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Research Says: Biggest Gains From AI Won’t Be AI Stocks

A fresh look at AI investing shows the most dramatic gains might come from broad market value and international stocks rather than the marquee AI players. This piece breaks down the logic and points to two ETFs worth a closer look.

AI's Biggest Gains Might Come From Outside the AI Giants

When the AI boom grabbed headlines, many investors raced toward the obvious winners: the giant tech companies building the tools, chips, and cloud services that power AI. The lore goes that if you own the machines that dream up AI, you’ll ride the wave to outsized gains. But what if the story is more nuanced? What if the most meaningful benefits from AI’s productivity breakthroughs don’t show up as bulletproof returns from a few megacap stocks, but as broader market improvements that lift many kinds of companies?

That question sits at the heart of a growing line of research and market commentary that challenges the dominant narrative. In particular, fresh analyses suggest that the biggest gains from AI could emerge in places investors often overlook: value stocks in the United States and developed international markets. The reasoning is straightforward: AI-enabled productivity and cost efficiency can lift profits across sectors, and the greatest leverage often comes from businesses with strong pricing power, disciplined capital allocation, and less expensive valuations. In short, the AI boost may show up as a multiplier for already solid companies, not just a handful of high-flyers.

Pro Tip: Start with a clear plan that uses AI-driven productivity as a lens, not a single bet on tech giants. Diversification across value and international exposure can help capture broader gains.

The Breakthrough Idea: research says: biggest gains

In recent investor journals and fund outlooks, researchers have used the exact phrase research says: biggest gains to describe a counterintuitive expectation: AI’s biggest payoff might come from the cumulative improvements across many firms, especially those with solid balance sheets and the ability to convert efficiency into profits. The core idea is simple: AI can reduce costs, speed up decision making, and improve customer experiences across a wide range of industries—from manufacturing and logistics to healthcare and consumer staples. When these efficiency gains compound, they prop up earnings growth for companies that may already be attractively valued. This broader tailwind can translate into price appreciation for sectors and geographies that aren’t at the center of the AI hype, yet stand to benefit disproportionately from AI-enabled productivity.

Pro Tip: If you’re evaluating AI exposure beyond tech stocks, quantify how much a company could save per year through AI-augmented operations and compare that to its current valuation.

Why Value and International Stocks Could Lead AI-Driven Gains

The conventional AI narrative leans heavily on software platforms, processors, and cloud infrastructure. While those areas will certainly grow, the research suggests a complementary outcome: as AI adoption spreads, the winners may be the companies that can translate productivity gains into higher margins. Value stocks—often characterized by lower valuations, steadier cash flow, and resilient dividends—could benefit more than highfliers when AI-enabled productivity lifts earnings, returns on equity, and long-run growth trajectories. In the international arena, developed markets offer diversified exposure to sectors that drive productivity, including financial services, industrials, and consumer staples, all of which can help translate AI improvements into stronger top-line and bottom-line results. Consider these practical channels through which AI may amplify gains for value and international equities:

  • Cost reduction and efficiency: AI-powered automation lowers operating costs in manufacturing, logistics, and administrative functions, boosting margins for value-oriented companies with pricing power.
  • Capital allocation discipline: Firms with strong balance sheets and prudent capital allocation tend to reinvest AI-driven savings in shareholder-friendly ways, supporting multiple expansion and dividends.
  • Diversified demand and resilience: International developed markets provide exposure to economies with varied cycles, helping smooth portfolio returns as AI adoption spreads unevenly across regions.
  • Broad productivity spillovers: AI can lift productivity across industries, which, in turn, raises earnings potential for large, established firms that dominate their sectors.

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From an investor’s viewpoint, this means a reframing: rather than chasing the hottest AI stock or the most prominent hyperscaler, you can seek exposure to the beneficiaries of AI-driven efficiency across the value spectrum and overseas markets. In the process, you may capture the “biggest gains” that research says are possible when AI accelerates productivity on a broad canvas rather than in a narrow slice of the market.

Pro Tip: Use a core allocation to value and international developed equities to build a resilient base for AI-driven gains. This approach complements focused bets on AI innovators and hardware suppliers.

Two ETFs That Could Be Better Buys Than AI Stocks

To put the idea into practice, consider two broad, low-cost exchange-traded funds (ETFs) that align with the idea of AI-powered gains through productivity and diversification. These aren’t the “AI-stock picks” you hear about in headlines; instead, they capture a broader audience of companies poised to benefit from AI-driven efficiency and global growth tailwinds.

1) A US Value-tilt ETF — This type of fund focuses on established American companies with lower valuations, stronger balance sheets, and stable cash flow. When AI boosts efficiency, these firms often translate savings into higher profits and, in turn, multiple expansion. An ETF in this category gives you exposure to sectors like financials, industrials, consumer staples, and energy—areas that can participate meaningfully in an AI-enabled recovery without overexposing you to narrow growth narratives.

Pro Tip: If you already own broad market exposure, a sleeve that tilts toward value can complement your position and reduce drawdowns during periods of tech-heavy volatility.

2) An International Developed Markets ETF — Developed markets outside the US give you exposure to diversified economies that often rely on export-oriented manufacturing, services, and infrastructure investments. AI-driven productivity gains in these regions could lift corporate margins across a broad swath of industries. An international developed markets ETF offers currency diversification and access to sectors that may not be fully represented in a US-only portfolio. Over time, this can help balance risk and potentially enhance long-run returns as AI adoption accelerates globally.

Pro Tip: Pair this with a US value ETF to create a balanced, globally diversified core that can participate in AI-driven productivity across cycles.

Putting It Into Practice: How to Use These ETFs in Your Portfolio

Executing on the idea requires a practical framework you can apply today. Here are steps to incorporate the two ETF themes into a diversified, AI-aware allocation:

  • Define a core allocation: Start with a 60/40 or 70/30 stock/bonds framework, with US value and international developed stocks each occupying a 10-15% slice. The rest can be broad-market exposure or fixed income based on your risk tolerance.
  • Tilt toward value for AI productivity: Within your equity sleeve, overweight value relative to growth. This tilt aligns with the theory that AI-driven gains may materialize as improved profitability and multiple expansion for value-oriented firms.
  • Capture international growth: Add a dedicated international developed markets ETF to diversify away from US-centric AI exposure and to benefit from productivity improvements in Europe, Asia-Pacific, and other developed regions.
  • Set a disciplined rebalancing cadence: Rebalance annually to maintain your target weights. If value or international exposure drifts, rebalance to keep your AI-focused thesis intact over multi-year horizons.
  • Incorporate a cash buffer: Maintain a cash reserve (e.g., 5-10% of the portfolio) for rebalancing opportunities during market swings and to avoid forced selling during drawdowns.
Pro Tip: Use dollar-cost averaging when adding new ETF positions to smooth entry prices, especially in a choppy market where AI headlines can drive sharp swings.

Risks to Consider

As with any investing thesis, the approach above comes with caveats. The idea that the biggest gains from AI will come from value and international stocks is not a guaranteed outcome. Market leadership can shift, and AI adoption can proceed unevenly across sectors and regions. Valuation discipline matters: value stocks can underperform growth for extended periods during positive AI cycles, and international markets can face currency and political risks. A well-constructed plan should include a transparent risk budget, stress-test scenarios, and a willingness to adjust course as data evolves.

Another reality is that the two ETFs discussed here are broad, diversified vehicles. They carry exposure to countless firms—some will benefit from AI, others will not. Diversification helps manage idiosyncratic risk, but it does not eliminate market risk. Keep your time horizon in mind: a multi-year view is typically required for AI productivity themes to fully play out in value and international markets.

Pro Tip: Regularly review expense ratios and liquidity. Even small differences in costs can compound over time, affecting your net returns after years of compounding.

Putting It All Together: A Simple Illustrative Scenario

Let’s walk through a hypothetical, conservative scenario to illustrate how the thesis might unfold. Suppose you have a 15-year horizon and a $100,000 starting portfolio. You allocate 20% to a US value ETF and 20% to an International developed markets ETF, with the remaining 60% split across a broad-market US ETF and a bond sleeve. If AI-driven productivity lifts earnings for the value and international holdings, you could see a combination of higher earnings growth and multiple expansion over time. Even if AI stocks lag in certain years, the diversified, value-tilted and international core could provide steadier growth and more consistent compounding. While this scenario is hypothetical, it demonstrates how a thoughtful, diversified approach aligned with AI productivity can deliver meaningful gains over the long run.

Frequently Asked Questions

Q1: What does research says: biggest gains really imply for AI investing?

A1: It suggests that the largest potential gains from AI may come from broad productivity benefits across many companies, especially those with value characteristics and international exposure, rather than from a handful of AI-focused stocks alone.

Q2: Are US value and international developed markets the only way to gain from AI?

A2: No. They’re a complementary approach. You can combine them with selective AI stock ideas, but the key is to balance risk and to position for AI-driven efficiency across a diverse set of firms and regions.

Q3: Which two ETFs should I consider and why?

A3: A US value ETF and an International developed markets ETF. The US value ETF provides exposure to cash-flow durable firms likely to benefit from AI-driven efficiency, while the international developed ETF adds diversification and access to productivity gains in Europe and other developed regions. Look for funds with low expense ratios and high liquidity.

Q4: How should I implement this in my portfolio?

A4: Start with a core allocation that includes a US value ETF and an International developed markets ETF, then layer in a broad US market ETF for overall exposure and a bond sleeve for risk control. Rebalance annually and adjust based on your risk tolerance and time horizon.

Conclusion: A Practical Path to AI-Informed Gains

The AI era is redefining how profits can be generated, but the route to the biggest gains is not guaranteed to run through the most high-profile AI stocks. The emerging view—supported by research and strategic market thinking—posits that the strongest, most durable gains could come from value-oriented US stocks and international developed markets that leverage AI-driven productivity gains across a broad set of industries. By combining a thoughtful value tilt with international exposure, investors can build a resilient core that stands to benefit as AI reshapes the business landscape. Whether you’re a long-term investor or navigating the current market volatility, this approach offers a practical, disciplined way to participate in AI’s transformative potential while managing risk and costs.

Pro Tip: Keep a running list of AI-related indicators you care about (pricing power, margins, R&D intensity, AI adoption rates) and revisit them quarterly to validate your ETF selections against evolving data.
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Frequently Asked Questions

What does research says: biggest gains imply for AI investing?
It suggests the largest potential gains from AI may come from broad productivity-driven improvements across many firms, especially those with value traits and international exposure, rather than from a narrow set of AI-focused stocks.
Why might US value and international developed markets lead AI-driven gains?
Because AI can lift efficiency and margins across a wide range of established firms, value stocks with solid cash flow and pricing power can compound gains, while international developed markets provide diversification benefits and exposure to regions where AI adoption and productivity gains may unfold differently.
Which two ETFs are recommended and why?
A US value ETF and an International developed markets ETF. They offer broad, low-cost exposure to firms likely to benefit from AI-driven productivity, across sectors and regions, helping to balance risk and capture potential gains beyond the AI giants.
How should I implement this idea in a real portfolio?
Start with a core allocation that includes the US value and International developed ETFs, add a broad market sleeve for market exposure, and include bonds for risk control. Rebalance annually, use dollar-cost averaging for entries, and adjust weights based on risk tolerance and time horizon.

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