Artificial intelligence (AI) is quickly becoming one of the most important drivers of future economic growth, and investors are taking notice. For those building long-term portfolios, the question isn’t just whether AI will matter, but how to gain exposure in a diversified, disciplined way.
In simple terms, AI refers to technology that helps machines learn, analyze data and make decisions more efficiently. It’s trending toward becoming the next quantum leap in global economic productivity.
The conversation has gone from whether AI was real, to whether it would matter economically, to just how definitively it will impact the entire economic spectrum. With each passing day — literally — it’s proving to be the most significant technological revolution of our time. This is creating compelling investment opportunities.
The rise of AI could add $19.9 trillion to the global economy by 2030.1
Why investors are paying attention
Interest in AI has surged as companies across many industries begin using it to improve efficiency, lower costs and drive growth. That interest has accelerated exponentially as “generative” AI — which has the ability to create new content such as text, images, videos or code based on a user’s instructions — entered the mainstream and emphasized the technology’s ability to reshape industries and economic growth.
But for many investors, it’s not clear how to translate this trend into a long-term investment strategy.
The question is no longer simply, “Which company builds the best AI model?” The more complex question is which businesses can successfully utilize AI to improve their processes, products and improve margins.
AI is increasing the demand for semiconductors, data centers, digital infrastructure and electricity generation, each with their own investment opportunities, and investors are starting to take note of:
- The potential for stronger earnings growth as companies use AI to reduce costs
- How AI adoption could expand profit margins and productivity
- Companies that have positioned themselves as early AI leaders with competitive advantages over peers
- Long-term AI investment trends that might create opportunities across both direct beneficiaries and secondary sectors (e.g., healthcare, industrials and agriculture)
AI builders vs. AI users
It’s helpful to think about AI investing in two broad groups: builders and users. While much of the early investment focus has centered on the large technology companies that are formulating AI (builders), its influence is expected to extend well outside of that sector (users).
Such “AI users” include:
- Healthcare – diagnostics, drug discovery, patient monitoring and administrative automation
- Industrials – robotics, predictive maintenance and supply chain optimization
- Energy & Utilities – rising electricity demand from data centers and grid modernization needs
- Consumer & Retail – personalization, inventory management and logistics efficiency
- Transportation & Logistics – route optimization, warehouse automation and fleet management
- Real Estate & Infrastructure – increased demand for data centers, digital infrastructure and power systems
- Manufacturing – automation, quality control and operational efficiency improvements
- Agriculture – precision farming, crop monitoring and resource optimization
- Education – personalized learning platforms and administrative automation
Users of AI represent a broader opportunity set, and it would serve investors well to stay aware of adjacent beneficiaries like these across the economy. (Example: The internet didn’t just benefit software companies, it also reshaped telecommunications infrastructure, logistics, retail, advertising and commercial real estate.)
Two ways to get in
Investors can access AI opportunities through both public and private markets, each offering unique ways to participate in the growth of its influence. Here’s a table that breaks down the differences.
| Public Markets | Private Markets | |
|---|---|---|
| Where they're traded | On public exchanges, such as the NYSE and Nasdaq | Not traded on public exchanges |
| Examples | Stocks, bonds, ETFs and public companies such as Apple, Microsoft and Nvidia | Private equity, venture capital, private credit and infrastructure |
| Access to your money | Investments can typically be bought or sold daily | Investments are generally held for longer periods and may be harder to sell quickly |
| Available information | Pricing and company information are publicly available | Less information is publicly available |
| How they may fit in a portfolio | Can provide liquidity and broad market exposure | Can provide diversification and access to additional opportunities |
Currently, public markets offer the most visible exposure to AI investing through large technology and semiconductor companies. This explains why “The Magnificent 7” (Apple, Microsoft, Nvidia, Amazon, Alphabet, Meta and Tesla) have accounted for roughly one-third of the S&P 500’s total market capitalization in recent years as investor enthusiasm surrounding
AI has skyrocketed.
Again, it’s important for investors to consider the bigger picture that extends beyond technology stocks alone, as AI is increasingly influencing industries across the broader global economy.
Rather than trying to pick a few winning companies, many investors are looking for ways to gain broad exposure to the AI trend across industries.
The case for thematic ETFs
If there’s one lesson the dot-com bubble of the late 90s taught us, it’s that transformative technologies can create unique opportunities, but early market leaders don’t always become long-term winners. And putting all your eggs in one basket might not be the most prudent investment approach.
For investors interested in AI but wary of betting on a single company or trend, thematic ETFs can provide disciplined, diversified exposure across the broader AI ecosystem.
Thematic ETFs allow investors to gain exposure to a wide range of companies involved in AI — from those building the technology to those using it to improve their businesses — within a single investment.
Sectors a thematic ETF might cover:
- Semiconductors and chip manufacturers
- Cloud computing and software providers
- Data centers and digital infrastructure
- Energy and power systems supporting AI demand
- Robotics and industrial automation
Diversification matters. Big Tech leadership can shift quickly, and rapid innovation, changing regulations and evolving trends can quickly reshape the investment landscape as new business models emerge.
A thematic ETF approach also helps investors participate in multiple layers of the AI ecosystem — not just the companies developing AI models, but the previously mentioned “users” that could realize growth from increased enterprise adoption.
Potential investment benefits include:
- Reduced single-stock risk
- Broad exposure across sectors and industries
- Lower costs through passive or rules-based strategies
- Daily liquidity and transparency
For long-term investors, thematic ETFs could offer an easy-to-implement way to participate in AI’s growth potential without trying to time the market or predict winners and losers.
Managing the hype cycle
We believe a long-term perspective and the support of a global, well-resourced equity research team positions investors best when looking to add AI’s potential to their portfolios.
With all the enthusiasm surrounding AI, we like to remind investors that periods of technological transformation like this often come with outsized expectations and increased market volatility.
We closely monitor several risk factors as part of our broader investment process, including:
- Elevated valuations in parts of the technology/AI sector
- Increased market concentration among a small number of companies (Magnificent 7)
- New competitors and emerging technologies that could disrupt today’s industry leaders
- Regulatory and data privacy concerns
Diversification across sectors and asset classes remains important for a healthy long-term portfolio.
The long view
AI may still be in the early stages of adoption, but its broader economic impact will likely be felt for years to come. Rather than viewing it as a narrow technology trade, investors might be better served by approaching it as a long-term economic shift with implications across industries and asset classes.
AI’s influence will soon start to be felt far beyond Silicon Valley, reshaping how businesses operate, how infrastructure is built and how capital is invested across the global economy. As with any bullish technological boom, investors focused on long-term fundamentals will be best positioned to navigate periods of both opportunity and volatility.
Taking a diversified, long-term approach can help investors participate in AI’s growth potential while managing the risks that come with rapidly evolving technologies.
