I'm Not Convinced the AI Bubble Exists

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The AI bubble is a speculative concept that the AI industry is extremely over-valued. If true, the value of most companies involved in AI (several of whom are worth well over a trillion dollars) will collapse, devastating the entire economy. If you check any online discussion about the financial situation of the AI industry, it's essentially taken for granted that the bubble exists and is going to pop any day now. I don't think that this is a reasonable assumption, though. Nobody can see the future, but I think that there's a pretty realistic chance that the meteoritic growth of AI companies in the past few years is justified, and that they have even more room for growth. Expenses Are Sky-High, But Constrained To say that AI companies are spending an absurd amount of money is an understatement. The debt and spending commitments for AI companies are handled through complex vehicles that make it difficult to tell exactly how much their expenses actually are (a serious problem, and one of the most salient points in favour of AI being a bubble), but they've committed to spending at least 3 trillion dollars so far. It's also been estimated that AI companies have already spent 1.9 trillion, bringing the overall expense of the AI industry to around 5 trillion dollars. This is unprecedented levels of investment, and AI just can't be profitable if this level of spending is maintained. However, there's no reason for why this level of spending has to be maintained in the first place. The reason why AI companies are spending so much money is to rollout data centres to run the AI in the first place. These expenses are one-off purchases, not regular operating expenses. Once all the data centres are built, AI spending is going to plummet. Outside of these expenses, AI doesn't cost that much to run. We don't have the full numbers for the entire industry here, but Anthropic's S-1 filing says that they make $2.08 for every $1 of compute. In other words, once you ignore the cost of building infrastructure, AI is very profitable. Crucially, the S-1 filing indicates that Anthropic has started to make more than their compute and infrastructure investments combined, which cuts against the idea that the cost of building data centres is inherently unsustainable. In a pinch, AI companies can also cut costs by no longer allowing people to use their products for free and temporarily suspending expensive AI research. This can be implemented instantly, whereas other kinds of expenses like leases and spending commitments are a lot harder to cut. The only serious long-term expenses to contend with here is the massive amount of debt that's been taken out to pay for these data centres in the first place. Like I said before, it's hard to really figure out these commitments because of the complex way that they're issued, but we can do some back of the envelope math. If the AI industry has to pay off 5 trillion dollars over the course of 20 years, that's 250 billion dollars a year. For context, Alphabet (parent company of Google and Youtube) reported earning almost 162 billion dollars of revenue just in 2019. Adjusted for inflation, that's an even more impressive 213 billion dollars. Because this is very rough math, the total needed revenue might come in to well over 250 billion dollars a year, but the point stands. Even though this is an enormous expense, paying it off isn't unthinkable with the data we have so far. Some of the debt is in convertible notes as well, which can be repaid through shares instead of cash. In the first 6 months of 2026, Anthropic has recorded 72 billion dollars of loss in the form of shares that are due to lenders. The cost is only so high because the valuation has skyrocketed to an estimated 1 trillion dollars, which means that Anthropic has more than enough equity to make lenders whole. Profits Can Grow, By A Lot In their S-1 filing, Anthropic records their revenue going from 41 million in 2023, 386 million in 2024, 4.585 billion in