Artificial Intelligence: Participating Without Overconcentrating
Technology stocks took a brief backseat during the first quarter, with many high-profile names pulling back from their all-time highs amid concerns about valuations and the broader economy. However, since the quarter ended, technology and AI-related stocks have once again emerged as the dominant drivers of market returns as investors have refocused on the long-term potential of artificial intelligence.
Companies across the economy are now investing heavily in AI. Technology giants are spending hundreds of billions of dollars on semiconductors, data centers, and cloud infrastructure, while businesses in industries ranging from healthcare to logistics are beginning to incorporate AI into their everyday operations. In fact, Amazon, Alphabet, Meta, Microsoft, and Oracle are expected to collectively invest roughly $650 billion in data centers and related infrastructure this year alone, highlighting the unprecedented scale of the buildout underway. As a result, the debate is no longer whether AI will influence the economy, but which companies will ultimately benefit and whether current market prices already reflect those expectations. This is one reason diversification remains especially important as investors evaluate AI-related opportunities.
The AI Boom Is Also an Infrastructure Boom
While much of the attention has focused on software developers and technology platforms, one of the more underappreciated aspects of AI is that it is also a massive infrastructure story. Training and operating advanced AI systems requires: semiconductors, data centers, electricity and cooling systems, networking equipment, and cloud infrastructure.
This has created what increasingly resembles a modern infrastructure cycle. Major technology companies are dramatically increasing capital expenditures to build the systems needed to support AI demand. Some Wall Street analysts estimate that hyperscaler AI-related capital spending could eventually approach or exceed $1 trillion annually.
Importantly, the spending does not appear to be entirely speculative. Recent earnings commentary from large cloud providers suggests customer demand for AI capacity remains extremely strong. Some firms are reporting growing backlogs of future contracted business tied to AI and cloud computing infrastructure.
This helps explain why AI’s impact is extending far beyond technology stocks alone. Utilities, industrial companies, power infrastructure providers, and data center-related businesses may also benefit from rising AI demand. In fact, BlackRock recently highlighted the growing importance of what it calls “new economy infrastructure” — physical assets such as energy systems, industrial facilities, and infrastructure that are difficult to digitize but may benefit from increased AI-driven demand regardless of which software platforms ultimately emerge as long-term winners.
AI Is Already Showing Signs of Increasing Productivity
While investors have focused heavily on the companies building AI infrastructure, the ultimate value of the technology will likely depend on whether it improves productivity across the broader economy. Early evidence suggests that this process is already underway.
Artificial intelligence is becoming increasingly integrated into everyday workflows and is proving particularly effective at tasks such as:
- Drafting emails
- Summarizing documents
- Assisting with coding
- Automating customer service interactions
- Analyzing medical data
- Optimizing logistics and supply chains
Businesses are beginning to report measurable efficiency gains from these capabilities. A recent survey from Capital Group found that 46% of employees are already saving between 11% and 20% of their time through the use of AI. Some technology leaders believe the impact could become even more significant. As Meta CEO Mark Zuckerberg recently noted, “We’re seeing more and more examples where one or two people are building something in a week that would have previously taken dozens of people months.”
Beyond office productivity, AI’s potential applications extend far beyond knowledge work. Manufacturers are increasingly using AI-powered robots to automate repetitive tasks and improve production efficiency. Autonomous vehicles, drones, and emerging air taxi technologies rely on AI to process massive amounts of data and make real-time decisions. While many of these applications are still in their early stages, they illustrate how AI’s impact may extend well beyond software and potentially reshape industries ranging from transportation and logistics to manufacturing and aerospace.
While the long-term implications remain uncertain, examples such as these suggest that AI has the potential to increase productivity by allowing employees to accomplish more with the same amount of time and resources. As more companies implement AI initiatives and workers become increasingly comfortable with the technology, these benefits could continue to expand across the economy.
At the same time, AI still has meaningful limitations. While AI systems are often impressive at summarization, pattern recognition, and repetitive tasks, they continue to struggle with judgment, context, and reasoning in more complex situations. Most professionals who use AI regularly can likely point to examples where the technology produced confident but inaccurate answers, highlighting the continued importance of human oversight.
AI may prove extremely useful as a productivity tool without necessarily becoming a perfect replacement for human decision-making. In many industries, the more likely outcome may be augmentation rather than full automation, with AI helping employees work more efficiently rather than replacing them outright. If that proves to be the case, the economic impact could still be substantial even if the technology falls short of some of the more ambitious predictions currently being made.
You May Already Have Significant AI Exposure
Artificial intelligence has already had a significant impact on financial markets, particularly within large-cap U.S. technology stocks. Companies involved in AI infrastructure, semiconductors, cloud computing, and software development have driven a substantial portion of recent market gains, contributing to both elevated valuations and increased market concentration.
As shown in the chart below, the ten largest companies in the S&P 500 represented nearly 38% of the index’s total value as of March 31. This figure has roughly doubled since 2016, largely due to the rapid growth of the technology giants often referred to as “hyperscalers.” Except for Berkshire Hathaway, each of these top ten holdings has significant exposure to the AI ecosystem through either direct investment in AI infrastructure or the development of AI-enabled products and services.
As a result, many investors already have substantial exposure to artificial intelligence through broad market index funds such as the S&P 500. Investors in large-cap growth strategies or technology-focused indexes such as the Nasdaq may have even greater exposure. Consequently, some investors may already be making a larger bet on the future of artificial intelligence than they realize.
Investing in the AI Theme
Investors interested in artificial intelligence have no shortage of investment options. AI-focused ETFs and thematic strategies can provide targeted exposure to companies involved in semiconductors, cloud computing, software platforms, and other areas of the AI ecosystem.
For some investors, allocating a modest portion of a portfolio to these strategies may be appropriate. However, it is important to recognize that many thematic funds are highly concentrated and may experience significant volatility. Investors should size these positions at a level they are comfortable holding through potentially large swings in performance.
Even if artificial intelligence ultimately meets its lofty expectations, investment returns will depend not only on business growth, but also on the price investors pay for that growth. History suggests that transformative technologies often experience periods of both excitement and disappointment. During past innovation cycles, many early leaders experienced substantial drawdowns even when the underlying technology ultimately succeeded. As a result, AI-focused strategies may be particularly susceptible to boom-and-bust cycles as investor expectations evolve.
Diversification Beyond the Obvious Winners
One of the challenges with investing in AI is that many investors already have significant exposure through broad market index funds. The largest technology companies now represent a substantial portion of major U.S. indexes, meaning that additional AI investments can sometimes increase concentration rather than diversification.
Fortunately, the AI opportunity extends far beyond a handful of U.S. technology companies. As shown in the chart below, several emerging market companies occupy critical positions within the AI supply chain while trading at significantly lower valuations than many of their U.S. counterparts. These businesses, which Capital Group refers to as the “Emergent Seven”, include semiconductor manufacturers, memory chip producers, networking companies, and electronics suppliers that help power the AI ecosystem.
This highlights one way investors can gain exposure to AI while maintaining a more diversified portfolio. In some cases, these companies may provide exposure to critical AI infrastructure at valuations that are significantly lower than many of their U.S. counterparts. Rather than concentrating exclusively in a small group of U.S. technology stocks, investors may benefit from owning a broader set of companies and regions that stand to benefit from rising AI investment and adoption.
AI is also creating opportunities outside of technology. Utilities, industrial companies, power generation providers, infrastructure businesses, and data center operators may all benefit from the enormous capital spending required to support AI growth. In many cases, these businesses may benefit regardless of which software platforms emerge as the long-term winners.
Ultimately, the goal is not necessarily to avoid AI. Rather, it may be to participate in the opportunity while maintaining a diversified portfolio and avoiding excessive dependence on any single company, sector, or investment theme.
Final Thoughts
Artificial intelligence may become one of the defining economic and investment themes of the next decade. Its influence is already reshaping markets, corporate spending, and the broader economy as businesses invest heavily in infrastructure and increasingly incorporate AI into their operations.
At the same time, investing in AI is not as simple as identifying a single winning company or technology. The benefits may extend well beyond software developers and semiconductor manufacturers to include utilities, industrial companies, data center operators, and businesses that successfully use AI to improve productivity. History suggests that the ultimate beneficiaries of technological change are often difficult to identify in advance, making diversification especially important.
For investors, the challenge is not deciding whether AI will matter, but how to participate without becoming overly dependent on a single company, sector, or investment theme. While AI may become an incredibly powerful tool, investing still requires judgment, discipline, and thoughtful analysis. Recent market volatility, including the sharp technology selloff on June 5, serves as a reminder that even the most promising long-term themes rarely move in a straight line. As with past technological revolutions, the long-term winners may not be those who chase the fastest-growing trend, but those who build resilient portfolios capable of adapting across a range of possible outcomes.
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