Throughout history, each generation has encountered technological advances that have reshaped the way that people live and work. Some of us have experienced several of these periods of profound innovation within our own lifetimes. While each technological breakthrough is always unique, the questions that arise are usually remarkably familiar: Will machines replace workers? Will productivity eliminate jobs? And how should investors position themselves for a world that may look very different a decade beyond? 

In 1966, long before the personal computer or the internet, President Lyndon Johnson established the National Commission on Technology, Automation, and Economic Progress to study whether automation would lead to widespread unemployment. One intriguing passage from that commission’s report is particularly striking because it sounds remarkably similar to concerns being expressed today: 

“According to one extreme view, the world—or at least the United States—is on the verge of a glut of productivity sufficient to make our economic institutions and the notion of gainful employment obsolete.” 

At that time, almost one-third of the U.S. workforce was employed in manufacturing, so fears that machines would replace workers were more than just theoretical—they affected the livelihoods of millions of Americans. 

In retrospect, what is perhaps most interesting is that many of the occupations at the center of today’s AI debate didn’t even exist in 1966. Software engineers, web developers, cybersecurity specialists, cloud architects, and data scientists would not emerge as major professions until decades later. While automation undoubtedly displaced some jobs, it also created entirely new industries and careers that were difficult—if not impossible—to foresee. 

In other words, history often teaches us that we are generally much better at predicting which jobs technology will disrupt rather than which industries, companies, and professions it will ultimately create. That doesn’t mean that the concerns surrounding AI are misplaced, but rather that history encourages a degree of humility when making long-term predictions about the winners and losers of technological change. 

While AI will certainly change the way we work, it also has the potential to expand who can create new products, services, and businesses. Even after decades of personal computers, smartphones, and the internet, most Americans still don’t know how to write software code. AI is beginning to lower that barrier. Someone with an idea—but little or no programming experience—can now build a website, develop an application, automate a workflow, or create digital content using tools that simply didn’t exist a few years ago. As a current example of this, we need to look no further than YouTube. Few would have predicted that a video-sharing website would give rise to millions of creators, educators, entertainers, and entrepreneurs. AI may prove to be another example of a technology that enables entirely new forms of work and creativity, but only time will tell whether its long-term impact follows the same pattern as previous technological revolutions. 

When it comes to potential investing opportunities, periods of seismic technological innovation have often led investors to become overly optimistic about the pace and magnitude of ongoing future change. While AI has undoubtedly fueled enthusiasm in the equity markets, it is important to distinguish between excitement and fundamentals. Unlike the late 1990s, the strength in global equity markets over the past three years has been meaningfully supported by robust corporate earnings rather than expanding valuations alone. In fact, this year, the valuation of the U.S. stock market has declined modestly as earnings growth has outpaced share price appreciation. 

That said, not all of today’s earnings are likely to prove equally durable. In certain areas of the market—most notably memory chip manufacturers—there is growing concern that current profits reflect unusually favorable supply and demand dynamics that may not persist. As capacity expands and the market normalizes, earnings in these more cyclical businesses could come under pressure, a pattern that has repeated itself many times over previous semiconductor cycles. 

As with most periods of technological change, the benefits of AI are unlikely to be distributed evenly across the market. History suggests that while some companies benefit from the initial wave of investment surrounding a new technology, the most durable winners are often those that successfully incorporate the technology into their products, services, and business models over many years. For investors, the challenge is not simply determining whether AI will be transformative, but identifying which businesses are building sustainable competitive advantages rather than benefiting from a temporary surge in demand. Furthermore, the competitive landscape continues to evolve. There is growing evidence that countries beyond the United States, particularly China, are making significant progress in developing competitive AI models and capabilities. For investors, maintaining a globally diversified portfolio provides exposure to a broader set of opportunities while reducing the risk of relying too heavily on any single company, sector, or geographic area as the AI landscape continues to develop. 

The future of AI will almost certainly produce both winners and losers, just as every other major technological revolution has in the past. No commission in 1966 could have imagined or anticipated software engineers, cybersecurity specialists, cloud architects, or YouTube creators any more than we can confidently predict the professions and industries that AI may enable decades from now. For investors, that uncertainty is a reminder to remain humble, maintain a disciplined and diversified approach, and recognize that many of tomorrow’s most important opportunities, and even challenges, may not be as obvious as they currently seem.