The AI Revolution: How AI is Showing Up in Markets and Portfolios (Part 2)

In our last blog, we broke down what AI is, its significant impact on markets today, and how it’s evolving. We also emphasized the importance of cutting through short-term hype and focusing instead on long-term, value-driven investment opportunities.

In this follow-up, we’re taking a closer look at the industries and sectors that could benefit most from AI, both directly and indirectly. We’ll also explore how AI trends are manifesting in both the public and private markets and what it means for investors. This edition covers:

• The Obvious AI Plays in Tech
• Beyond the Tech Industry
• AI in Public Markets
• AI in Private Markets

The Obvious AI Plays in Tech

The Technology sector has been the key engine of U.S. stock market growth over the past decade, and AI represents a new growth opportunity for the sector. For investors looking to gain exposure to the emerging AI ecosystem, there are a few obvious areas to start.

Semiconductors: The Heart of AI

Semiconductors, often called “chips”, are the most important technology powering AI because they provide the speed and processing power needed to handle enormous volumes of data. One key example is the Graphics Processing Unit (GPU), which excels at managing the many rapid-fire decisions AI systems make.

When prompted to explain how it prepares a response to a simple finance question like “What’s the outlook for interest rates?”, ChatGPT explained:

“I don’t generate the full answer all at once. I build it piece by piece, choosing each word based on everything you’ve asked and what I’ve already said. Even for a short response, that means making around 150 decisions — and behind each one are billions of fast calculations happening in the background.”

That’s why AI models like ChatGPT rely on GPUs. These chips are designed to perform massive amounts of math at lightning speed, enabling AI to analyze complex financial questions and deliver clear, real-time responses. Other chips, like Tensor Processing Units (TPUs), go even further and are built specifically to run AI tasks with maximum efficiency. These semiconductors are what make today’s advanced AI capabilities possible.

Hardware and Equipment: The Physical Body

In addition to chips, AI also needs the right hardware to run smoothly. That includes servers, storage drives, and networking equipment, the infrastructure that allows AI systems to process information and communicate with each other. This machinery can be found stored in data centers, which are large buildings that manage and house the hardware.

Software and Services: The Intelligence Layer

If hardware is the body of AI, software is the brain. Software includes code, systems, and platforms that developers use to create and train AI programs. It also includes the business tools that allow companies to integrate AI into their everyday operations, such as customer service or supply chain management.

Beyond Tech: The Expanding AI Ecosystem

While tech companies are often at the forefront of the AI conversation, its impact extends far beyond the tech industry. As adoption accelerates, sectors like Utilities and Industrials are becoming essential contributors—quietly building the foundation that keeps AI moving forward.

Utilities: The Energy Behind AI

AI programs use troves of electricity. Every time you interact with a chatbot or generate an AI image, it requires significantly more power than a typical internet search. For example, while a single Google search uses about 0.3 watt-hours, a single ChatGPT query requires closer to 2.9 watt-hours¹. With nearly 9 billion internet searches conducted each day, shifting all of them to AI-powered queries could demand nearly 10 terawatt-hours (TWh) of additional electricity each year. That’s roughly equivalent to the annual energy consumption of over 900,000 U.S. homes, based on 2022 figures.²

That’s where utilities come in. These companies provide the electricity that keeps AI’s lights on, literally. Many are already partnering with major tech firms to scale up the infrastructure needed to meet rising demand.  As AI adoption continues to grow, utility providers stand to benefit from the long-term increase in energy use.

Industrials: Building the Infrastructure for AI

While utilities supply the power, industrial companies provide the infrastructure that allows AI to grow and operate. These firms design and build the data centers that house the servers, cooling systems, and electrical components needed to support AI at scale. Since 2022, capital spending by hyperscalers, or the largest tech companies, has more than tripled. By the end of 2026, nearly 800 billion dollars is expected to be invested in capital projects, much of which is aimed at expanding data center capacity to meet rising AI demand. Beyond physical infrastructure, industrials are also helping scale technologies like industrial robotics, humanoid robots, and full self-driving systems. These innovations are becoming increasingly feasible as generative AI improves the ability to process complex tasks, adapt to real-world environments, and learn from vast amounts of data.

This level of investment shows how essential physical infrastructure has become to AI’s future. Data centers are more than storage spaces; as AI models grow more complex and real-time applications expand, the need for energy-efficient, high-capacity facilities will continue to increase.

AI in Public Equity Markets

AI has quickly become one of the most powerful forces shaping U.S. stock market performance. The top 10 companies in the S&P 500, most of them in the tech sector, now make up more than one-third of the entire index. These firms have led the charge on AI investment, but what makes them especially notable is how interconnected they are across the AI ecosystem.

Take NVIDIA, for example. Much of its recent revenue growth has come from just a few major customers — the same hyperscalers building the AI infrastructure we discussed earlier. That level of concentration can amplify risk. If those hyperscalers slow their AI-related spending or shift direction, the ripple effects could stretch across the broader market. Still, there’s a strong case for why so much capital continues to flow into these companies. They aren’t just chasing growth; they’re using AI to build long-term efficiency.

The idea is simple: higher productivity, lower labor costs, and stronger profit margins. We’re already seeing signs of this play out. Despite their massive scale, employment growth across the “Magnificent 7” has been minimal, with headcount growth sitting at just 2% in 2024. These firms are generating more revenue with fewer new hires, a sign that AI may be helping them do more with less.

AI has the potential to contribute to a substantial increase in productivity, which can directly contribute to improved profit margins for the companies that best harness it. For investors, that means potentially stronger returns from companies that can scale without adding significant cost.

That said, investing in this theme isn’t just about chasing the biggest names. Market leadership changes, innovation can be unpredictable, and even powerful trends like AI come with real risks. Most investors may not realize that they already have meaningful AI exposure through their core equity holdings. As we discussed, the top 10 companies now make up roughly 35% of the S&P 500 with the majority being tech giants. As a result, investors with broad index exposure are already meaningfully exposed to AI and Tech, so adding individual stocks or thematic funds on top of that can further exacerbate concentration risks. Looking forward, to the extent that these hyperscalers grow faster than the broader market, their weight in the index will rise, and investors’ exposure will increase naturally with no deliberate action needed. It is natural to want to chase the latest investment themes, but it’s important to understand what exposures may already be embedded in portfolios and think holistically about maintaining proper balance over the long-term.

AI in Private Equity Markets

Some investors may be better served by looking toward private markets as a way to access the upside potential associated with AI. Private markets are often where tomorrow’s innovation takes place. They provide access to the early stages of the AI ecosystem, where emerging technologies are built and refined long before they reach public markets. As these companies grow, some eventually go public, but private investors can participate earlier in the journey, which is where growth potential can be greatest.

The private market has expanded significantly over time and now exceeds the public market in terms of the number of companies. Within it, tech and AI-focused businesses make up a meaningful and expanding portion. While private investments are not a fit for everyone due to their complexity, lack of liquidity, and higher risk profile, they can be a compelling option for investors with the right risk tolerance who may be seeking more targeted exposure to specific technologies.

Looking Ahead

The excitement surrounding the AI ecosystem is immense, and it’s easy to get caught up in the hype. But it’s important to remember that we are still in the early stages, and we encourage investors to take a step back and consider the full picture. The investment opportunities related to AI span multiple sectors and extend beyond the public markets alone.

In our next post, we’ll zoom out to explore the broader economic influence of AI, looking at its potential effects on productivity, labor markets, and inflation. As investors think through the ripple effects of this technology, understanding its macro implications will be just as important as tracking its role in equity markets.

Sources:

[1] IEA (2024), Electricity 2024, IEA, Paris.

[2] U.S. Energy Information Administration (2024), “How much electricity does an American home use?”, EIA, Washington, DC.

This material should not be construed as a recommendation, offer to sell, or solicitation of an offer to buy a particular security or investment strategy. The information provided is for informational purposes only and should not be relied upon for accounting, legal, or tax advice. While the information is deemed reliable, Wealthspire Advisors cannot guarantee its accuracy, completeness, or suitability for any purpose, and makes no warranties with regard to the results to be obtained from its use.

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