AI’s Next Trillion Dollar Opportunity! The AI STOCKS You Need To Own!

Let's talk about the next trillion dollar opportunity in the AI stock sector and specifically let's talk about bottlenecks because it is the bottlenecks. It is the sectors where demand is outpacing supply where truly the real opportunity exists. One of these we know we've talked about a lot and I've covered it in depth in my channel. It is number two, middle column here, memory. We're going to talk about memory in this video, but it ironically is actually not the biggest opportunity. I'm going to share with you the biggest opportunities, the other two AI sectors where there is so much demand and the supply simply is not going to keep up. It is these bottlenecks that present to you and I a trillion dollar opportunity to own these stocks. And I'm going to share with you seven or eight stocks that you need to be looking at and that you should consider adding to your portfolio. These stocks are the ones that you need to own these AI stocks. If you're new to me, my name is Austin. Please, please, please hit that like button and definitely hit that subscribe button because I'm building an AI stock community here covering memory, covering different sectors, all with the eye and the goal, the eye towards helping you make more money in this sector. Let's jump into this. Okay, so look, there's three bottlenecks that shape up AI's next trillion dollar opportunity. We're going to talk about the middle one first. We're going to talk about the one that we all know, memory. I've talked about it at length here on my channel and this also is an area where you need to remember this as we look out into the future as we look towards 2030 and 2033 and we look at where all of the money is going to go that is being spent by the hyperscalers Amazon Nvidia you know Meta so forth the vast majority of it's going to flow into these three areas okay and really that's where we need to keys keep we need to key in on this so memory is currently the biggest bottleneck. We all know it's very very well publicized. There's three main competitors SKHix, Micron, Samsung. They control 890% of the HBM, DRAMM, and NAND market. Okay? And it is the biggest bottleneck. It's the one that we all know. And and I mean I'm I'm not putting anything down as it associated with the memory AI stock sector. I love Micron. I own it. I'm buying some SKHIX this week. So forth. Okay. Agentic AI though is what we need to shift our focus towards because as AI shifts right here below this head this title. See this right here. As AI shifts from training models LLM large language models to running billions of AI agents which Agentic AI is the next massive wave and it is AI agents. There's three infrastructure bottlenecks. CPUs, memory, and networking. And inside of that is where we're going to dig in and we're going to expand on this and talk about this. So, continuing down this memory path real quickly, I kind of jumped to the middle one because it's the one that a lot of you in my audience already know. And you can see Agentic AI needs right here. Let me zoom in on this a little bit. Agentic AI needs HBM, DRAM, and NAM storage. Manufacturer shifting shifting capacity to HBM reducing supply of traditional memory. But again key here is that two demand curves are colliding into one constrained supply chain. Okay, because we now have a need as we look towards Aentic AI. It is going to need more DRAM and nan storage. HBM is still very very important but it's going to need all three associated with the deployment of Agentic AI and the Agentic AI market in general is looking to be three times 3x larger than the training models phase of AI which is what we've been in the LLM phase. All right, 3x. So, Micron is standing tall there and looking to benefit. Skhinx will benefit as well. Samsung will benefit as well. So, Micron probably the top company to watch as it comes on with, you know, the deployment of more DRAM and NAND um memory. Okay. So, let's jump back to this and kind of talk about things. So, we've got that 5.55 trillion capex. That's the number that's targeted to 2030. Okay, the capital is committed and I and I want to really reiterate this. We constantly every week see on Wall Street messaging coming the the questioning of capex expending and all that kind of stuff. And I've talked a lot about this on my channel, guys. This is not something you need to worry about. If we do get if we see the hyperscalers andor enterprise clients like General Motors and Ford and you know big big companies start to change their messaging about how much capital expenditure dollars they're going to deploy to AI then that is a different equation but nobody I repeat nobody is saying that right now okay so I want to re really reiterate and stress that okay so kind of going back here so the money is spent and who what decides who gets paid is all about a supply constraint and buying First, the shift from training models to running agents is rewiring all three markets. The CPU market, CPU market, the memory market, and the networking market. Okay? And by the way, it is the networking market that nobody's really talking about from an AI bottleneck standpoint and probably the biggest opportunity out of these three. Okay? So, continuing on, you need to understand how Agentic AI works. Okay? And right here in the yellow is really where it where it comes down to. So agentic AI agents behave like people. Each agentic AI node if you if you will needs its own compute the chip needs its own memory micron and constant communication networking that inverts the old hardware math and drives outsiz demand into three categories training treated as afterthoughts. Okay. The market is shifting and I don't think that Wall Street has quite caught up yet, at least as far as what their messaging is out on the street. And that's why I think this is so revolutionary. Okay, I've already mentioned this. The Agentic area will be roughly 3x the size. And by the way, the company that produced this is Spear. Um, and right here it is uh Spear. There's their naming right where was that? Oh my god. Right here. Uh, Spear. Spear Investing. Okay, go back up here really quick. That's the company produced this report and I agree with it 100%. Okay, so 3x the size of the training models. So CPUs are the most underappreciated inflection. Okay, the agentic ratio moves towards one CPU per GPU because every agent needs its own orchestration. So let's go back to this graphic. Okay, and now let's focus on number one. See over here on the left, this is a bottleneck. Well, Austin, we know Nvidia is there and all that kind of stuff. Yes, I know. But we're talking about a seismic shift in the CPU market as we move in from LLM AI, large language models, training models, if you will, towards Agentic AI. CPUs are becoming more important. Okay, CPUs from companies like AMD, Intel. Agentic right here. Agentic AI requires orchestration for every AI agent driving massive CPU demand. The CPU to GPU ratio is moving closer to a one:1. Historically, that ratio has been the other way. Okay, key points. One CPU could manage dozens of GPUs. Now, Nvidia is the winner in the GPU space. Don't misunderstand. Nvidia is also moving into the CPU space as well. And it has been for a while. One CPU managing dozens of GPUs. That was inverted. It was the other way. Now with Aentic AI, it's going the it's going now towards CPUs during the training boom. Okay. U now every AI agent needs its own orchestration. CPU demand is set to accelerate dramatically. Okay. Market outlook. Today the CPU market is a 35 to40 billion market. By 2030, over $200 billion dollar is how big that market will be. And it is most likely we're going to run into a potential bottleneck in that scenario from these potential winners. AMD, Intel, and ARM. So, let's take a look at those. AMD right now, this is current market value. Um, up about 3.4% in today's current trading session. So, you can see that ticker obviously is AMD. By the way, I'm going to be covering AMD more on my channel. ARM Holdings, ticker is ARM. It's down about 4.6% today. So, look into that one. Obviously, Intel, you ever heard of Intel? Probably have. It's up 5.67%. The entire kind of AI tech stock space is moving back up. We had a really good um inflation print report come in today. So, that's why you're seeing kind of things move in the right direction that way. So again, as we're looking towards these AI bottleneck spaces, look in the CPU space. All right. And so kind of in the model here, it is networking that it stands to look be to be kind of the most underappreciated biggest investment opportunity right now. We're going to get into that here in just a minute. Followed by CPUs and then kind of third by memory. Again, I'm not Don't misunderstand what I'm saying. Well, Austin, are you saying memory is the last? No, that's not what I'm saying. I'm saying that memory if you're looking at these three spaces every it's already very very widely well known about the memory shortage compared to demand right and I think it's a lot of that's already built in I think Micron still is the winner I think we're going to see Micron go past it $1500 price target and on its way to 2000 skinex is going to lift etc etc etc but if we're looking for and trying to identify those opportunities that may be underappreciated slash undervalued at this time it is networking followed by CPUs and then thirdly memory. Okay, we're gonna again jump into kind of now jump and shift here. Okay, kind of going back over here to kind of finish some other things. So CPUs are kind of one of the one of the ones that we we need to again think about. Okay, so if we before we move on to networking, a few final thoughts around memory right here. Gross margins have nearly doubled to 80% unheard of for a business that historically earned 30 to 50% in good times and went cash flow negative in bad ones. We've talked a lot about this on my channel about how historically memory has been very cyclical um prone to a lot of production and chips sat in warehouses and then had to be discounted which eroded price mar price price and eroded margins all those kind of things. Prices are up 7x from the cycle bottom flowing straight to Micron's bottom line and straight out of the budgets of Nvidia, Alphabet, Microsoft, you know the hyperscalers, right? Continuing to move on and again this drive is structural. It's a gentic AI. So memory becomes that really core key component right there sitting you know pure and level with it with the the semiconductor space. All right. And again we talked about the fact that two demand curves that have been independent are colliding into one constrained supply base. Microsoft Micron excuse me CEO sees quote no line of sight when supply catches up particularly in HBM and we think the squeeze runs into 2028 and beyond. And remember, Micron has locked in those 16 strategic customers. Hundred billion dollars in revenue uh committed and combined through 2030. We know about that. Memory has always sold as a spot, which is the reason it traded at a permanent discount historically for a cycl for cycl cyclicality. I can never get that right. Multi-year fixed pricing exactly what can dampen the downside and why the market is debating a rerating. I've talked about this at length about these 16 strategic customer agreements, how it's changing the n the cyclical nature and ultimately the AI boom is completely restructuring the memory sector and in and moving memory away from a commodity scenario. Okay. But key here is and I want to stress this is where this particular um article and this particular Spear Investings talks about the proof only comes from generating cash through a full down cycle which Micron has not gone through. Okay. And we may not really see a down cycle. So that's something to consider which is still a cycle away. Agreements do cut both ways. Customers could walk if the buildout slows. Now we don't know all the finite deed the finer details of these customer agreements. There's probably some type of get out clause if those companies should so desire. But I'll remind you that part of the strategic customer agreements that Micron put into place, it moved those companies to the front of the line. Do they want to give that up and lose their space as far as memory? Think of a company like General Motors of Ford. Are they going to walk away from crucial components, memory components from Micron that need to go into their cars to ship their cars? Do they are they going to walk away from those from those agreements? No, I don't think they're going to, but it is something that is relevant. Okay, so this particular report talks about two other really good uh actually three other really good opportunities and they call them the picks and shovels kind of associated with the memory memory space and we need to look at those as possible ones that you should look at maybe getting into and this is again sign of some show some some golden nuggets if you will nuggets if you will uh from possible investment opportunities and I'm going to be looking at these myself one of them is um KLA right here KLA Corporation again kind of that picks and shovels associated with memory but it's not a pure memory play by like owning for example Micron SKH okay so KLA ticker is KLAC currently up 4.6% 6%. You see that right there and if we look at kind of the one-mon chart you can see this dramatic move up. I mean it is just moved up dramatically. Okay. All right. So KLA another one mentioned again the kind of that picks and shovel scenario is Lamb Research. The Pix and Shovels associated with the memory space ticker is LRCX. Look at that one. Up five and a half% today. And on the one-mon chart, again, just that major swing up, kind of continuing to move, but we're on a little bit of a down tick there from its high 436, currently trading at around 347. So the, you know, you'd be picking it up at a little bit of a discount right there. And then the other one was Applied Materials. Ticker is AMAT. Currently trading up in this session 3.9 plus percent, trading at 597. And if we look at the one-mon chart, similar graph, right? That kind of looks similar, doesn't it? But you can see right here uh it's high 709 currently trading at 597. Again, a little bit of a discount off of that peak we've seen in the last month. So there's kind of three associated with the picks and shovels aspect which I really really do love associated with the memory kind of the memory sector. Okay. All right. Moving on. Okay. Okay, so let's jump back over to our graphic here and now shift our attention to the left side, excuse me, the right side of this and talk about networking, which quite frankly is the one that nobody is really talking about associated with a bottleneck, a trillion dollar bottleneck opportunity with the AI infrastructure buildout and that and part of that those 5.5 trillion capex dollars that coming a lot of them are going to go to this space as well. So networking may be the biggest opportunities as AI agents constantly communicate, right? There's there's constant communication, data movement explodes and it's going to explode and network infrastructure becomes critical. Think of it this way in the LLM in the LLM space, the training model space, which is kind of where we're in and we're moving out of that space and moving more towards the agentic AI space. That LLM, it wasn't it wasn't a con as much of a constant need for data to move. Yes, it was, but not like we're going to see in the agentic AI space, which again, it's just going to be constant communication. I mean, the the the network traffic is going to increase, you know, X X XXX. Okay. So the key point here is you want to focus on companies enabling both copper and optical networking as far as the physical the physical cabling in the data centers. There's this lot there a lot of discussions going on with is copper better is optical networking better and you should look at it like I don't care which is better because by the way a lot of these data centers have both. Okay. So you want to look at this go okay from a key point standpoint optical component manufacturing lead times right here continuing have stretched we're starting to see the lead times for the companies who are delivering and and developing this technology uh has is is stretched and if we look at what some of the actual cabling companies are let's take a look real quickly uh right here so you look at some of the suppliers right here on the cabling side it's Corning Um, it's momentum coherent. I love corning. I've done some videos on Corning. Those are suppliers in that kind of that in that part of the stack as far as the cabling goes. The cabling stack goes. All right, moving back over here. Fiber prices have risen 50%. We're starting to see that, right? Fiber, the demand is outpacing the supply. Say, okay, so fiber prices have risen 50 plus percent since January. and the optical networking market could eventually exceed $150 billion dollar. Remember, we're trying to identify opportunities here in these different AI bottlenecks. Okay, top companies to watch, Credo and Astera. So, let's take a look at their tickers and what's going on currently with them. So, you can see Credo right here is in today's trading session up 027 um percentage. you see right there and on the last one month you can see pretty significant move up. Uh we've hit a high in this month of 270. We're currently trading in that 230 range again. So not as much of a massive runup as maybe we saw you know in in kind of the the picks and shovels for the memory space. KA Lamb uh applied materials. Okay. So that was Credo. We saw that one. And then Astera Labs ticker when the screen will load here. Asterolabs ticker is ALAB right there and we are up 1.4% 4% and on the one month chart you can see pretty significant move up u in the just in the last 30 days where we've seen it move up from a price in you know prices well quite frankly in the $50 70 you know50 60 70 range all the way up to 480 right and now we're trading at 373. So you're seeing that people are already starting to identify that these are pretty key players in this networking space that we need to possibly be looking at as far as kind of that AI bottleneck space goes. Okay, so let's wrap up with a few final thoughts here. There are definitely companies that I think are the bigger opportunities and I think the potential winners are in the networking space, Credo and Astera Labs. I think in the CPU space it's AMD, Intel, ARM and ARM is really a good one there. And they kind of on the picks and shovels front associated with mic with the kind of that memory space, not necessarily pure plays like Micron, escort and or Skhinx. Not dissing those, okay? Just giving you other opportunities kind of in that picks and shovels. Again, we talked about equipment companies to watch Applied Materials, uh, Lamb, KLA. Remember the bottom line here in the lower right hand corner is that the next phase of AI is aentic AI. No one disputes that it is coming and it fundamentally shifts and changes the nature of where a lot of those capex dollars will go and it will go to these three sectors CPUs, memory, networking. Those are the three phases that are making up a 20, no, excuse me, five plus trillion dollar space heading into 2030. There you go. Thanks for giving me a few minutes. Appreciate you and I'll see you down the road.