Is this the real life or is this just fantasy?

Henry Jennings | Marcus Today 

AI is everywhere. Everyone is talking about it, investing in it, and fearing they’ll get left behind. Stock prices are soaring, valuations are stretching, and the headlines scream “bubble.” But is it really the dot-com 2.0—or something fundamentally different? Let’s break down what’s driving these markets, why the hype is so intense, and what it means for investors.

Over the last few months, many commentators have tried to time the U.S. market, often calling it a bubble—one very narrowly focused on AI through the big drivers: NVIDIA, Microsoft, Amazon, Alphabet, and Meta. This is creating a circular kind of valuation dynamic. Investors are pouring money into AI-exposed companies simply because “everyone else is,” rather than because of fundamentals. It reminds me of the Cold War arms race, or perhaps more presciently, the remuneration committees of many companies that keep pushing CEO and director pay higher simply because “the other guy” is doing it.

In the cosy boardrooms of Australia, that mentality tends to prevail. And, to some extent, the same thing is happening now with AI-exposed companies. We are beginning to see some silliness creep in. Many analysts argue that both the U.S. and Australian markets are entering bubble territory. Valuations are high, and in some cases, absolutely ridiculous.

Recently, we’ve seen huge runs on the ASX in gold miners and defence stocks like Electro Optic Systems (EOS) and DroneShield (DRO), and even peripheral players like Elsight (ELS)—with little regard for fundamentals. When you look at the profits and revenues of these businesses, they simply don’t justify their multibillion-dollar market caps. Part of the issue is that many technical-analyst “gurus” focus purely on charts, which always look good—until they don’t. Charts don’t take into account the fundamentals, and share prices can run rampant even when the underlying business is really not justification for the rises.

The bulls, of course, will tell you it’s different this time. Every frothy bubble always seems to be. During the dot-com era, analysts invented new ways of valuing companies—on “eyeballs” and “clicks”—because traditional measures didn’t make sense. Today, analysts are valuing companies, not on AI profits or ROI, but on how much they’re spending on AI. As Mark Zuckerberg put it: “It’s better to spend too much than too little and be left behind.”

Every tech company looks at Apple as a warning: once a market leader, now arguably left behind in the AI race. So, is it different this time? Well, yes and no. Unlike 25 years ago, today’s tech giants have extraordinary balance sheets and mountains of cash. Back in 2000, Facebook didn’t even exist; now Meta is a global powerhouse. Similarly, Microsoft, Amazon, and Alphabet each have tens of billions of dollars ready to invest in AI projects, acquisitions, or new technologies. This financial strength fundamentally changes the dynamics of the market.

But it’s not just financial strength that has changed the game. We now have passive ETFs that funnel billions automatically into the biggest companies. Success begets success, and the bigger a stock gets, the more ETF money flows its way. Add in algorithmic and AI-driven trading, and the velocity of price moves has become extraordinary. Look at Australia’s last reporting season: so-called blue-chip stocks like CSL plunged over 20% on their results, and volatility was the highest I’ve ever seen. With more trading run by black boxes, liquidity is an issue, swings are sharper, and valuations more extreme.

AI itself is also transforming the market. Investors are chasing potential rather than actual returns. The narrative is powerful: companies that invest heavily in AI are seen as future-proof, capable of dominating their sectors, and ultimately creating outsized profits. But at the moment, much of this is still a promise. Very few companies can yet show material ROI from AI. Revenues and profits are modest compared to the staggering valuations they command.

That said, the potential is enormous. AI promises not only cost savings through automation, but also enhanced productivity, smarter decision-making, and entirely new revenue streams. Imagine a logistics company that cuts delivery times by 30% through AI routing software, or a pharmaceutical firm that accelerates drug discovery by years. Even if only a fraction of these potential gains materialises, the impact on earnings could be transformative. That is what investors are pricing in today.

Another key difference from past bubbles is the interconnectedness of global markets. The dot-com boom was largely U.S.-centric. Today, AI investment, talent flows, and venture capital are global. Chinese tech giants, European AI labs, and Middle Eastern sovereign wealth funds are all competing for the same breakthroughs. Chinese tech has seen extraordinary gains this year. This adds both opportunities and risks. Regulatory developments, geopolitical tensions, or sudden changes in technology adoption can cause massive swings in share prices, sometimes in ways that are impossible to predict using traditional models.

Moreover, the speed of innovation is unprecedented. Twenty-five years ago, it could take a decade for a technology to disrupt an industry. Companies like Fairfax failed to see the writing on the wall.  Today, AI breakthroughs can propagate across the world in months, creating winners and losers almost overnight. The pace of change amplifies market volatility and forces investors to adjust more quickly than ever before.

And yet, despite all this, there are lessons to be learned from history. The internet was revolutionary, but profitability took far longer than expected. Many dot-com companies failed spectacularly, yet a handful emerged as industry titans. AI may follow a similar path. Not every investment will pay off, but the companies that succeed could dominate entire sectors for decades. This makes AI both a source of incredible opportunity and heightened risk.

Finally, it’s worth noting the human factor. Investor psychology, FOMO, and herd mentality are just as important as cash flows and balance sheets. When a few high-profile AI wins make headlines, money floods in, often regardless of fundamentals. This dynamic is amplified by social media, financial news outlets, and online forums, creating a feedback loop that pushes valuations higher.

So, is this a bubble? Perhaps. But it is unlike anything we have seen before. The scale of investment, the depth of the balance sheets, the speed of innovation, and the potential economic impact of AI all differentiate it from previous market manias. Returns may be modest at first, but the underlying technology has the potential to reshape industries, economies, and societies. Investors who recognize both the opportunities and the risks are likely to be the ones who navigate this new era successfully.

Conclusion – What Investors Can Take Away

For investors, the key takeaway is balance. AI represents a revolutionary shift, but hype often outpaces reality. It pays to focus on companies with strong balance sheets, clear AI strategies, and the financial discipline to turn potential into profits. Be wary of chasing momentum purely because “everyone else is investing.”

Diversification remains critical. Even within AI, not every company will succeed. Spreading exposure across established tech giants, promising mid-cap innovators, and selectively in AI-adjacent industries (like semiconductors or cloud infrastructure) can mitigate risk while still capturing upside.

Timing the market is notoriously difficult, and with AI-driven volatility, it may be even more so. Patience will be rewarded for those who understand the long-term potential. The AI revolution is not a short-term trade—it is a structural shift. Returns will come, but likely unevenly and unpredictably.

Finally, stay informed and skeptical. Track investments, scrutinise fundamentals, and understand the assumptions behind valuations. AI promises to change the world, but it will also challenge investors to separate the signal from the noise. For those willing to navigate the complexity, the opportunities are extraordinary—but so are the risks.

In short, AI is here to stay. But in the race for profits, strategy, patience, and discipline will distinguish the winners from the herd.

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