$200B AI WAR - I Think This Stock Wins

Right now, the biggest companies in the world on Amazon, Meta, Microsoft, they are spending hundreds of billions of dollars per year building out AI infrastructure. And for a while, Wall Street was cheering this absolutely blindly. Now, they're pushing back as short-term cash flow profits are taking a hit. The question every investor needs to answer right now is, will it all end up being worth it? So, let me give you the real numbers first because I think when you see them written out, the scale of what is happening becomes very clear. Amazon is committed to spending roughly $200 billion on AI infrastructure. You didn't hear that incorrectly, guys. $200 billion. Amazon CEO stood in front of investors and defended that number. That is part of Amazon's business model. They have built their entire company on reinvestment and it's paid off tremendously in the last few decades. They take chances and they bet big on potential opportunities. Now, Meta, the company that owns Facebook, Instagram, and WhatsApp, they've raised its AI data center budget for just one single facility in El Paso, Texas to $10 billion. And then on top of that, they committed another 21 billion to a company called Coreweave to rent even higher amounts of computing power. And if you recall, Trump sat with Zuckerberg and asked them, "How much do you expect to spend in the next few years?" And Zuckerberg said, "$600 billion on capbacks." Microsoft is committed to $80 billion in AI infrastructure spending in one single year. And Alphabet, which is Google's parent company, and also the owner of YouTube, is spending at a very similar pace to Microsoft. Add it all up and you're looking at somewhere between 300 billion and 500 billion dollars being spent by just four companies in one single year on AI infrastructure. That is more than the entire GDP of so many countries. It's unbelievable in one single year on one new technology. Now let me explain what these companies are actually building. A data center is basically a giant warehouse full of very powerful computers. These computers are what make AI work. Every time someone uses an AI tool, every time you go to chat GPT or Claude and you type something in, the model learns from new information, every time your question gets answered by those companies, every time a business runs an AI process, it requires enormous computing power. And computing power requires data centers. So, these companies are all racing to build as many data centers as fast as they possibly can because they believe that demand for AI computing is going to keep growing for a very long time. That is exactly what Amazon CEO Andy Jasse has said repeatedly in messages to shareholders. And for a while, investors love this. More AI infrastructure meant a bigger moat, a bigger competitor advantage, a stronger position in what everyone agreed was the most important technology of the decade. That means more and more opportunity for future growth. Every earnings call where a CEO announced higher AI spending, the stock would rally immensely. Wall Street was rewarding the ambition. Then something shifted. And guys, we always talk about that. That's not going to last forever. Eventually, people will get tired of the story. And the push back started when investors began doing a simple calculation. You're spending $200 billion. When do you get it back? Guys, it's a very fair question. Spending money is very easy. Turning that spending into profits that justify the investment is much harder, especially when it comes to a new technology. And right now, the AI revenue being generated by these companies, while real and growing, is still a fraction of what they're spending to build that infrastructure. The gap between what they're putting in and what they're getting out is enormous for the time being. And that gap is showing up in the numbers. Free cash flow, which is actually cash generated from the operation of the business minus their capital expenditures, has been falling at all these companies because so much cash is going out the door to build the data centers. If you watch our other videos, we talk about the difference between free cash flow and net income. And we always say, look, they're spending so much on these data centers. It could very well pay off. But the question is, will it pay off? CNBC recently reported that Wall Street is genuinely uneasy about the size of these commitments, and you can see why. Guys, the end of the day, investors hate uncertainty. They're comfortable paying for a business that generates predictable cash today. They are much less comfortable paying for a business that is burning enormous amounts of cash today on the promise that it'll pay off enormously tomorrow, especially when tomorrow keeps getting pushed out further and further. That is the exact reason why companies like Costco and Walmart with lower growth and lower returns on capital are trading at higher multiples than Microsoft or Meta as we speak. There's also a real question about whether all of this infrastructure is actually needed. We've started to see examples that show the powerful AI models can be built with far less computing power than previously assumed. So if that's true, do they really need to spend all this money on data centers? Does Amazon need to spend $200 billion worth of their money on data centers? Or are some of those data centers going to sit idle earning no return? And then there's competition. Every one of those companies is building at the same time. Amazon is building, Meta is building, Microsoft's building, Google is building. when they're all done, will there be enough demand to fit all that capacity? Let me give a very simple analogy to this. Let's say all of a sudden we found every oil field in the entire world that could be tapped and every oil company went out there and put a drill right in there and we all of a sudden increase the amount of oil we're producing by 10x. What would happen to the value of that oil? Will some of these data centers end up being something like that where there's more supply than the market needs? The same way the fiber optic cable boom in the late 1990s left the ground full of unused cables following the dotcom bubble. These are the questions that investors should be asking and are making investors nervous. And guys, they're legitimate questions. Just because you're asking the question doesn't mean that it's not going to happen. But it's a good question to ask. And here is where I think the story gets a little more nuanced and way more interesting. So let me give you the flip side of the argument because I think the bears are asking the right questions, but they might be missing the full picture. Remember, it's important to see the full picture, both sides of the argument, and then determine for yourself which one is more plausible based on the price you're paying. So, let's think about what happened with cloud computing. In the early 2010s, Amazon was spending billions building out AWS, Amazon Web Services, which is their cloud computing platform. Investors hated it. The spending was enormous. The returns were not yet visible. Guys, I missed it on there. Analysts questions whether it made sense. And then AWS became one of the most profitable businesses ever built. AWS did $128 billion in revenue last year alone and over 45 billion of it went to operating income. So the companies that built CL cloud infrastructure early and built the most of it won. So the bulls making the AI case are saying guys this is that same moment again. Super investor Bill Aman actually recently said exactly that in an interview. He said that investors should be applauding the spending for future growth rather than punishing it. And I don't disagree with them. Doesn't mean that every time you invest in future growth, it's going to pay off. These are the questions to ask. The companies that build the most AI infrastructure now, that lock in the best relationships with enterprise customers, that have the most data and the most computing power, those are the companies that are going to win the next decade according to Acman. And the price of not building now is potentially losing the race entirely. Guys, this could be one of those situations where it's an all or nothing thing where the one who wins occupies 80% of the market. We don't know, but I think that's what these CEOs are thinking. And an Amazon CEO put it plainly when he defended the $200 billion spend recently. He essentially said, "We regret the times we underinvested in the past and we're not going to make that mistake again." And when you look at what AWS has become, you can understand why he feels that way. There's also something important happening on the demand side that some tend to underestimate. AI adoption across corporate America is still in its very early stages. Most companies have barely begun integrating AI into how they actually operate. The enterprise AI market, which means businesses paying to use AI tools, is expected to grow enormously over the next 5 to 10 years. And when that demand arrives, the companies that built the infrastructure early will be the ones capturing the majority of that revenue. The ones that waited will be paying premium prices to to try to catch up. So, who's right, the bears or the bulls? Honestly, I'm sure in some respect both are. Some of the spending will prove to be brilliantly timed. Some of it will probably prove to be excessive. The market is going to separate the winners from the losers over the next few years. And that's exactly why doing the work on individual companies matters so much more right now. And that's exactly what we do at Everything Money. Our in-house analysts, our community members, myself, we want to understand these businesses and determine what price we need to pay for shares today to do well over years to come. Now, the hardest part is determining what that future outlook looks like when the future's unknown, especially in a new field like AI. Now, the company I want to focus on today is Microsoft because Microsoft has been sitting at the center of everything we've been talking about. They are one of the biggest AI spenders. They are a software company. They are an infrastructure company. And they are one of the most durable businesses ever built. And let me explain what they do very simply, guys. Microsoft makes software that runs world's offices and our households. Word, Excel, PowerPoint, Outlook, Teams. Hundreds of millions of people pay for those tools every single month. that is a rockolid recurring revenue stream that does not disappear when markets get volatile. They run Azure, the second largest cloud computing platform in the entire world. When companies build AI tools, many of them are building on Azure. That means every dollar spent on AI by other companies often flows back into Microsoft as revenue. They are not just a spender in the AI AI arms race. They're also one of the main suppliers. They have a deep partnership with OpenAI, the company behind chat GPT, and have woven AI into their products through C-pilot. Now, Word with Copilot drafts documents for you. Teams with C-Pilot summarizes meetings. These are the tools hundreds of millions of people already use, now made more powerful by AI. The switching cost when it comes to Microsoft is enormous. The concern is the spending. Microsoft is committed to $80 billion in AI infrastructure in one fiscal year. Guys, that's real money coming out of their cash flow. And investors want to know when is it going to pay off. So, let's run the numbers and find out what the stock is actually worth right now because a lot of our community members have been discussing this exact company in recent months in our chat. Microsoft is sitting here at $417 per share. But if you're new to the channel, I want to remind you that is not the price of the business. The price of the business is the market cap. 3.12 trillion. Yes, you're buying a share, but you're buying a piece of a $3.12 billion business. Now, here's what I love. Enterprise value of 3.31. So, it's roughly $200 billion, which is the difference between market cap and enterprise value. That's essentially their debt. Guys, look at this. Their free cash from the last year was $77.5 billion. That's incredible. That means they can essentially pay off all their debt with three years of their free cash flow. And by the way, their cash flow is down a lot from their income because of how much capital expenditures they have. Guys, this company is selling for 40 times free cash flow, 26 times earnings. Usually, when free cash flow is a lot lower than net income, I get very apprehensive. Most investors do, but remember, they're spending a lot on capital improvements to build these data centers. I understand why they are so different because you'll find in other videos when I talk about the difference between net income and free cash flow. I will always say find out why it's different. That's really important to understand because a lot of times people can manipulate net income and they use that as a way of because everybody's focused on net income here. In this situation, I'm not as worried about that. Now guys, they pay a dividend of 08% which is beyond adorable and it only eats up 25 billion of their 75 billion in free cash flow. I say only because it's a small percentage 33%. Guys, great returns on capital in the last 5 years. Lower last year because they're because their free cash flow is lower. And look at this growth rate in revenue. 14% 14% 13%. These are over the last three, five, and 10 years. And guys, growing profit margin 33% a year for the last 10 years, 36 a.5% for the last five, 39% last year. So the question you have to ask yourself is, is this going to continue going? Their profit margin is getting better. That means even as they grow their revenue, they're going to grow their profit even faster. This is a great business. Now guys, I threw a lot at you here, a lot. And if you're new to investing or just new to our channel, this is going to feel overwhelming, but don't worry. It's been overwhelming for every great investor at some point. If you want to be a good investor, you got to tough through this. Luckily for you, I made a great and easy cheat sheet for all of these key metrics. So, click the link below or it's the link in the first pin comment. We will email you this PDF immediately. You'll have at your fingertips. It'll allow you to be able to speak the same language as us. And I assure you that you will get much better at this as you watch more videos. This is exactly why I teach on YouTube. I wanted people to start thinking like investors and not speculators, not thinking, great story, let me buy it. Great story, at what price? And in a couple minutes, guys, I'm going to show you the right price based on my assumptions that I want to pay for Microsoft. So, let's go check out the eight pillars here. Now, remember, eight pillars not are here to tell a story. They're not here to tell you buy or not buy. We have 2X, which is our our valuation metrics. Everything else is a check mark. So this says to us it's expensive. But is it? I don't know. Remember expensive means what's the future hold? If if God came down right now and said, "Paul, Microsoft's going to double its profit every year for the for the next 20 years, I would pay probably five times more for this company. But if they're going to grow it at 3% a year, this is too expensive." So I want you to remember that in and of itself, those data points don't mean much. It's what the future holds. And Microsoft future probably looks pretty good. The question is how good. Well, let's see what analysts think about their future. Look at this growth rate in profit. $17 growing to $32 in the next four years. That's almost double in a matter of four years. 24% 14.5 22 and 16% earnings growth. That is monster earnings growth for a company that's $3 trillion. And then look at their revenue. 335 billion growing to 600, 17 and a half, 15 and a half, 16 and a half, 17, and 14 and a.5% revenue growth for a company this large. Now, they're probably assuming some really good things on the AI front. Now, I'm not telling you they're right or wrong on that, but the question is, how likely is that? So, it takes us now to our stock analyzer tool. This allows us to take the story and the numbers and put them together. Now remember, I'm running this early on in this situation. And the reason being is I want to make sure that I even figure out is Microsoft worth more time because if I do all my assumptions here and the stock's selling for 417 and I think it's worth 100, I'm being hypothetical. Why spend any more time? It's got to fall 75% before I'm even interested. But if all of a sudden it's worth 400 to me or 500, I got to spend more time on it. So let's pull up the last time I did Microsoft in our chat here in our community. So, let's do revenue growth first, guys. You'll see my revenue growth assumptions are a lot lower than than analysts think. A lot lower than people think. So, I might be too conservative here. I did 7 911. I can understand if you did 7 10 and 13, 9, 12, and 15. I get it. But for me, I'm sitting there saying, let me be a little cautious because what if this we're too early in AI to know for sure if it's going to work out. Profit margin. I did 34, 37, and 40. And guys, I kept free cash flow and profit margin the same. Even though they've been different because over long periods of time, they'll equate out and they've been really hit hard on the free cash flow because of this AI spend. So, I'm okay with this. Now, what PE or price to free cash flow would I assign to the company 10 years from now at the end of my analysis? Well, guys, the market average over long periods of time is 15 or 16. But I always tell people, increase that number for good companies, decrease for bad companies. Guys, Microsoft's a great company. High returns on capital, good growth rate, solid, great moat. So, I put 20 23 and 26. Now, is that reasonable? I don't know. But I think this is a premium business. If this company was selling for 14 times earnings today with these kind of this kind of future, I'd be buying it up like crazy. Now, this 9% return is my intrinsic value return. I do not recommend buying it for intrinsic value. You have to put in a margin of safety. My personal one is going to be different than yours, but it's very important to understand what's what makes sense to you. So, I hit the analyze button. Hope is not a plan. I used to buy stocks hoping that they would go up, but hope doesn't protect you when the market turns. Hope doesn't help you sleep better at night. Hope it doesn't decrease your fear. I had to learn how to build a real strategy, one that makes sure that I personally never go to zero. Now, every investment I make is based on numbers, not hype. This is why I built everything money. It was built for me. I wanted the tools that gave me clarity, took the fear out of investing, and helped me make better decisions that helped me sleep better. People saw me using them on YouTube and said, "Paul, can you give us that software?" And I said, "Well, I can't cuz it's mine right now, but I can create it." And so, I did. And a real community was born. Real people sharing ideas, live chats, live streams, and tools that help beat 99% of investors. I still use these tools like the stock analyzer every single day. Stop guessing. Start learning. Click the link below. Try our trial. $7 for 7 days and see how confidence will replace your fear. Boom. I've got a low price of 3.45, high price of 672, middle price of 4.84. So, this is showing that it's probably worth my time to do more investigation. The question is based on today's price, if all of my assumptions occur in the middle, it's about 11% return. Is that enough for me? That is the question we have to ask right now. So guys, here's the bottom line in all of this. AI spending arms race is real. The numbers are huge and Wall Street's push back is legitimate. These companies need to show returns and right now the spending is far outpacing the visible payoff. But the question becomes, are we just missing the visual payoff? Do we know what's going to happen? AI is brand new. It is a bet. But here's what I keep coming back to. The companies that are building the most durable AI infrastructure today, the ones with the best cloud platforms, the deepest customer relationships and the strongest competitive positions are the ones that are most likely to win the next decade of enterprise AI adoption. On top of that, I like betting on the Microsofts, the Googles, the Metas of the world when they go in a new business field. Why? Because if they're wrong, they still have a phenomenal business behind them. The other companies, if they're wrong, they're probably going to zero or they're going to have to pivot tremendously and a lot of value will be lost. The spending is not necessarily irrational. It's a bet. It is a big bet. And the track record of these specific companies when they make big bets is actually pretty decent. That's why the most important thing is to analyze what the future of the businesses could look like and buy at reasonable prices. A simple process is good. Don't let anyone convince you otherwise. Now, if you want to see the three stocks that we think could be huge long-term winners from here, including some that are down significantly from their highs and look very interesting, click the link on your screen for our potential multibagger stocks video. Thank you for your time.