How to Thrive in the AI Stock Boom Without Getting Burned: Essential Lessons from Previous Bull Markets

The AI revolution is here. Avoid traps, learn from past booms, and profit in this once-in-a-lifetime opportunity: Part 1 of a series.

The AI revolution is reshaping industries and creating unprecedented opportunities. For investors, this could be a once-in-a-lifetime chance to build wealth. But let’s face it: navigating a fast-evolving market is anything but easy. History is filled with examples of investors who got caught up in the hype or missed out altogether. To make the most of this revolution, it’s crucial to learn from the past and avoid common pitfalls. Here are six key problems that could derail even the most well-intentioned investors: 

Problem 1: Logic Fails

Markets don’t always behave logically, especially in the early stages of innovation. Consider TSLA vs. GM in 2013—the market favored Tesla despite its lack of earnings, while GM had a strong business foundation. I captured a fair amount of Tesla’s 2013 advance but missed out on its massive 2020 run-up. Why? In hindsight, it seems ridiculous, but at the time, many traders on my desk and online constantly pointed out Tesla’s much larger market cap compared to GM and even the entire auto industry despite much less revenue. That reasoning made me question the stock’s ability to climb higher. 

It was a seemingly logical argument, but the market often looks past common knowledge as it anticipates an uncertain future. The market frequently exaggerates potential, rewarding new movers (even without earnings) who eventually become the winners. This “exaggeration” phase is often misunderstood, causing many to underestimate new, disruptive players and miss out on enormous opportunities. 

Problem 2: Hindsight Bias

“Just buy and hold the best company” sounds simple—until you’re living in real time. Remember Blackberry? What about the hype around 3D printing? Hindsight makes success stories look obvious, but picking winners in the moment is far more challenging. Many promising technologies fade, while a few truly transformational ones emerge as dominant forces. 

Problem 3: No Systematic Process

Without a clear, systematic process, even the stocks you love can lead to disaster. Look at the COVID bull market: companies like PLTR, AFRM, UPST, PTON, and OPEN were massive winners—until they weren’t. Most of them crashed because investors failed to manage risk effectively. The lesson? Loving a stock isn’t enough; you need a disciplined strategy for buying, holding, and selling. 

We’ll dive deeper into this topic in an upcoming February workshop designed to help investors navigate these challenges.  Click HERE to know more about the workshop.

Problem 4: Blindness to Possibility

To understand what’s truly possible in an AI-driven world, look back at the 1990s. The internet supercharged tech stocks during the rollout, and many underestimated how transformative this new platform would become. AI is following a similar path, with exponential growth potential and unpredictable innovation on the horizon. Real-world applications like autonomous driving, robotics, and advanced data analysis are just scratching the surface. The future possibilities are endless, but only those with vision and preparation will thrive. 

Problem 5: Fear of Being Wrong

Innovation is inherently uncertain, and investing in it can feel equally risky. Many investors hesitate, unwilling to make mistakes in a world where failure is common. But the inability to take calculated risks—or manage them effectively—can lead to bigger failures. A balanced approach, blending optimism with discipline, is crucial for navigating these uncertainties. 

Problem 6: Misinterpreting Normal Advances

Some investors think we’re already in “climax tops” after a normal advance. This mindset often misses the bigger picture. By studying past tech leaders, like those from the 1990s internet revolution, you can see what’s possible and develop a playbook for spotting future opportunities. Understanding historical context is key to avoiding premature exits during multi-year bull markets. 

Why the AI Bull Market Is Real

As a pro trader, I put little faith in words—I follow actions and money. And the signs are undeniable: 

• BlackRock, Microsoft, and SoftBank have each announced $100 billion AI funds. 

• US large-cap tech companies are spending hundreds of billions of dollars on NVIDIA superchips. 

Those with the best knowledge are backing their beliefs with massive investments. Just like the internet revolutionized communication, AI is a platform that can revolutionize knowledge and action. 

Real-world applications like autonomous driving and robotics are already showing transformative potential. And that’s just the beginning—we can’t even imagine what’s yet to come. 

Internet Case Study: Lessons from the 1990s

The internet boom shows how innovation builds on itself. Each new company leveraged prior advancements, creating exponential growth. Yet, even during the decade-long internet bull market, leadership rotated frequently. Most leading stocks dominated for only a year or two before being replaced by new players. 

Key lessons: 

1. Most stocks didn’t remain leaders—even with the internet’s ongoing growth. 

1. A systematic process is essential. Many top stocks of the 90s crashed in 2000, causing massive losses for those who didn’t manage risk effectively. 

The tech boom of the 1990s also demonstrated how entirely new industries could emerge, building on prior innovations. For instance, companies like Amazon and eBay wouldn’t have succeeded without advancements in online payment systems like PayPal. Similarly, the rise of broadband technology enabled streaming platforms, setting the stage for giants like Netflix in the following decade. The interconnected nature of innovation means that each wave of technology lays the foundation for the next. 

Another important takeaway from the 1990s is how investor expectations often shift dramatically. During the early years of the internet, companies with little to no profits were given astronomical valuations because of their perceived future potential. While many of these companies eventually failed, a few—like Amazon and Cisco—went on to redefine their industries. However, even those winners faced sharp corrections during the dot-com crash, underlining the importance of timing and risk management. 

Investors today can draw parallels with the AI boom. Just as the internet brought about transformational changes in communication, commerce, and entertainment, AI has the potential to redefine industries such as healthcare, transportation, and education. Understanding the lifecycle of past innovations can provide a framework for navigating the uncertainties and opportunities ahead. 

Case Study 1: Oracle (ORCL)

Oracle (ORCL) is now a modern database behemoth, but its origins trace back to the early 1990s during the PC and internet revolution. While it’s easy to view Oracle as an undefeatable leader today, that wasn’t the case in its early years. At the time, IBM and Sybase were considered the major incumbents in the database market, with Microsoft beginning to make inroads with its SQL Server offering. Many investors underestimated Oracle’s ability to establish itself as a dominant player against these well-entrenched competitors. 

IBM was the undisputed leader in enterprise computing during this period, with its DB2 database serving as the gold standard for large-scale enterprise systems. Following “logic” by favoring IBM and dismissing Oracle as an overpriced upstart would have meant missing out on one of the greatest stock runs in history—a 73,000% gain over 14 years. For perspective, a $10,000 investment in Oracle would have grown to $7.3 million (Figure 1). 

In hindsight, Oracle’s rise seems obvious, but in real-time, it was anything but certain

The Phases of Oracle’s Staggering Advance

Despite its staggering gains, Oracle’s 73,000% move didn’t happen overnight. The advance occurred in three distinct phases, as shown in Figure 2, each lasting between 1.5 and 7 years and producing gains of 1,300% to 5,700%. 

Key Lessons from Oracle’s Bull Market 

Bull Markets and Innovation Rollouts Take Time 

• Genuine innovation-driven bull markets require patience. If your goal is to ride such an advance, focusing on short-term trading (like swing trading) will likely prevent you from staying with a stock long enough to capture its full potential. 

Massive Corrections Are Part of the Journey 

• Each of Oracle’s phases was followed by corrections of 57% to 84%. These drops would have shaken out most unprepared investors. If you bought during the hype due to FOMO, it’s almost certain you would have panicked and sold during one of these sharp declines, locking in a significant loss. 

Recovery Can Take Years—If It Happens at All 

• Following its final phase, Oracle’s stock required 17 years to recover its losses. For investors who bought lower-quality companies at their peaks, recovery never came. 

Even with its mind-blowing 73,000% gain, Oracle’s journey demonstrates that unprepared investors could easily have lost significant amounts of money despite the stock’s overall success. 

A Roadmap for What’s Possible

Oracle provides a clear vision of what’s possible in innovation-driven bull markets:

• How long they take to unfold.

• The nature of the gains and corrections.

• The numerous pitfalls along the way.

In future articles, we will dive deeper into Oracle’s advance, exploring the nuances of its journey and the lessons it offers for navigating similar opportunities in today’s markets.

Looking Ahead

The AI revolution has all the ingredients of a transformative bull market, but only those with a disciplined approach will thrive. Without a systematic process, you risk significant losses—or at the very least, you’ll fail to maximize the incredible profit potential.

In the coming weeks, we’ll review specific stocks to highlight the key problems described above, provide proper context, and share the most important lessons to take away. Stay tuned!