Artificial Intelligence: A Bundle of Possibilities
In recent years, very few developments have captured investors' imagination and curiosity as much as the emergence of generative artificial intelligence (AI). Although its origins trace back to the 1950s, the release of ChatGPT—a consumer-focused AI chatbot and virtual assistant—in late 2022 marked a turning point that sparked a global frenzy around all things AI.
Thanks to its public accessibility and intuitive interface, ChatGPT gained over 100 million active users just two months after launching, as shown in Figure 1. The tool's meteoric rise into one of the fastest-growing applications in history evidences the magnitude of demand for AI technologies and excitement around its transformative potential.
Figure 1: Months to Reach 100 Million Global Users
Image
Source: Bloomberg. As of January 2024.
In simple terms, generative AI uses various technologies to simulate human intelligence and problem-solving capabilities. AI can "learn" from past data to autonomously perform complex tasks like writing software code from scratch and providing accurate answers to user queries.1 In fact, AI has already surpassed human performance in several areas, including image classification, visual reasoning, and English understanding, according to research from Stanford University.2
Despite its infancy, different studies have proven that generative AI's ability to model intelligent behaviors can boost business productivity and enhance business performance.3 According to PwC, the sectors most exposed to AI—such as financial services, information technology, and professional services—are seeing productivity gains five times larger than those less exposed to AI.4 Across the technology landscape, businesses have entered an "AI arms race," making substantial investments to build generative AI capabilities to capture a slice of what Bloomberg estimates will become a $1.4 trillion market by 2032 (Figure 2).5
Figure 2: AI Market Growth Forecast
Image
Source: Bloomberg. Most recent estimates were published in June 2024.
The AI Rally: Is There a Bubble Brewing Underneath?
So far this year, ever-increasing momentum around AI propelled global equity indexes to record highs, with mega-cap tech leading the rally. According to Bloomberg, the seven biggest U.S. companies—commonly known as the "Magnificent 7"— saw their combined weighting in the S&P 500 rise to a record 30% as some investors believe they stand at the center of AI adoption and deployment given their vast scale, financial resources, and talent.6 Nevertheless, the rapid pace of the rally has left other investors concerned about frothy valuations drawing similarities with the dot-com boom of the 1990s, which propelled the NASDAQ index—a barometer of the U.S. tech sector—800% higher in just five years, only for it to plunge 78% after the Internet bubble burst in 2000, taking more than 12 years to recover fully.7
Though our research indicates that valuations appear stretched in some areas of the market, we believe today's investment landscape vastly differs from the one seen during the dot-com bubble.8 Unlike the unprofitable tech companies of the 1990s, the latest U.S. earnings season results showed that booming demand for AI adoption has resulted in revenue growth for the companies at the epicenter of AI enablement. Meanwhile, instead of rising along with early leaders, money-losing tech companies have seen their share prices sink this year as investors become increasingly more discerning.9
Furthermore, stock valuations are much lower than during the dot-com bubble's peak. Currently, the S&P 500 trades more than five times earnings beneath its 2000 peak cap-weighed P/E, and the largest tech companies trade at nearly half the P/E multiples from the late 1990s tech bubble10. When equities peaked in March 2000, the top 7 ranked by market cap in the S&P 500 traded at 64 times P/E, and the Four Horsem*n11 traded at more than 80 times trailing earnings. Today, as seen in Figure 3, the five largest S&P 500 companies trade at a P/E multiple of 36 times, less than half the Four Horsem*n's top P/E.12
Figure 3: Trailing Twelve Months P/E Ratios: 2000 Valuations vs. Today
Image
Source: Bloomberg. As of May 28, 2024.
Is It Too Early or Too Late to Invest in AI?
The rapid surge in AI-related stocks has left some market participants questioning whether it's too late to invest in the sector. Despite this year's positive performance, our research indicates AI is still in its early stages, and much uncertainty lingers around issues like governance, ethics, data security and accuracy. As Figure 4 shows, similar to other digital solutions, most of AI's potential remains untapped and not fully understood. Yet, it is essential to remember that a promising narrative does not always necessarily translate into a great investment. Therefore, we believe investors should exercise patience and a long-term mindset when seeking opportunities across the AI innovation cycle.
Figure 4: Untapped Potential of Technology Solutions
Image
Source: Accenture. Study published June 2024.
While many companies have made significant investments in AI, we believe not all will be able to turn expenditures into profits. As we have seen in the past, widespread adoption of technological advances—such as the internet—usually takes time to develop, and market leaders change often and swiftly. For example, according to data compiled by Bloomberg, of the ten best performers in the NASDAQ the year leading up to the index's 2000 peak, only two still exist as standalone companies today.13 Similarly, the companies at the helm of the AI revolution may look different five years from now, with incumbents falling behind competitors or even new companies becoming market leaders.
Investor Takeaways: Look Beyond Today's Winners
Looking forward, we believe AI will pave the way for many compelling investment opportunities over the next decade. However, given that we are still in the early days of AI, we think it is important to resist the fear of missing out driven by the allure of quick gains. Rather than aiming to be the first to hop on a new trend or hot company, we believe that taking our time to truly understand a company's prospects before we invest in it is critical in assessing the sustainability of its competitive advantages.
Even for those businesses leading the AI rally, certain risks loom. For example, NVIDIA14 —which manufactures the chips that power AI systems—reminded investors last month that stocks don't go up forever. The company's shares experienced their worst selloff in four years amid concerns about its ability to sustain its fast pace of revenue growth in the years to come.15 According to our research, the company's valuation could prove expensive if there is a meaningful digestion period following the purchases from its large customers in the past two years.
Also, we believe that investors focusing on just a few U.S. tech companies may be overlooking AI opportunities in other regions. With AI gaining momentum worldwide, domestic champions are rising across Europe and Asia, where valuations are more attractive. For many economies experiencing labor shortages and low productivity growth, AI represents an opportunity for economic development and the creation of new industries entirely. Hence, we suggest investors apply a global lens when exploring AI opportunities, favoring high-quality businesses with proven competitive advantages led by management teams prioritizing long-term performance.16
Despite our constructive outlook, we believe that AI's evolution and growth won't be linear but bumpy as new solutions emerge and the divide grows between winners and losers. With over 30% of the S&P 500's value concentrated in the "Magnificent 7," investors should know that index exposure in today's market does not represent diversification. For passive investors, a sudden shift in expectations of the "Magnificent 7" could result in a sharp correction, particularly when some companies are trading at elevated levels relative to the broader market. This is why we believe employing an active approach in today's environment is essential— looking at each company individually and understanding their unique circ*mstances and prospects.
Download the whitepaper
