AI stocks vs traditional value: how to balance your portfolio in 2026

After years of AI-driven growth dominance, 2026 has seen a clear rotation: value stocks are outperforming growth across all major U.S. market-cap categories, with the Russell 2000 Value index up 9.7% vs 2.6% for growth as of April 2026, according to Oppenheimer Asset Management. That shift doesn't invalidate the AI thesis — but it does force a more deliberate approach to how much exposure you hold, and why. Here's a framework for balancing both.

What's actually happening in markets right now

As of April 2026, the AI stock narrative that dominated 2023, 2024, and most of 2025 is showing its first sustained pause. Growth massively outperformed value during that period — the Vanguard Growth ETF (VUG) returned 20.3% in 2025 vs 12.7% for the Vanguard Value ETF (VTV), according to Motley Fool reporting on Vanguard data. Growth outperformed value in 13 of the last 16 years going back to 2010.

In 2026, something shifted. Value stocks are beating growth across all major U.S. market-cap categories, according to Oppenheimer Asset Management's April 2026 analysis. The Russell 2000 Value index is up 9.7% year-to-date vs 2.6% for its growth counterpart as of April 10. Morningstar analysis cited energy stocks as a primary driver — a sector heavily represented in value indices — combined with a pullback in high-multiple AI names from their 2025 peaks.

This doesn't mean the AI story is over. Fidelity's Asset Allocation Research Team has estimated that AI has contributed significantly to recent U.S. economic growth — accounting for an estimated 60% of growth over a recent period, according to their methodology, and earnings for AI-exposed tech companies have been growing in the mid-20% range compared to flat or mid-single-digit growth for the rest of the S&P 500, according to Fidelity reporting. The long-term AI thesis remains intact. But the short-term performance leadership has rotated.

The case for maintaining AI exposure

If the rotation is cyclical rather than structural — which the evidence suggests — the question becomes: how much AI exposure still makes sense given current valuations and the environment?

The long-term investment thesis for AI stocks doesn't change based on a few months of underperformance. For clarity, "AI stocks" here includes semiconductor firms, cloud platforms, and software companies whose growth is directly tied to AI adoption — not just Nvidia-type names. Several data points remain structurally compelling:

• Earnings growth divergence is real. AI-exposed tech companies are growing earnings in the mid-20% range vs flat to mid-single digits for the rest of the S&P 500, per Fidelity. That gap doesn't disappear in a cyclical rotation.
• Valuations have compressed. BlackRock noted that 2025's tech performance came primarily from earnings growth, not multiple expansion — and that multiples have slightly contracted since then. The most stretched AI valuations of 2024 are less stretched today.
• The market is underallocated. BlackRock's review of 901 moderate advisor portfolios found the average technology allocation is 9% below the S&P 500 weighting, even though 60% of advisors say they are bullish on AI stocks. Underallocation by professional advisors suggests most retail investors are also underexposed relative to the benchmark.
• The AI market is early. The artificial intelligence market is currently valued at approximately $371 billion with projections toward $2.4 trillion by 2032, according to IndexBox citing industry data. Whether these projections materialize is uncertain, but the directional opportunity is orders of magnitude larger than the current allocation in most portfolios.

The case for traditional value stocks

Value stocks aren't simply "not AI" — they represent a distinct investment philosophy with its own compelling logic in the current environment:

• Valuation support is real. After years of compression, value stocks are trading at historically wide discounts relative to growth. Invesco's analysis found value outperformed growth in both the U.S. and Europe in 2025 despite intense AI focus, and expects the trend to continue as economies accelerate.
• Higher-rate environment favors value. High-multiple growth stocks are mathematically more sensitive to discount rates — their future earnings are worth less when discounted at higher rates. Value stocks derive more of their value from near-term earnings and dividends, making them less sensitive to the "higher for longer" rate environment.
• Dividends provide real yield. In an environment where inflation is running above 3%, dividend-paying value stocks provide an income stream that offsets some of the purchasing power erosion. AI growth stocks typically pay no dividends.
• Cyclical leadership tends to persist. Hartford Funds data shows value and growth leadership tend to run in multi-year cycles. When value takes the lead after extended growth dominance, the rotation has historically been sustained — not a single quarter.
• International value is outperforming. MSCI data shows international developed market value significantly outperformed U.S. growth in 2025, with European banks in particular driving returns. Geographic diversification through value-oriented international exposure has added return in the past 18 months.

How to think about your allocation

The right AI vs value allocation depends heavily on your time horizon, risk tolerance, and what you already own. There's no universal answer. Note that these categories overlap — your S&P 500 allocation already includes AI exposure, so the "AI / tech" portion represents an intentional overweight beyond what the index already provides. Here's a framework:

NerdWallet suggests a practical guideline: devote no more than 10% of your overall portfolio to individual stocks in any single theme. For investors using ETFs for AI exposure — such as the iShares A.I. Innovation and Tech Active ETF (BAI) or the Roundhill Generative AI & Technology ETF (CHAT) — a higher allocation is more defensible than concentrated single-stock bets, since ETF exposure spreads risk across multiple AI layers (infrastructure, applications, semiconductors).

One useful framework from TECHi's April 2026 analysis suggests thinking about AI exposure across multiple layers: infrastructure (data centers, chips), platforms (cloud providers), and applications (software using AI). A balanced AI allocation across all three layers has historically shown better risk-adjusted returns than concentration in any single layer.

The DCA investor's approach

For investors using dollar-cost averaging — which is most long-term investors — the AI vs value question doesn't need to be an either/or decision made at a single point in time.

The practical DCA approach: If you DCA into a broad index fund (S&P 500 or total market), you already own both AI stocks and value stocks in their market-weighted proportions. The S&P 500 naturally includes the big AI names (Nvidia, Microsoft, Alphabet, Meta) as well as value-leaning sectors (energy, financials, consumer staples). Market-cap weighting means you automatically hold more of what's working and less of what isn't, without any active decisions.

If you want targeted exposure: Consider running a separate, smaller DCA schedule into a specific AI ETF or value ETF alongside your core index allocation. TECHi's suggested framework for a $10,000 AI allocation covers multiple layers of the ecosystem rather than concentrated single-stock bets — the same logic applies to a monthly DCA amount.

The rotation timing problem: The 2026 value rotation is real, but the timing of how long it lasts is unknowable. Invesco's analysis expects value to outperform as economies accelerate — but if the Federal Reserve cuts rates later this year, growth/AI stocks historically re-accelerate quickly. Trying to time the rotation by shifting allocation based on a few months of performance data is more likely to hurt returns than help them.

What not to do

• Don't abandon AI exposure based on a few months of underperformance. Value led in 2016 and 2022 before growth resumed dominance. The AI earnings growth story hasn't changed — the multiple expansion story has cooled, which is different.
• Don't concentrate in single AI stocks at stretched valuations. Companies like Palantir have at times traded near 100x forward earnings. Even strong AI execution may not justify premiums at that level if growth expectations moderate.
• Don't treat value stocks as "safe." Value stocks can and do decline significantly in recessions. Energy and financial stocks — the largest value sector drivers in 2026 — are highly cyclical. Value is not synonymous with low risk.
• Don't chase whichever style has just outperformed. By the time a rotation is obvious enough to act on, much of the move is usually over. Most investors who rotated into value after its 2022 outperformance missed the growth re-acceleration of 2023–2025.
• Don't ignore international value. MSCI data shows international developed market value significantly outperformed U.S. growth in 2025. Geographic diversification through international value-oriented exposure is an underutilized tool for most U.S.-focused retail investors.

The bottom line

The 2026 value rotation is real and, based on historical patterns, may have further to run. That doesn't mean abandoning AI exposure — the long-term earnings growth story remains intact, and many portfolios, including advisor-managed ones, remain underweight AI relative to its share of index weighting.

The sensible approach for most long-term investors is to hold both through a diversified index, with targeted tilts toward AI ETFs or value/dividend ETFs depending on time horizon and risk tolerance. The allocation table above provides a starting framework, but your specific situation — age, income stability, existing portfolio composition — matters more than any general guideline.

For DCA investors specifically: keep your schedule running, let the index rebalance itself naturally, and resist the urge to make tactical allocation shifts based on which style is winning in any given quarter. The goal isn't to pick the winning style for 2026. It's to build a portfolio that can handle whichever one wins next.