Artificial intelligence (AI) is one of the strongest trends on Wall Street in 2025. I began trading in the 1990’s and the AI trend reminds me of the early stages of the dot-com boom during the late 1990s (in excitement, hype, and lofty expectations). When we look back in history the creation of the internet will likely go down with the same impact as fire, the wheel, or the printing press. Now, investors are wondering will AI have the same impact? The short answer is, only time will tell.
In the rush to find the next big monster stock, many investors are repeating old patterns that have historically ended with disappointment. The AI revolution is real, but investing successfully in it requires discipline, patience, proper risk management, and rational analysis. Remember, most dot com stocks are not around today. The same is true for other major technological disruptions like the airlines, railroads, and countless other examples.
Here are three common mistakes I see smart people making when they invest in AI stocks.
Mistake 1: Chasing Hype Without Fundamentals
The allure of the next big winner is extremely powerful and that causes many smart people to make emotional, not rational, decisions with their money. One common emotional mistake I see people make time and time again is thinking this time might be different and they jump in, after a big move up, and chase a big winning stock. The solution here is to have a plan, respect risk, and remember, this time is not different.
After you buy a stock, it can only do one of three things, go up, down, or sideways. It doesn’t matter if it is an AI stock, gold stock, or railroad. All stocks go up, down, or sideways. Even great companies that are around today that survived the dot com boom and bust, had huge swings in their prices and those swings would knock out most investors. It’s easy to get caught up in the hype and excitement. It happens to most people but respecting risk, focusing on fundamentals, and making rational decisions are keys to long-term success in the market.
It is also important to note that AI is full of visionaries, bold promises, and captivating stories. It’s easy to be pulled in by exciting headlines about startups developing new AI models, or tech giants unveiling massive investments in training computers to think “like humans.” Just like in the dot-com boom, the stories feel groundbreaking.
The problem? Many companies riding the AI hype lose money. Some are even startups with barely any revenue. The same was true during the dot com boom and subsquent bust. Typically, what happens is investors pile in hoping to capture outsized returns, but they often end up buying into businesses that can’t support their lofty valuations and ultimately lose money when the stock falls.
The history lesson: dot-com déjà vu
In 1999, companies with “.com” in their names raised billions, even when they had no plan to generate lasting cash flow. When the bubble burst, most collapsed. A similar pattern can’t be ruled out for AI. While some winners will emerge and dominate, many current players may fade into irrelevance or bankruptcy.
What fundamentals still matter in AI
A lesson often forgotten during speculative booms is that traditional financial metrics matter. Cash flow, balance sheet strength, and proven demand should anchor investment decisions. For chipmakers like NVIDIA that already generate substantial profits, the AI boom supports a strong existing foundation. But for early-stage firms, the risks can outweigh the potential if investors ignore fundamentals.
Investor takeaway: Always separate visionary storytelling from hard financial data. A revolutionary technology is not a guarantee of revolutionary profits.
Mistake 2: Overconcentration in One or Two Big Names
The temptation to “go all in” is real and is another common mistake I see very smart people make in various market cycles. NVIDIA’s meteoric rise has transformed it into one of the best-performing stocks of the decade, largely due to AI. Its chips are essential for training AI models, and its revenue has exploded as demand for data center hardware soars. For many investors, the temptation is to put a disproportionate share of their portfolio into one strong idea. The temptation is there for just about any stock, it especially when the stock is going up.
The same happened in past cycles. During the dot com boom, names like Intel, Cisco, Qualcomm, and Microsoft raced higher. During the smartphone revolution, it was Apple. Those who bet heavily on a single titan enjoyed enormous returns—but timing and risk management matter. Investors who bought those names at their peak lost a lot of money during the dot com crash.
Investor takeaway: AI is bigger than one or two companies.
Proper risk management and proper diversification across the value chain can help reduce risk while maintaining upside potential as long as AI stocks remain in favor.
Mistake 3: Ignoring Cycles and Valuations
The myth of endless growth and this time is different are very powerful.
Boom cycles make it feel like the good times will never end. In 2023 and 2024, AI fueled explosive stock runs, with market leaders adding billions to their market caps in months. The narrative was simple: AI will reshape everything, and therefore valuations don’t matter.
That mindset is very dangerous. No matter how transformative a technology, growth slows and expectations reset. Even industry titans experience profit cycles, regulatory pressures, and increased competition. Assuming AI leaders will post quarter after quarter of uninterrupted growth ignores how markets function.
Why valuation discipline matters in AI
When investors pay 100-400+ times earnings, they are essentially betting that hypergrowth will continue for years without fail. That leaves no margin of safety. If growth merely slows rather than collapses, stocks priced for perfection can still fall by double digits.
Tesla, for example, soared on future-oriented narratives about electrification. Yet periods of slower sales or increased competition triggered sharp corrections in the stock, even though the long-term thesis hasn’t disappeared. AI stocks face the same risk: growing markets, but volatile share prices.
Liquidity, rates, and market sentiment
Another overlooked factor is the broader economic cycle. AI companies thrive in markets with plentiful liquidity, like when interest rates are low and growth capital is abundant. Markets and the economy move in cycles. Investors who ignore this reality may get caught in market downturns that can be far more brutal than expected.
Investor takeaway: Even the best AI stocks can tumble if valuations get too stretched. A disciplined entry point, and strong respect for risk, matters as much as believing in the long-term story.
Putting It All Together: An Investor Playbook
AI is unlike any other technological wave because of its scope, touching everything from healthcare and finance to defense and entertainment. Yet human behavior in markets has not changed, and the same investor mistakes recur.
To avoid missteps, investors can build a playbook:
Prioritize fundamentals: Separate hype from balance sheet strength. Profitable companies with durable moats offer safer long-term prospects.
Diversify exposure: History has taught me that it is usually a good idea not to put all your money in one “hot” stock.
Respect cycles: Recognize AI leaders can endure corrections when valuations run too hot—patience, timing, and risk managemnet always matter.
Stay adaptive: The winners today may not be winners tomorrow. New stocks come all the time and shifts in regulation can disrupt even dominant players.
Measure conviction against risk: Ask whether your excitement is based on headlines—or on sustainable advantages.
Conclusion: Riding the AI Wave Wisely
Investors are right to be excited about AI. It will likely be as transformative as the internet, smartphones, or electrification. But the stock market has a way of turning great technologies into poor investments when enthusiasm divorces from discipline.
The good news: by avoiding these three mistakes—chasing hype without fundamentals, overconcentrating in one name, and ignoring valuation cycles—investors can improve their odds of capturing long-term gains without succumbing to short-term pain.
There is a very strong chance that over time, AI will create trillion-dollar companies. It will also produce plenty of losers. The key is remembering that markets ultimately reward patient, rational investors who separate stories from substance.