The world has been abuzz over artificial intelligence and the possible benefits and threats. These range from the practical, such as better tools for workers and ways for students to avoid writing papers, to including what it means to the impact on human civilization. In between, there are more mundane questions around the economy and markets, especially for technology-related sectors. Given the promises and excitement around AI, what can long-term investors do to maintain perspective and stay properly invested?
Tech stocks have benefited from falling interest rates and enthusiasm for AI
The two decades since the internet bubble have witnessed numerous hype cycles over new technologies. In just the past few years, these have included the metaverse, virtual reality, blockchain technology, self-driving cars, space exploration, and many more. Each of these has been accompanied by how they will transform society. The computer scientist Roy Amara famously said that people tend to overestimate the impact of technology in the short run and underestimate the effect in the long run. Although many new technologies do eventually play an important role in business and everyday life, investors can often get ahead of themselves sometimes.
When it comes to AI, this is partly because the term naturally ignites the imagination. However, today's AI and large language models are statistical and computer science techniques that can be more accurately described with the sober-sounding term "applied statistics." Just as with any new development, investors should try to maintain levelheaded views on the potential of this new technology. It is yet unknown how it may be able to benefit companies and individuals.
For example, while products such as OpenAI's ChatGPT, Google's Bard, and others have only recently burst onto the scene, the methods underlying these tools have been decades in the making. The latest cutting-edge AI models, known as transformers, were described by Google researchers in 2017. Previous state-of-the-art techniques, which have names such as RNNs and LSTMs, were actually invented in the 1980s and 1990s. The growth in computing power, especially the availability of graphics processing units (GPUs), and an abundance of natural language data (i.e., the internet), is what have allowed the field to leap from academic research to practical application.
From an economic perspective, the promise of new technology is a boost to productivity. Whether it's new machines, software, or just a better way of doing things, technology is what allows us to accomplish more with less. After all, the simplest way to think about the economy is that growth occurs when there are more workers (labor), more machines (capital), or improved technology (e.g., better trained workers and/or better machines). Productivity, or the ability for the same number of workers to produce more, is what improves quality of life generation after generation.
Productivity is the key to sustainable economic growth
New technologies often lead to questions around "creative destruction," a term coined by the economist Joseph Schumpeter. This is especially true when they disrupt established methods, ideas, and businesses, potentially creating existing skills to become outdated and a loss of jobs. But, at the same time, technological advances has created new industries, benefiting workers with the proper skills and training, as well as the consumers of these new products and services. Whether this progress is positive or negative is debated each time a transformational technology disrupts the status quo.
Regardless of one's views on AI and technology, it's undeniable that productivity growth has slowed in recent decades. The average year-over-year productivity growth rate since 1948 is 2.1%, but only 1.5% over the last few years. Prior to the pandemic, one of the biggest concerns cited by many economists was known as "secular stagnation," or the idea that the economy would grow at a slow pace due to poor demographic trends, aging infrastructure, and slowing productivity. This isn't just a concern in the U.S. - many parts of the world, including Japan and throughout Europe, have aging populations and poor productivity.
While the differences in growth rates may seem small, they have big implications when compounded over years and decades. If the economy grows at a steady 3% annual rate, it can double every 23 years. In contrast, a growth rate of 2% requires 35 years while 1% growth takes nearly 70 years. Small differences in growth can have huge differences on economic outcomes. So, regardless of whether the hype around AI pans out or not, technology that can boost long run productivity is important for maintaining the quality-of-life improvements that we have grown to expect.
Market returns have been concentrated in tech-related sectors this year
From a market perspective, enthusiasm for AI has boosted tech-related sectors and benefited diversified investors. While the S&P 500 has gained 12% this year to date, the information technology and communication sectors have climbed 35% and 33%, respectively. These returns have more than offset the poor performances of sectors such as energy and financials, and have overshadowed problems in the banking and commercial real estate industries.
While there is a debate around whether this is good or bad for markets, the reality is that this is not something investors can control. What they can control is whether they are diversified across all of these sectors. Those that have appropriate portfolio exposures have benefited from these trends, just as they benefited from strong energy returns last year, while also staying prudent as valuations rise to higher and higher levels. This is further evidence that it is difficult to predict what will outperform in any given year, and thus it remains important to be properly diversified.
The bottom line? Investors should maintain a level head around new technologies such as artificial intelligence. Growth and strong sector returns are a reason for investors to stay diversified and focused on the long run.