Is The AI Bubble Going To BURST?

So, are we in an AI bubble? And is the stock market going to crash? So, let's look at some history and go back to 1630. You're standing on the docks of Amsterdam as ships unload the latest tulip bulbs from the Ottoman Empire. Traders are shouting prices across the harbor, and buyers are fighting to get their hands on the rarest colors. You buy a few bulbs, sell them for a quick markup, and then do it again and again. Before long, everyone around you is trying to get rich from tulips. And after just a few years, some bulbs are selling for the equivalent of luxury homes. But by 1637, reality catches up. Buyers disappear, prices drop, and the bulbs you paid a fortune for become worthless overnight. This was one of the first recorded market bubbles. In the US, we've seen similar patterns play out many times. Bubbles are a normal part of financial markets, but everyday investors are often the ones left holding the losses when they burst. Today, there's a growing speculation that we may be in an AI bubble. And you might be wondering what that means for your investments if that starts to unfold. And that's exactly what I want to walk through today. I want to start by explaining what bubbles actually are. So, if you just want to see what this means for your ETFs, feel free to jump ahead. But, I really recommend watching this part first because history tends to repeat itself in investing. So, as you've seen with the tulips, bubbles are periods where prices rise far beyond what something is actually worth, driven more by hype than real value. Some historians debate whether tulips were a real bubble, but it's still one of the clearest examples of how bubble behavior works. If we had to plot it on a graph, it would look something like this. This progression happened in under 10 years. You can see how prices started slowly with early investors buying in during the stealth phase. Then momentum builds as more people notice pushing prices over the mean during the awareness phase. But the real spike happens during the mania phase where public excitement takes over, prices accelerate rapidly and people start buying simply because they expect to sell to someone else for more. Eventually the momentum breaks and what follows is a sharp collapse, wiping out most of the gains as prices return closer to their true value. Now just to be clear, a bubble and a crash aren't the same thing. This entire graph demonstrates a bubble building up and crashing, but a crash is just that final drop. So, all bubbles end in crashes, but you can have crashes that weren't preceded by bubbles, if that makes sense. And in many bubbles, you'll often see a brief recovery after the initial drop before the market falls again. This is something called a dead cat bounce based on the old Wall Street saying that even a dead cat will bounce if it falls from a great height. In the US, there have been around 5 to 10 major bubbles over the last century, including the dot bubble. So, if you think back, do you remember when the internet first arrived? My friends and I would sit around this old desktop loading random flash games and AOL chat rooms while his mom shouted that we had to get off the internet so that she could make a phone call. If you picked up the phone, you would hear that weird screeching noise or whatever dialup tone telling you that the line was busy. Now, we were just kids back then, and the internet was this fun new thing that we got to explore. But outside our homes, the markets were quickly changing. Investors thought online companies were the future. If a startup pitched an online business like selling pet supplies or delivering groceries, they threw money at them. This was brand new territory, so they weren't paying attention to traditional ideas like a business plan or whether the company was actually making any money. One example of this is Etoysoys, an online toy retailer that promised to take on traditional stores like Toys R Us. It was started by this guy named Toby Link in 1997, a former Disney executive who believed the internet would allow them to grow faster than any physical retailer ever could. At its peak, the company claimed to have over 2 million customers. But just four years later, in 2001, it filed for bankruptcy and sold most of its assets to KB Toys. if you remember that story. Now, this next story isn't verifiable, so take it with a pinch of salt. But one Wall Street trader remembers having a call with a client who was so impressed by the overnight gains of etos and acting on the advice of a smart son-in-law, wanted to invest $80,000. Luckily, he talked her down, pointing out that the company itself didn't look like it was doing very well, even though the share price had jumped from $20 to $76 on its first day of trading. He ended the conversation by saying, "I'll feel a lot better watching you lose $4,000 than I would if you lost $80,000." And she reluctantly agreed. Whether that conversation really happened or not, it shows how stock prices can disconnect from reality during a bubble. And companies like Cisco helped fuel the cycle even further. They were a networking hardware company that built much of the equipment needed to run the early internet. As investors poured money into internet startups, they spent huge amounts on servers, networking equipment, and internet infrastructure, which caused companies like Cisco to report explosive growth. Instead of looking closely whether individual startups were actually profitable, many investors pointed to Cisco's growth and took that as proof that the entire internet industry was destined to keep booming. Cisco made it appear as though the demand was real, but much of it was being fueled by investor money flowing in circles through the system. If you look at the graph for etos, you'll see a very similar pattern to the tulips. The price surges rapidly after launch, drops sharply, experiences that same deadcat bounce that we just talked about, and then continues falling until it's effectively wiped out. So, before I continue, just real quick, if you're someone who's new to investing, watch all of my videos, but still don't know how to start by yourself, you can download my road map that shows you exactly what to do within the next 14 days. And if you have more than $100,000 of uninvested cash just sitting in a lowinterest bank account, my team and I can jump on a call with you to guide you on what to do next. If any of this is interesting, you can download the road map below. So, now that we know what bubbles are, the big question is, are we currently in a bubble? The truth is no one knows for sure. After looking into both perspectives, I find myself hovering somewhere in the middle. On the one side, companies are investing massive amounts into AI infrastructure, but the industry's revenues are still relatively small in comparison. For example Amazon Microsoft Meta and Alphabet alone are expected to spend around $670 billion on AI infrastructure this year, while Open AAI and Anthropic together are only generating revenues of roughly $44 billion per year. On the surface, this looks like the pattern that we saw in the Tulip and bubbles. Investors pour money into AI. AI companies spend this money on infrastructure. Infrastructure companies report huge growth and growth attracts even more investor money. Over the last few years, AI quickly went from helping with basic writing task to building websites and generating realistic videos, even though a lot of it is, I feel, is just AI slop. But now, companies are spending dramatically more money and computing power on improvements that feel smaller than before. One study from CES found that increasing AI training spent from around $10 million to hund00 million only improve coding success rates from roughly 64% to 74%. And according to their projections, even a trillion dollar model would only push those odds to just over 91%, showing how much more expensive each additional improvement becomes. On the other hand, AI is already embedded across major industries with companies using it every day to write code, automate workflows, analyze data, and run support systems. This suggests that unlike some past bubbles, at least part of the investment in AI is tied to products and services that businesses are already actively using and paying for. The docom bubble was filled with startups that could be launched with a small team and a basic website. AI on the other hand requires enormous investments in chips, servers, electricity, and data centers before the technology can even function at scale. In other words, there's a lot more writing on this, which means the industry is tied much more deeply into the real economy than many past bubbles were. Just looking at my own business, my team and I use AI every single day. We use it to write video descriptions, as you'll see down below, brainstorm content ideas, review code, and fact check resources like the calculators and spreadsheets inside my road map. We even use AI agents for parts of our workflow because in some cases they're already cheaper and faster than hiring another person. For example, I've been using AI tools like Many Chat AI, Atlas, and Heroes to help reduce the sales cycle in my business, and I'm actually planning on spending more money because I find it cheaper than hiring someone else to contact my leads and analyze and consolidate all of my crazy data. Now, these tools are definitely not perfect yet. They still hallucinate, misunderstand my instructions, and occasionally go completely off the rails. But even with these flaws, they've already improved how quickly we can get our work done and even increase some parts of our revenue. If AI stopped improving today, if the tools we currently have are basically as good as they'll ever get, then I do think that there's a strong chance that we might be in a bubble because businesses probably won't keep increasing their spending forever just to keep the same level of output. But if AI keeps improving from here, if it becomes dramatically better at say reasoning, automation, coding, customer support, and business operations, then companies will most likely keep paying more for it because the productivity gains will justify the cost. And if this happens, then the massive investments we're seeing today may eventually line up with the real world value AI creates. But if you look back at the bubbles that we talked about today, you'll notice that at the time many people generally believe those investments also made sense, which is why personally I think trying to predict whether we're in a bubble is mostly just speculation. Of course, I don't know if we're in an AI bubble. And if you hear someone on the internet telling you that we are or that we're not, really, no one really knows for sure. But I strongly believe that AI is going to be a tool that everyone's going to use on a regular basis in the future. And for me personally, I believe that AI is just going to get better from here. So if we don't know for certain whether this is a bubble or not, what does this mean for your ETF investments? Well, when the do-com bubble burst, the NASDAQ fell by around 78% from peak to bottom. Can you imagine having a $100,000 portfolio and watching it fall to roughly $22,000? I have to admit, I'd probably be losing a lot of sleep if I saw that happen to my portfolio. But let's say you decide today that we're definitely in an AI bubble. So, you pull your money out of tech heavy ETFs like QQQ or VGT, which averages around 10 to 15% growth, and move it into something more defensive like dividend ETFs or bonds, which might average closer to around 6% growth. Then let's say that the AI bubble never fully materializes and tech continues growing over the next decade. If you moved to a $100,000 portfolio, you would end up with roughly $179,000 after 10 years instead of about $259,000. That's an $80,000 difference just from being too defensive too early. But let's say the AI bubble is real. Then yes, you avoid part of a major crash, but you also risk missing the recovery afterward because historically some of the market's strongest gains have happened shortly after major crashes. Even when markets fall, I tried to remember that lower prices also mean future buying opportunities. During the recent Iran Israel market fears earlier this year, many people were panic selling while my community and I were buying more shares of the ETFs we already believed in. And when the markets recovered, our portfolios recovered with it. Regardless of what the headlines say, my community and I are still bullish on long-term tech and innovation and continue investing in ETFs like QQQ, QQQM, VGT, and S&P 500 ETFs like SPYM, and VO. I even just added a couple more Amazon and Google shares to my portfolio just the other day. In the end, I personally think it's better to stay invested than to constantly jump in and out based on scary headlines or clickbait YouTube thumbnails. A lot of financial media and these social media influencers benefit from fear because it gets clicks, attention, and ad revenue. So, my plan is to stay calm and continue dollar cost averaging as I've always done. I'm not an economist or a market guru, so I'll never know exactly what's going to happen next, but I do trust the long-term investing principles that have informed my decisions this far. So, what do you think about the AI bubble? Is it something that's worrying you, or do you think AI still has a long runway ahead of it? Let me know some of your thoughts down below. And again, if you want to get my road map and hop on a call with me and my team, you can download it down below. And after you get it, I'll see you in this video