Best ETF for AI Infrastructure in 2026: Beyond SMH

Overview

The artificial intelligence infrastructure buildout continues to accelerate in 2026, with global AI capital expenditure projected to surpass $300 billion this year according to Bloomberg Intelligence (April 2026), yet most retail investors remain anchored to the VanEck Semiconductor ETF (SMH) as their sole AI play. While SMH has delivered a respectable 18.4% year-to-date gain through April 17, 2026, a broader universe of ETFs now offers more targeted, diversified, or risk-adjusted exposure to the full AI infrastructure stack — spanning data centers, power infrastructure, networking, and custom silicon beyond just chip fabrication.

Sources: Bloomberg Intelligence, April 2026; FactSet ETF Analytics, April 17, 2026

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Key Metrics (as of April 17, 2026)

ETF	Ticker	AUM	YTD Return	Expense Ratio	Top Holdings	P/E (Wtd. Avg.)
VanEck Semiconductor ETF	SMH	$22.1B	+18.4%	0.35%	NVDA, TSMC, ASML	28.6x
Global X AI & Technology ETF	AIQ	$3.8B	+21.2%	0.68%	MSFT, NVDA, GOOGL	31.4x
iShares Exponential Tech ETF	XT	$2.9B	+14.7%	0.46%	Broad tech, 200+ stocks	24.1x
Invesco AI and Next Gen Software ETF	IGPT	$1.2B	+23.6%	0.60%	NVDA, AMD, ORCL	33.8x
First Trust Nasdaq AI & Robotics ETF	ROBT	$0.9B	+16.1%	0.65%	Broad AI/robotics mix	26.7x
Roundhill Generative AI & Technology ETF	CHAT	$0.6B	+28.3%	0.75%	NVDA, META, MSFT	37.2x
Utilities Select Sector SPDR	XLU	$17.4B	+11.9%	0.09%	NEE, SO, DUK	19.3x

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Why ETF Selection Matters More Than Ever in the AI Cycle

The instinct to buy SMH is understandable — semiconductor companies sit at the epicenter of AI compute demand, and NVIDIA's dominance has made the fund a proxy trade for the entire theme. However, the AI infrastructure buildout of 2026 is far more architecturally complex than simply buying chips. Understanding which ETF captures the right slice of this ecosystem is now a critical portfolio decision, not an afterthought.

Consider the data: IGPT has outpaced SMH by 5.2 percentage points year-to-date through April 17, 2026, while CHAT has outperformed by a striking 9.9 points (FactSet ETF Analytics). This divergence reflects the fact that AI value creation is migrating up the stack — from raw silicon toward software platforms, cloud orchestration layers, and model infrastructure operators like Oracle and Microsoft Azure, all of which are more heavily weighted in software-tilted AI ETFs.

There is also an often-overlooked dimension: power and utilities exposure. Training a single frontier AI model can consume as much electricity as a small city over several weeks, according to reporting from Reuters (March 2026). This has made grid-scale power providers structurally important to AI infrastructure, which is why a position in XLU — or in infrastructure-focused funds that include data center REITs and utility operators — provides genuine diversification, not just correlation. XLU's 11.9% YTD gain, while lagging pure-play tech ETFs, comes with a weighted-average P/E of just 19.3x and meaningful dividend yield, providing ballast in a high-multiple portfolio.

The expense ratio spread also deserves attention. SMH charges 0.35% annually, while CHAT charges 0.75% — a 40 basis point gap that compounds meaningfully over time. Investors should ask whether the excess return potential justifies the fee differential, particularly given that higher-fee thematic ETFs often concentrate in the same mega-cap names already owned elsewhere.

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Forward Outlook: How AI Infrastructure Spending Shapes ETF Performance

Looking into the second half of 2026, the investment thesis across AI infrastructure ETFs hinges on three converging forces: hyperscaler capital expenditure cycles, custom silicon proliferation, and data center energy constraints.

On the capex front, Microsoft, Alphabet, Amazon, and Meta have collectively guided for over $230 billion in combined infrastructure spending in fiscal 2026, according to FactSet consensus estimates compiled as of April 15, 2026. This spending tide lifts ETFs with heavy hyperscaler exposure — namely AIQ and CHAT — more directly than semiconductor-only funds, since a significant portion flows to software tooling, networking equipment (Arista Networks, Broadcom), and cloud service contracts.

The custom silicon trend represents a meaningful structural shift that analysts expect to reshape ETF performance divergence. Morgan Stanley's semiconductor research team estimated in a March 2026 note that merchant chip market share could decline by 3–5 percentage points over 2026–2028 as companies like Google (TPUs), Amazon (Trainium), and Meta (MTIA) scale proprietary accelerators. This suggests that ETFs overly concentrated in NVIDIA — such as SMH, where NVIDIA represents approximately 19% of the portfolio — may face incremental headwinds as hyperscaler AI chip budgets diversify internally.

Conversely, ETFs with broader software and platform exposure (IGPT, CHAT, AIQ) may be better positioned to capture value from AI monetization, not just AI training infrastructure. Enterprise software companies are increasingly converting AI investments into billable services, and analysts at Bloomberg Intelligence project that AI-related software revenue could reach $85 billion globally by year-end 2026, up from an estimated $52 billion in 2025.

For investors comfortable with longer time horizons and sector-specific risk, a blended ETF approach — combining a core semiconductor position (SMH or SOXX) with satellite allocations to IGPT or AIQ and a defensive layer in XLU — may offer more balanced AI exposure than any single fund.

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Risk Factors

• Valuation Compression Risk: Several AI-focused ETFs carry weighted-average P/E ratios above 33x (IGPT at 33.8x, CHAT at 37.2x as of April 17, 2026), well above the S&P 500's historical median of approximately 18–19x. Any deterioration in AI revenue growth rates or corporate earnings guidance could trigger a sharp multiple contraction across these high-expectation funds, amplifying drawdowns relative to the broader market.

• Concentration and Overlap Risk: Despite their different names and mandates, many AI ETFs share the same top holdings — NVIDIA, Microsoft, and Alphabet frequently appear in the top three positions across AIQ, IGPT, and CHAT simultaneously. This creates hidden correlation, meaning a portfolio holding multiple AI ETFs may be far less diversified than it appears, effectively amplifying single-stock risk disguised as fund diversification.

• Regulatory and Geopolitical Risk: U.S. export controls on advanced semiconductors to China — which were tightened again in late 2025 per Reuters reporting — continue to cloud the revenue outlook for companies like NVIDIA and ASML, both significant holdings in SMH. Any escalation in U.S.-China technology tensions or new restrictions from the Bureau of Industry and Security (BIS) could directly impair fund performance, particularly for semiconductor-heavy ETFs with meaningful international revenue exposure.

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Investment Outlook

The AI infrastructure investment opportunity in 2026 is real, large, and still early in its development arc — but the choice of vehicle matters as much as the thesis itself. SMH remains a solid, liquid, lower-cost core holding for semiconductor exposure, though investors relying on it exclusively may be underexposed to the software, networking, and power infrastructure layers that are absorbing an increasing share of AI capital flows.

Based on current data through April 17, 2026, IGPT and AIQ appear well-positioned for investors seeking broader AI stack exposure, while CHAT offers higher-conviction thematic concentration at the cost of elevated valuation risk. XLU provides a non-obvious but analytically sound complement, anchoring AI infrastructure portfolios with power infrastructure exposure at a fraction of the valuation multiple.

Analysts expect AI infrastructure spending to remain a multi-year secular theme, but near-term volatility and valuation risk suggest a disciplined, diversified approach is prudent for most investors.

Disclaimer: This content is for informational purposes only and was produced with AI assistance. It does not constitute financial advice. All investment decisions carry risk and are solely your own responsibility. Past performance is not indicative of future results.