Alphabet’s full-year 2024 revenue increased 14% (or 15% constant currency) to $350 billion. Its operating margins expanded 500 basis points to 32% and its EPS grew nearly 39% to $8.04 year-over-year. Its free cash flow increased 5% to nearly $73 billion even though its CapEx increased 63%. Alphabet generated a FCF margin of 21% and FCF conversion (FCF/Net income) of 73%. Its FCF conversion of 73% is below its long-term average going back to 2015 of 105%, but my perspective is that Alphabet spent a combined $102 billion in twelve months on R&D and CapEx ($49.3 billion in R&D and $52.5 billion in CapEx) to reinvest in growth and fortify its moats, yet still generated $73 billion in free cash flow. I suspect that, in time, its FCF conversion will approach 100% again. At this point in its massive investment cycle, its returns are still rising. It generated a 2024 return on equity (ROE) of 33% (up from about 27% in 2023) and return on invested capital (ROIC) of 21% (up from about 18% in 2023).
Rising depreciation spend from this unprecedented CapEx cycle will act as a headwind to earnings and ROIC in the next few years but strong revenue growth and efficiency gains across the company could offset the margin compression. So, one scenario is that earnings growth slows and ROICs decline somewhat, but in this case, I think its excess return spread (ROIC minus WACC) will remain safely positive, and that it can still grow EPS by 10%-15% annualized over the next five years. But I think an equally likely scenario is that continued margin expansion at Google Cloud and internal efficiencies across the company from AI (some of which may be almost unimaginable today) result in Alphabet’s ROIC remaining stable or even rising and its EPS growing at the higher-end of my 10%-15% range (and possibly higher). Its net cash decreased to $67.5 billion in 2024 (down from $81 billion in 2024). But its net cash still makes up 15% of total assets and 3.4% of its market cap. Alphabet is using its massive balance sheet and FCFs to return capital to shareholders via a growing dividend and share repurchases. It returned nearly $70 billion in 2024.
Alphabet is a text-book case of a hated stock. At $170 it currently trades at a NTM P/E of 19x, which is a discount to its long-term average of 23.5x and a discount to the S&P 500 (which trades at a NTM P/E of 21x according to FactSet on Feb 28, 2025). Alphabet, in my opinion, is not only clearly higher-quality than the average business in the S&P 500 (and therefore deserves to trade at an above-average multiple), but I think it’s one of the highest quality businesses in the world. Yes, still.
Here is another way to think about its relative valuation. Its closest peers (Amazon, Microsoft, Apple, and Meta) trade at an average NTM P/E of 30x and none of them have a P/E lower than 26x (Meta is at 26x). So, Alphabet trades at a confusing and strange eleven-point discount to the peer average and a seven-point discount to Meta. Alphabet’s ROIC, expected growth, and cost of capital suggests to me that its justified P/E should be in the peer-group range of 26x-30x. Like I said, it’s hated.
I think the market is concerned about the impact that AI data center investments will have on its future earnings, FCF, and ROIC, but that is true of the peer group as well, and as I said above, it’s still massively profitable, massively FCF-generative, and I think it has a long runway of per-share growth and that free cash flow will mirror net income over time. The market is also concerned that Gen AI is a competitive threat to its core search business, but I think that Alphabet is a pioneer and leader in AI and that it has more resources than almost any company on earth to invest in re-working search for an AI-first world (remember over $100 billion of investment spend in 2024 alone). I think AI search is Google’s game to lose rather than some competitors game to win. Any other company with the financial profile that I just laid out that is also a clear leader in AI (and btw is also a leader in digital media/entertainment, autonomous driving, smartphone operating systems, and is one of the three largest full-stack hyperscale cloud providers, with optionality coming from quantum computing, fiber, and a variety of other bets) would likely get rewarded with a P/E multiple of 26x to 30x (or possibly even higher).
Mega-cap tech companies like Alphabet, Amazon, Meta, and Microsoft are positioned to win in the AI world because they provide the crucial foundational infrastructure layer (and platform layer) with their global (and growing) network of datacenters, their core infrastructure cloud platforms (in Google Cloud, AWS, and Azure), and their custom AI semiconductors (accelerators), but also because they have the most capital, the most users, and therefore the most data that can be used to train ever increasingly complex generative AI models. These company’s products extend from the enterprise to the consumer and that creates both cost and revenue synergies that competing companies just don’t have and won’t be able to replicate (in my opinion) because of almost impossibly high barriers to entry created by the hundreds of billions in capital and decades it would take to replicate their technological and computing power and infrastructure, as well as the constant flow of data they receive from their billions of users. There are 5 trillion search queries on Google each year.
I think it’s a forgone conclusion that the aforementioned companies (and a few other key AI infrastructure providers like NVIDIA) are winning (and will win) the infrastructure layer of the AI stack (and the infrastructure part of this AI buildout cycle), but I also think these companies will be leading providers of AI applications (apps) that will live in and sit on top of their infrastructure/platform layers because as mentioned before, they have the capital (rock solid balance sheets plus enormous FCF generation), the users, and the data to create AI apps that their users want. To give an idea of just how many users Alphabet has (and consequently how much user data), it has 7 products with at least 2 billion monthly users, and all 7 products are currently using/offering Alphabet’s generative AI model Gemini. Alphabet is also using its own AI tools internally to cut costs and improve efficiency and productivity. It’s still early days yet more than ¼ of all new code written at Google is generated by AI and then reviewed and accepted by human engineers. It’s hard for me to wrap my head around just how much progress on internal efficiencies/productivity these leading providers of AI tools will be able to make over the next 5 to 10 years. The future is here, and no one has any idea what it entails given the speed of development in these AI models. (BTW their infrastructure layers will not only host and deploy their own apps, but host/deploy all the apps from their customers as well).
Google Cloud gets cast as a distant third to AWS and Azure, but let’s not forget that Google Cloud is growing 30%, is taking market share, and is still under-earning (I think it has the potential for at least 1000 basis points of operating margin improvement). YouTube is a one-of-a-kind media asset and is gaining even more relevance in our influencer-based media and social landscape (ex: over 70 billion YouTube Shorts are watched every single day, and viewers watch over one billion hours of YouTube on their TVs daily). Google Cloud and YouTube alone generate combined annual revenue over $100 billion and are growing at very attractive rates. Waymo is the clear commercial leader in autonomous ride-sharing at this point, having conducted over 4 million trips in 2024 and driving over one million fully autonomous miles each week. Waymo is operating in Phoenix, San Francisco, and Los Angeles, and is planning to launch in Austin and Atlanta in 2025 and Miami in 2026.
My thesis: Alphabet has $67.5 billion in net cash, which is equal to about 15% of its total assets and 3.4% of its market cap. Its legacy business (Search) is arguably the greatest business in the history of the world. Yes, Search is under intense regulatory scrutiny and Google may be forced to remove Safari as the preferred Search tool on Apple and Android devices, but Alphabet also has seven products with 2 billion monthly users and 5 trillion search queries flow through the Google AI engine each year. It also has the equivalent of its own Netflix (with YouTube), the third largest hyperscale cloud company in the world in Google Cloud (which is arguably the most advanced AI cloud platform) that is taking market share with possibly 1000 basis points (or more) of operating margin expansion potential, the (currently) leading autonomous driving platform in Waymo, the largest mobile operating system in the world in Android, quantum compute optionality, and a host of Other Bets (moon shots) that provide additional upside optionality. Yet the stock trades at 19x forward, an unjustified discount to the market, to its own history, to its peer group, and to what a fair and warranted absolute P/E is for a business of this quality with a long runway of profitable growth. The P/E drops to 16.5x on 2026 consensus estimates.
Key Quotes from the Q4:2024 Earnings Call:
“For the full year 2024, revenue grew by 14%, or by $43 billion, reaching $350 billion. Google Services and Google Cloud each continued to see double digit revenue growth, coupled with margin expansion. YouTube and Cloud revenues combined ended the year at $110 billion annual run rate. And in 2024, we generated total [operating] income of $112 billion, an increase of 33% from 2023.”
“We delivered Free Cash Flow of $24.8 billion in the fourth quarter, and $72.8 billion for the full year 2024. We ended the quarter with $96 billion in cash and marketable securities.”
“In Q4, we returned value to shareholders in the form of $15 billion in share repurchases and $2.4 billion in dividend payments. Overall, we returned a total of nearly $70 billion to shareholders in 2024.”
“Turning to the Google Cloud segment, which continued to deliver very strong results this quarter, revenues increased by 30% to $12 billion in the fourth quarter, reflecting growth in GCP across Core GCP products, AI infrastructure and Generative AI Solutions. Once again, GCP grew at a rate that was much higher than Cloud overall. Healthy Google Workspace growth was primarily driven by an increase in average revenue per seat. Google Cloud operating income increased to $2.1 billion, and operating margin increased from 9.4% to 17.5%.”
“Moving to investments, starting with our expectation for CapEx for the full year 2025. As we mentioned on the Q3 call, as we expand our AI efforts, we expect to increase our investments in capital expenditure for technical infrastructure, primarily for servers, followed by data centers and networking. We expect to invest approximately $75 billion in CapEx in 2025, with approximately $16 billion to $18 billion of that in the first quarter.”
“I’m excited that we ended the quarter at $12 billion and a 30% year-over-year growth. Very impressive growth. And as I’ve mentioned in the prepared remarks, GCP grew at a much higher rate than overall Cloud. Two items to think about from a deceleration perspective, the first is we are lapping a very strong quarter [in] AI deployments in Q4 2023. The second is the one you’ve alluded to. We do see and have been seeing very strong demand for our AI products in the fourth quarter of 2024. And we exited the year with more demand than we had available capacity. So we are in a tight supply-demand situation, working very hard to bring more capacity online. As I mentioned, we’ve increased investment in CapEx in 2024, continuing to increase in 2025. And we’ll bring more capacity throughout the year.”
“And as you’ve seen in the comment I just made on Cloud, we do have demand that exceeds our available capacity. So we’ll be working hard to address that and make sure we bring more capacity online. We do have the benefit of having a very broad business. And we can repurpose capacity, whether it’s through Google Services or Google Cloud to support. As I said, whether it’s Search or GDM or Google Cloud customers, we can do that in a more efficient manner. We also look at every investment that we make to ensure that we’re doing it in the most cost-efficient way to optimize our data centers. As you know, our strategy is mostly to rely on our own self-designed and built data centers. So they’re industry-leading in terms of those costs and power efficiency at scale. We have our own customized TPUs. They are customized for our own workloads, so they do deliver outstanding, superior performance in CapEx efficiency.”
“Part of the reason we have taken the end-to-end stack approach is so that we can definitely drive a strong differentiation in end-to-end optimizing and not only on a cost, but on a latency basis, and a performance basis. Be at the Pareto frontier we mentioned. And I think our full-stack approach and our TPU efforts all give a meaningful advantage [in terms of the cost to generate one million tokens]. You already see that. I know you asked about the cost, but it’s effectively captured. When we price outside, we pass on the differentiation. It’s partly why we’ve been able to bring forward Flash models at very attractive value props, which is what is driving both developer growth. We’ve doubled our developers to 4.4 million in just about six months. Vertex usage is up 20x last year.”
“In terms of expenses. First, the increase in our investment in CapEx over the past few years will increase pressure on the P&L, primarily in the form of higher depreciation. In 2024, we saw 28% year-over-year growth in depreciation as we put more technical infrastructure assets into service. Given the increasing CapEx investments over the past few years, we expect the growth rate in depreciation to accelerate in 2025.”
“I think there’s been a lot of observations on DeepSeek. First of all, I think it’s a tremendous team. I think they’ve done very, very good work. Look, I think for us, it’s always been obvious over time. There’s frontier model development; but you can drive a lot of efficiency to serve these models really, really well and if you look at one of the areas in which the Gemini models shine is the Pareto frontier of cost performance and latency. And if you look at all three attributes, I think we lead this Pareto frontier. And I would say both our 2.0 Flash models, our 2.0 Flash Thinking models, they are some of the most efficient models out there, including comparing to DeepSeek’s V3 and R1. And I think a lot of it is our strength of the full-stack development, end-to-end optimization, our obsession with cost per query. All of that, I think, sets us up well for the workloads ahead, both to serve billions of users across our products and on the Cloud side. A couple of things I would say are, if you look at the trajectory over the past three years, the proportion of the spend towards inference compared to training has been increasing, which is good, because obviously inference is to support businesses with good ROIC. And so I think that trend is good. I think the reasoning models, if anything, accelerates that trend, because it’s obviously scaling upon inference dimension as well. And so, look, I think part of the reason we are so excited about the AI opportunity is we know we can drive extraordinary use cases, because the cost of actually using it is going to keep coming down, which will make more use cases feasible, and that’s the opportunity space. It’s as big as it comes, and that’s why you’re seeing us invest to meet that moment.”
“In Search, AI overviews are now available in more than 100 countries. They continue to drive higher satisfaction in Search usage. Meanwhile, circle to search is now available on over 200 million android devices. In Cloud and YouTube, we said at the beginning of 2024 that we expected to exit the year at a combined annual revenue run rate of over $100 billion. We met that goal and ended the year at a run rate of $110 billion. We are set up well for continued growth.”
“Let’s start with AI. Last quarter, I outlined the three areas of our differentiated full stack approach to AI innovation. Our leading AI infrastructure, our world-class research, including models and tooling, and our products and platforms that bring these innovations to people at scale. First, AI Infrastructure. Our sophisticated global network of cloud regions and data centers provides a powerful foundation for us and our customers, directly driving revenue. We have a unique advantage, because we develop every component of our technology stack, including hardware, compilers, models, and products. This approach allows us to drive efficiencies at every level, from training and serving, to developer productivity. In 2024, we broke ground on 11 new cloud regions and data center campuses in places like South Carolina, Indiana, Missouri, and around the world. We also announced plans for seven new subsea cable projects, strengthening global connectivity. Our leading infrastructure is also among the world’s most efficient. Google data centers deliver nearly 4x more computing power per unit of electricity compared to just 5 years ago. These efficiencies, coupled with the scalability, cost and performance we offer, are why organizations increasingly choose Google cloud’s platform. In fact, today, cloud customers consume more than 8x the compute capacity for training and inferencing compared to 18 months ago. We’ll continue to invest in our cloud business to ensure we can address the increase in customer demand.”
“Second, world class research including models. In December, we unveiled Gemini 2.0, our most capable AI model yet, built for the agentic era. We launched an experimental version of Gemini 2.0 flash, our workhorse model with low latency and enhanced performance. Flash has already rolled out to the Gemini app, and tomorrow we are making 2.0 flash generally available for developers and customers, along with other model updates. So stay tuned. Late last year, we also debuted our experimental Gemini 2.0 Flash Thinking Model. The progress-to-scale thinking has been super fast, and the reviews so far have been extremely positive. We are working on even better thinking models and look forward to sharing those with the developer community soon. Gemini 2.0 advances in multi modality and made of tool use enable us to build new agents that bring us closer to our vision of a universal assistant. One early example is Deep Research. It uses agentic capabilities to explore complex topics on your behalf, and give key findings, along with sources. It launched in Gemini Advanced in December, and is rolling out to android users all over the world. We are seeing great product momentum with our consumer Gemini app, which debuted on IOS last November. And we have opened up trusted tester access to a handful of research prototypes, including Project Mariner, which can understand and reason across information on a browser screen to complete tasks and Project Astra. We expect to bring features from both to the Gemini app later this year. We’re also excited by the progress of our video and image generation models. Veo 2, our state-of-the-art video generation model, and Imagen 3, our highest quality text-to-image model. These generative media models, as well as Gemini, consistently top industry leader boards and score top marks across industry benchmarks. That’s why more than 4.4 million developers are using our Gemini models today, double the number from just 6 months ago.”
“And we continue to drive research breakthroughs in quantum computing. At the end of last year, we announced Willow, our new state-of-the-art quantum computing chip that can reduce errors exponentially as we scale up using more qubits. Willow is an important step in our journey to build a useful quantum computer with practical applications. This technology holds so much promise, which is why there was real excitement around this breakthrough.”
“Third, our Products and Platforms put AI into the hands of billions of people around the world. We have seven Products and Platforms with over 2 billion users and all are using Gemini. That includes Search, where Gemini is powering our AI overviews. People use Search more with AI overviews and usage growth increases over time as people learn that they can ask new types of questions. This behavior is even more pronounced with younger users who really appreciate the speed and efficiency of this new format. We also are pleased to see how Circle to Search is driving additional Search use and opening up even more types of questions. This feature is also popular among younger users. Those who have tried Circle to Search before now use it to start more than 10% of their searches. As AI continues to expand the universe of queries that people can ask, 2025 is going to be one of the biggest years for Search innovation yet.”
“First, Google Cloud. Our AI-powered cloud offerings enabled us to win customers such as Mercedes-Benz, Mercado Libre and Servier. In 2024, the number of first-time commitments more than doubled, compared to 2023. We also deepened customer relationships. Last year, we closed several strategic deals over $1 billion, and the number of deals over $250 million doubled from the prior year. Our partners are further accelerating our growth, with customers purchasing billions of dollars of solutions through our Cloud marketplace. We continue to see strong growth across our broad portfolio of AI-powered Cloud solutions. It begins with our AI Hypercomputer, which delivers leading performance and cost, across both GPUs and TPUs. These advantages help Citadel with modeling markets and training, and enabled Wayfair to modernize its platform, improving performance and scalability by nearly 25%. In Q4, we saw strong uptake of Trillium, our sixth-generation TPU, which delivers 4x better training performance and 3x greater inference throughput compared to the previous generation. We also continue our strong relationship with NVIDIA. We recently delivered their H200-based platforms to customers and just last week, we were the first to announce a customer running on the highly-anticipated Blackwell platform. Our AI developer platform, Vertex AI, saw a 5x increase in customers year-over-year, with brands like Mondelez International and WPP building new applications and benefitting from our 200+ foundation models.”
“Vertex usage increased 20x during 2024, with particularly strong developer adoption of Gemini Flash, Gemini 2.0, Imagen 3, and most recently, Veo. We are also seeing strong growth in our AI-powered databases, data analytics, and cybersecurity platforms. Customers including Radisson Hotels are now using Gemini to Search and analyze multi-modal data from across multiple Clouds. Our AI-powered Threat Intelligence and Security Operations products help customers, including Vodafone and AstraZeneca, identify, protect and defend against threats. Our growing portfolio of AI applications is also seeing strong customer adoption. In Q4, we introduced Google Agentspace, which helps enterprises synthesize data with Google-quality Search, create Gemini-powered agents, and automate transactions for employees. In addition, we recently gave all Google Workspace Business and Enterprise customers access to all of our powerful Gemini AI capabilities to help boost their productivity.”
“Moving to YouTube. Nielsen data shows YouTube continues to be number one in streaming watchtime in the U.S., with our share of streaming now at a record high. On election day alone, over 45 million viewers across the U.S. watched election-related content on YouTube. Our early investment in podcasts is paying off. We integrated podcasts into the core YouTube experience, particularly with video. We are now the most frequently used service for consuming podcasts in the U.S., according to a recent Edison report. This success reflects our long-term approach of investing in emerging trends, from mobile to the living room. We now have over 250,000 creators in the YouTube Shopping affiliate program in the U.S. and Korea alone. We expanded YouTube Shopping at the end of last year to three additional countries, allowing even more creators to share their favorite products with fans and grow their businesses.”
“Last month, we announced the first beta of Android 16, plus new Android updates, including a deeper Gemini integration, coming to the new Samsung Galaxy S25 series. We also recently announced Android XR, the first Android platform built for the Gemini era. Created with Samsung and Qualcomm, Android XR is designed to power an ecosystem of next-generation extended reality devices, like headsets and glasses.”
“Finally, a few words on Waymo, which made tremendous progress last year, safely serving more than four million passenger trips. It’s now averaging over 150,000 trips each week and growing. Looking ahead, Waymo will be expanding its network and operations partnerships to open up new markets, including Austin and Atlanta this year and Miami next year. And in the coming weeks, Waymo One vehicles will arrive in Tokyo for their first international road trip. We are also developing the sixth-generation Waymo driver, which will significantly lower hardware costs.”
“Google Services revenues were $84 billion for the quarter, up 10%, driven primarily by 11% year-on-year growth in Advertising revenues. Strong growth in Search and YouTube advertising was partially offset by year-on-year decline in Network revenues. In terms of vertical performance, the 13% increase in Search & Other Revenues was led by Financial Services, followed by Retail. The 14% growth in YouTube advertising revenues was driven by strong spend on U.S. election advertising, with combined spend from both parties almost doubling from what we saw in the 2020 elections. Now, in Q4 we saw continued strong growth in revenues from Search. We had lots of exciting updates in December, and we’re rapidly integrating our AI innovation into our consumer experiences. We’ve already started testing Gemini 2.0 in AI Overviews and plan to roll it out more broadly later in the year. In Search, we’re seeing people increasingly ask entirely new questions using their voice, camera or in ways that were not possible before, like with Circle to Search. We’re making these benefits available to more consumers. Google is already present in over half of journeys where a new brand, product or retailer are discovered. By offering new ways for people to search, we’re expanding commercial opportunities for our advertisers. Shoppers can now take a photo of a product and, using Lens, quickly find information about the product, reviews, similar products and where they can get it for a great price. Lens is used for over 20 billion visual search queries every month, and the majority of these searches are incremental. Retail was particularly strong this holiday season, especially on Black Friday and Cyber Monday, which each generated over $1 billion in ad revenue. Interestingly, despite the U.S. holiday shopping season being the shortest since 2019, retail sales began much earlier, in October, causing the season to extend longer than anticipated. People shop more than a billion times a day across Google. Last quarter, we introduced a reinvented Google Shopping experience, rebuilt from the ground up with AI.”
“Shorts continues its ascent and is closing the gap with long-form. In 2024, the monetization rate of Shorts relative to instream viewing increased by more than 30 percentage points in the U.S., and we expect to make additional progress in 2025. We’re making it easier for advertisers to benefit from Shorts on all screens. We’re particularly excited by its success on connected TV, which now makes up 15% of Shorts viewing in the U.S. Using a combination of ad formats, Louis Vuitton reached their overall objectives on both long-form and short-form content. Their Shorts exceeded the luxury goods benchmark for average view duration by 89% for equivalent video lengths, while their long-form content exceeded the benchmark by over 15%, with strong engagement from Gen Z and Millennials. Looking into the Living Room, we continue to be number one in streaming watchtime in the U.S. for nearly two years, according to Nielsen. And our share of streaming is at a record high. Viewers globally streamed over one billion hours of YouTube content daily on their TVs in 2024.”
“We have also invested in podcasts, where popular shows like Club Shay Shay and Lex Fridman are increasingly a visual format. YouTube creators and viewers are embracing this. In 2024, people watched over 400 million hours of podcasts each month on living room devices alone. YouTube is now the most popular service for podcast listening in the U.S., according to Edison.”
“Subscription, Platforms and Device revenues increased 8% to $11.6 billion, primarily reflecting growth in subscription revenues, partially offset by the shift in timing of the launch of our Made by Google devices to the third quarter compared with the fourth quarter in 2023. We continue to have significant growth in our subscription products, primarily due to increase in the number of paid subscribers across YouTube TV, YouTube Music Premium and Google One. With regards to Platforms, we saw a slight increase in the growth rate in Play, primarily due to a strong increase in the number of buyers. Google Services operating income increased 23% to $32.8 billion. And operating margin increased from 35% to 39%, representing a meaningful margin expansion.”
“I certainly see opportunities for further productivity and efficiency. And this is one of our priority areas. And we’re going to do that so that we can make sure we continue to invest in areas such as AI and Cloud, where we see potential for continued growth. I’ll remain focused on areas that I’ve mentioned before, which include the technical infrastructure. So the $75 billion in CapEx I mentioned for this year, the majority of that is going to go towards our technical infrastructure, which includes servers and data centers. So ensuring we do that in the most efficient way is critical. Second is managing headcount growth, and we’re going to be investing in areas of growth, such as AI and Cloud. But looking across the organization, moderating that growth will be important. Optimizing our real estate footprint is one of the areas I’ve mentioned. We’re continuing to focus on that, as well as looking at how we simplify the organization. We previously mentioned bringing like areas together. Sundar talked about bringing some of the AI research teams together so that we can operate with increased speed. But also, how we operate within the organization, using our own AI tools to how we run the business. Whether it’s the code that Sundar mentioned on the previous call, writing code with AI. Or even running some of our key processes using AI tools. So we’re looking at all that. This is not a one-quarter type of effort.”
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