to emphasize an additional point, our deep investment in security layers keeps everything safe. And I think we’re the only provider in the market that offers all of these capabilities in a fully integrated vertical stack.
So, overall—and going back to my earlier comments to Brian—I view all of this through the lens of Google Cloud. We have many different ways to serve our customers, enabling us to meet them in a manner suited to their specific needs, better than other players in the market. And looking ahead, I truly believe our ability to invest at this moment and remain at the frontier puts us in a strong position. Importantly, we’re doing this based on tangible demand signals we’re seeing—not just on the revenue side, but also within our ROIC framework—and that’s what’s helping us navigate this moment responsibly.
Philip Schindler
On the second part of your question—look, we’re in the early stages of the agentic era. Agentic goes beyond merely completing transactions; we all know this. We see agentic experiences as additive, and they will fundamentally transform how we shop—from discovery to decision-making—while clearly helping brands differentiate themselves. We’ve been very intentional about creating a seamless experience that works for both our users and partners across the entire ecosystem. Our goal is really to eliminate the tedious parts of shopping so consumers can focus on the enjoyable aspects. For decades, you could either shop fast or shop smart. With agentic commerce, you no longer have to choose between speed and certainty.
Our vision is to make commercial experiences universally assistive, more personal, and more fluid. We’re carefully designing space and agentic workflows so users can recognize valuable elements of their shopping journey beyond just price—such as customer service, brand loyalty, and more—while removing the friction in the process I just mentioned. And this is precisely where the second part of your question comes in: the Universal Commerce Protocol (UCP), a new open standard for agentic commerce that functions seamlessly across the entire shopping journey—from discovery and purchase to post-purchase support, as I just described.
UCP was co-developed with industry leaders—including, as I mentioned, Shopify, Etsy, Walmart, and others—and we’ve already received tremendous feedback from hundreds of top tech companies, payments partners, and retailers who are eager to integrate. It will power a new checkout experience in AI mode within Search and the Gemini app, allowing shoppers to check out directly from select merchants right as they’re researching products on Google throughout their shopping journey. So we’re very, very excited about it.
Operator
Our next question comes from Ross Sandler with Barclays. Your line is now open.
Ross Sandler
Yeah, just following up on the last question on agentic shopping. So it seems like we're at the point in time where this is actually going to start happening finally. So Philip, just to elaborate a little bit—as you try, as you look at carrying the AdWords business from kind of the old way of doing things to this new agentic, frictionless shopping way—how do you see the price and volume growth trends for core AdWords evolving as you start implementing more agentic workflows and search?
Philip Schindler
Look, our number one focus is obviously on the user experience here. And I think the most important part in this is what I mentioned before. We are carefully designing the space in the agentic workflows for users to actually see the valuable components within that shopping journey. And the second you have that space, you obviously have the ability to introduce interesting advertising models. I think it's also worthwhile noting that beyond not just traditional agents, there are a lot of additional ways we can actually use AI to improve the shopping experience. You can think about it like our apparel try-on tools that are now available in the US, or Google Lens.
So there's a lot more to do here, but I think the key part is actually what I said before. We focus on the user experience here, and then I think everything else will follow if we pay attention to the points I mentioned.
Operator
Your next question comes from Michael Nathanson with MoffettNathanson. Michael, your line is now open.
Michael Nathanson
Thanks. One question for Philip. Senator—if I may connect Brian’s question and Eric’s question and go a little bit higher—I wanted to understand how you’re deciding, how you’re allocating which divisions and projects get excess capacity, even though you're constrained, right? So how do you decide between all the internal projects you have and the external projects? Right? What kinds of screens are you running to decide who gets the capacity? And then for Philip, I've noticed that you mentioned from the Gemini app that there are more and more images coming into the shopping journey. Can you talk about your thoughts on adding advertising to that app and what's guiding your decision-making here regarding adding ads on Gemini? Thanks.
Sundar Pichai
Thanks, Michael. I think that’s a great question. You know, on an ongoing basis, I’m looking forward to Gemini helping me more and more as I work through this. Look, I do believe the foundation we start with is: what do we need from an AAR and D standpoint to develop frontier models? So, what do you actually need—specifically for training these models—and effectively, the compute required for GDM, since it’s foundational to everything we do. That’s a core principle guiding how we operate. And then, obviously, with our ability to plan ahead, we develop long-range plans for our core areas—be it Search, YouTube, or what we see in Google Cloud.
And clearly, in Google Cloud, we’re providing enterprise AI solutions—which this quarter saw an 800% year-over-year increase compared to the prior year. So we’re seeing strong demand for Gemini Enterprise and our AI solutions there. We also see robust demand for infrastructure in Google Cloud. And as I mentioned earlier, in certain cases, we’re seeing demand for TPU hardware, as well as other data center components. So we’re modeling all this out and working to allocate resources across these areas. Obviously, we’re constrained by compute capacity in the near term—for example, our cloud revenue would have been higher if we could have met all the demand.
So we’re working through that moment right now, and we’re investing—but we have a robust, long-range planning framework, and we see extraordinary opportunities ahead. We’re allocating resources with that framework firmly in mind.
Philip Schindler
Regarding the second part of your question, as I mentioned in my previous answer, we’re obviously focused first and foremost on the user and creating a truly great user experience across all our products—especially your products—and specifically around monetization. In the Gemini app, our current focus is on AI mode, but it’s fair to say we strongly believe a format that works well in AI mode would translate successfully to the Gemini app. Right now in the Gemini app, we’re concentrating on the free tier and subscription offerings. And our AI plans have been a sizable contributor to the growth in Google One revenue.
But let’s also be clear: ads have always played a major role in scaling products to reach billions of people. And when done well, ads can provide genuinely valuable and helpful commercial information. At the right time, we’ll share any plans—as we’ve said before—but we’re not rushing anything here.
Operator
Thank you. Your next question comes from Mark Shmulik with Alliance Bernstein. Your line is now open.
Mark Shmulik
Yes, thanks for taking the question. Philip, one more on search performance, if I may. You’ve mentioned several times your focus on optimizing the consumer experience. Beyond higher query volume, is it fair to conclude that consumers are using these AI tools—Google’s or others—and that this is shortening their purchasing journeys and leading to higher conversion rates? And if so, is there a way to quantify how much of the strength in search is driven by this behavioral shift versus some of the newer advertiser AI tools you’ve been launching and rolling out? Thank you.
Philip Schindler
I think the way to think about it is really to consider the expansionary moment we’re seeing here for search. This is the key part—AI is fundamentally changing how the world searches for and accesses information. Of course, we’re at all-time highs. Understand that traditional search really started with 10 blue links, and now we have overviews in AI mode, which have made search more intelligent than ever. They let you ask more complex questions, and we have Lens or Circle to search, as well as Search Live. Search Live is now available in all countries and languages that support AI mode, again highlighting the expansionary nature of this evolution.
And we have our AI-driven search campaigns, enabling SMBs to reach customers at a scale that simply wasn’t possible even a few years ago—you can also add in tools like Google Translate and so on. So, when you factor all of this in, I feel we’re in a pretty good place and are quite excited about where this is headed.
Operator
Your next question comes from Ron Josie with Citi. Your line is now open.
Ron Josie
OK, thanks for taking the question. Maybe this one is for—not, you know—we continue to see margins expand here. I wanted to understand, perhaps, if you could break down the cost drivers or really the drivers behind margin expansion, particularly within Cloud. There’s a thesis out there that AI revenues are generally lower-margin, yet we’re seeing margins improve. So, any additional insights on the Cloud business and what’s driving that margin expansion—obviously demand, maybe pricing—that would be helpful. Thank you.
Anat Ashkenazi
Sure. Let me help unpack the margin expansion. Obviously, we’re pleased to see pushes and pulls across the business, including specifically within Cloud. I’d start with the top line: the robust, strong revenue growth we’re seeing in both Cloud and Google Services provides leverage all the way down to the bottom line on the income statement. And, as you know, we’ve been working hard to ensure we’re running a productive and efficient organization—not just in how we operate the business, but even in areas like our technical infrastructure. With the significant CapEx investments we’re making in data centers and servers, we’re also focused on driving scientific process innovation within that organization.
And that efficiency is reflected in both Cloud and Google Services as we allocate costs based on consumption. Previously, I’ve mentioned the depreciation associated with these investments, which impacts both Google Cloud and Google Services. As you’ve seen in the numbers we just previewed, Google Cloud’s margin expanded quite significantly year-over-year. Much of this is driven by the strong top-line growth Google Cloud is delivering, along with an incredibly efficient way of running the business. I’d give Thomas and his team a lot of credit for running a very productive organization and ensuring we support our customers with the services and products they want and benefit from.
Continue to drive top-line growth and do so effectively from the middle of the income statement, all the way down to our highly efficient technical infrastructure. We’re thinking through how to leverage AI across our business. Sundar mentioned the internal use of coding or how Gemini helps us optimize our real estate footprint, and we will continue doing this. This is not where we stop—we won’t stop here. We will keep pushing for greater efficiency, recognizing that we’ll face headwinds associated with depreciation stemming from higher capital expenditure levels.
Ron Josie
Thank you, very helpful.
Operator
Our next question comes from Ken Garofsky with Wells Fargo. Your line is now open.
Ken Garofsky
Thank you very much. Two questions, if I may. First, regarding cloud and capacity, could you discuss how your verticalized capabilities enable you to navigate a complex supply chain—especially one experiencing inflation and constraints? Are you factoring any supply chain price inflation into your CapEx commentary for 2026 and 2027? And as part of that—or maybe separately—could you provide an update on the allocation of compute capacity between internal and external cloud usage? And one more, please: when you consider search query volume growth, we’re clearly seeing expanding use cases. Historically, of course, search has always been free to consumers and entirely ad-supported. Do you foresee future use cases where certain consumer applications might be more effectively monetized through subscriptions, potentially shifting the mix away from purely ad-supported 'free' search toward new search opportunities? Thank you.
Sundar Pichai
Alright, Ken, there are a few parts to that. Let me touch on them. On overall compute, as I mentioned earlier, we’ve shared how we think about allocating compute across our businesses. Again, our long-range planning and ROIC frameworks give us a solid foundation for forward-looking decisions. Clearly, as you pointed out, we’re operating in a complicated supply chain environment, and we are factoring that into all the guidance we provide. But I believe our scale and our ability to operate across all layers—from working closely with supply chain partners who recognize the strength of our diversified businesses and the demand we generate, to our frontier technology and investments throughout the stack—gives us a significant advantage.
I think these factors help us build deeper partnerships across the entire supply chain, and as I mentioned earlier, economies of scale also play a key role. So all of this contributes positively in that context. Regarding search—look, we’re proud that we build models at all. We’re at the forefront across the entire frontier. We think deeply about both capability and the cost frontier so we can serve users at scale while also deploying the most powerful models for the most demanding queries. And you’re absolutely right about the future: as we serve increasingly valuable use cases, there will inevitably be scenarios where users prefer—and are willing to pay for—access to the most powerful models.
And you know, there may be different ways to accomplish that. So we're going to put the user first and support them in the way they want to use the product. And we are already, you know, providing various tiers of our subscription plans in which you can get access to more powerful models. And that applies across your Google user experience, including in search. And you know, you've seen the momentum—we saw a very robust quarter in terms of our AI subscriptions growth, driven by interest in getting access to better Gemini models. And so I think that sets us up well to serve the breadth of use cases people would want in all places, including in search.
Operator
Thank you. And our last question comes from Justin Post with Bank of America. Your line is now open.
Justin Post
Thank you for taking my question. I expect a lot, lot of interest in your TPU sales. So can you help us think about how you're viewing the opportunity there and maybe break down the backlog growth a little bit between TPUs and cloud? And then, secondly, just thinking about the margins on these big generative AI cloud deals—how do you view, you know, these $100 billion deals coming in and the margins associated with those? Can they be similar to your current cloud business? Thank you.
Sundar Pichai
Look, overall I would say we see tremendous interest—there's tremendous demand for both AI solutions as well as AI infrastructure, including massive interest in our GPU offerings as well as TPUs. And so we’re proud that we can provide customers with a very diverse set of offerings and meet them wherever their needs are. Maybe I’ll pass it over to give some color on the backlog growth.
Anat Ashkenazi
Yep. So the backlog—the TPU hardware agreements that Sundar referenced in his prepared remarks—are reflected in our cloud backlog of $462 billion, although the majority of the backlog is still GCP agreements. Now, as you think about the total backlog, just over half of it will convert to revenue in the next 24 months, and for TPU hardware sales more specifically, we expect a small percentage of them to come through as revenue later this year and the majority to be realized as revenue in 2027.
Justin Post
And then anything on the big AI deal margins with the generative AI companies?
Anat Ashkenazi
Look, I think there’s nothing to comment on regarding any specific contracts, but overall, earlier there were a lot of questions about how we allocate—and remember, in a constrained environment, when we’re choosing to allocate across all these opportunities, we’re working off a robust ROIC framework.
Justin Post
Thank you.
Operator
Thank you. And that concludes our question and answer session for today. I'd like to turn the conference back over to Jim Friedland for any further remarks.
Jim Friedland
Thanks everyone for joining us today. We look forward to speaking with you again on our second quarter 2026 call. Thank you and have a good evening.
Operator
Thank you, everyone. This concludes today's conference call. Thank you for participating. You may now disconnect.
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