Holdings overlap in “AI” funds is extreme. Many portfolios marketed as cutting-edge AI plays look suspiciously like rebranded large-cap tech—often with higher fees. Here’s how to tell what you really own, why the overlap happens, and what to check in the factsheets before you pay up.
Why this matters now
AI has pulled billions into thematic funds in 2024–25. Morningstar’s latest tallies show global assets in AI and big-data funds topping about $38 billion by Q1 2025, with Europe the biggest market and the vast majority of holdings still concentrated in U.S. tech leaders. Nvidia appears in roughly 9 out of 10 AI funds, alongside repeat offenders like Microsoft, Alphabet, Meta and Amazon. (etf.com, MarketWatch)
That popularity creates a simple, uncomfortable question: if you already own broad tech or Nasdaq exposure, how different is your new AI ETF or fund, really?
What’s actually inside the largest AI-thematic ETFs
A quick scan of popular vehicles and their fees:
- Global X Robotics & AI (BOTZ) — expense ratio 0.68%. (Global X ETFs)
- Global X Artificial Intelligence & Technology (AIQ) — 0.68%; tracks Indxx Artificial Intelligence & Big Data Index. (Global X ETFs, ETF Database)
- WisdomTree Artificial Intelligence & Innovation (WTAI, U.S.) — 0.45%; (UCITS variant often 0.40%). (WisdomTree, justetf.com)
- First Trust Nasdaq AI & Robotics (ROBT) — 0.65%. (ftportfolios.com)
- Roundhill Generative AI & Technology (CHAT) — 0.75%, actively managed. (Roundhill Investments)
Now compare with “plain vanilla” tech and semi trackers:
- Vanguard Information Technology (VGT) — 0.09%. (Vanguard)
- Technology Select Sector SPDR (XLK) — ~0.08–0.10%. (SSGA)
- VanEck Semiconductor (SMH) — 0.35%; iShares SOXX — 0.34%. (ETF & Mutual Fund Manager | VanEck, BlackRock)
That cost spread is stark: many AI-thematic ETFs charge 5–8× the fee of broad tech trackers.
Top-10 names & weight caps: the mechanics behind the sameness
Why do AI funds look alike? Partly because index rulebooks funnel them into the same mega-cap names, then weight caps prevent any single giant from dominating. Example: AIQ’s index caps “high-exposure” constituents at 3% each and “low-exposure” names at 1%, with a 0.3% minimum weight; the index reconstitutes annually and rebalances semi-annually. (assets.globalxetfs.com)
Caps are supposed to help diversification, but they also flatten genuine conviction. Meanwhile, active AI funds like CHAT highlight the flip side—fewer caps, more discretion, but usually even higher fees. (blog.roundhillinvestments.com)
Across the universe, the top-10 holdings frequently include: Nvidia, Microsoft, Alphabet, Amazon, Meta, Broadcom, AMD, Salesforce, Oracle, and sometimes Apple or ServiceNow—exact line-ups vary, but the directional overlap is persistent and well-documented. Morningstar and MarketWatch’s synthesis: Nvidia is the near-ubiquitous common denominator in AI funds. (MarketWatch)
Overlap you can measure
Third-party overlap tools routinely show double-digit commonality between AI-thematic funds and cheap, broad tech ETFs. One example snapshot: VGT vs. AIQ showing ~33% overlap by weight (varies over time). If you already hold Nasdaq-100 or tech sector funds, an AI sleeve may stack the same leaders. (etfrc.com)
Factor exposures: you’re paying for growth & momentum (and sometimes quality)—not magic
Strip out the marketing and most AI funds lean hard into classic growth and momentum factors, with a pinch of quality (profitability, balance-sheet strength). Morningstar’s risk models and factor monitors have repeatedly flagged that pattern, and it’s perfectly sensible: the cash-rich mega caps building the AI stack screen as high quality; the buzzy names with surging prices screen as momentum. (Morningstar Indexes, Morningstar Direct)
But here’s the catch: you can access those same factors through broad tech (VGT/XLK), semis (SOXX/SMH), or even factor ETFs (quality, momentum) at far lower fees. If an AI fund doesn’t deliver meaningfully different factor tilts, you may just be paying more for exposure you already own. (Vanguard, SSGA)
Are AI funds “just expensive tech”? Not always—here’s where they can differ
- Methodology “purity.” Some indexes weight by revenue intensity from AI (e.g., Bloomberg’s AI index methodology), attempting to push capital toward the companies most economically tied to AI rather than simply the biggest. That can shift weights toward semis, model-hosting platforms, inference hardware, or niche software suppliers. (assets.bbhub.io)
- Up- and down-the-stack breadth. Certain funds reach beyond hyperscalers into tools (EDA), packaging, opticals, substrates, and data-center power—areas under-represented in broad tech. If your AI fund reaches deep into SiC power, optical interconnects, or HBM memory, that’s a real difference vs. VGT/XLK. (You can verify in holdings lists.)
- Regional mix. Some UCITS funds include more non-U.S. innovators, giving you exposure that VGT/XLK omit; but again, scrutinize whether the overweight is consequential.
Still, a lot of products revert to the same leaders—Morningstar warns explicitly about overlap with the “Magnificent Seven.” (Morningstar)
Cheaper substitutes for the common exposures (educational, not advice)
If your goal is general AI beta via the largest platform winners:
- VGT/XLK (broad U.S. tech) provide heavy Microsoft/Nvidia/Apple exposure at a fraction of the cost. (Vanguard, SSGA)
If you want the hardware spine of AI:
- SOXX/SMH (semiconductors) concentrate the chipmakers and usually charge ~0.34–0.35%. Note: these are concentrated too, just more transparently so. (BlackRock, ETF & Mutual Fund Manager | VanEck)
If you want a broader “AI adopters” tilt (apps & beneficiaries) without paying thematic premia:
- A standard Nasdaq-100 fund (e.g., QQQ) keeps fees lower (~0.20%) and already captures many AI-exposed names—albeit with broader non-AI holdings as well. (Investopedia)
Again, these are examples of exposure types—not recommendations. The point is to align what you’re paying with what you’re actually getting.
The fee hurdle math (why basis points matter)
Suppose an AI fund charges 0.68% and a broad tech fund charges 0.09%. That 59 bps gap is the performance hurdle the pricier fund must clear each year just to break even with the cheaper alternative. Over a 10-year horizon, those extra fees compound meaningfully, especially in volatile themes where timing risk already looms large. (Morningstar and FT have repeatedly noted that many thematic ETFs underperform their benchmarks over time, partly due to launch-timing and valuation effects.) (Financial Times)
What to read in the factsheet before you buy
1) Index methodology (or active process).
- Selection rules: Are constituents screened by revenue share from AI, patents, R&D intensity, or buzzwords scraped from filings?
- Weight caps: Caps near 3% (AIQ’s index) create breadth but also dilute the “winners.” Active funds may exceed caps but charge more. (assets.globalxetfs.com)
2) Rebalance & reconstitution frequency.
- Semi-annual rebalances can lag rapid leadership changes. Check when the next reset occurs.
3) Fee & trading costs.
- Expense ratio is obvious. Also check average spreads and securities-lending policies (the latter can offset costs but introduces counterparty considerations). XLK/VGT show how low fees can go. (SSGA, Vanguard)
4) Concentration/overlap.
- Use a holdings-overlap tool to see how much of your AI fund duplicates your existing tech or Nasdaq holdings. (Example snapshot: VGT vs. AIQ ~33% overlap by weight.) (etfrc.com)
5) Country & size mix.
- Many AI funds are U.S.-heavy. If you seek diversification, confirm non-U.S. weights actually move the needle. Morningstar notes Europe is the biggest market for AI funds, but the holdings are still largely U.S. (MarketWatch)
6) Capacity to be different.
- If it’s an index fund with tight caps, don’t expect big off-benchmark calls. If it’s active (e.g., CHAT), understand the team’s process and risks—then weigh those against the fee. (Roundhill Investments)
Red flags that scream “expensive proxy”
- Top-10 looks like your tech ETF’s top-10. (Nvidia/Microsoft/Alphabet/Amazon/Meta + usual suspects.)
- Fees >0.60% with no clear differentiation in holdings or factor profile.
- Marketing claims about “pure-play AI” but factsheet tilts toward mega-cap platform companies already dominant in VGT/XLK.
- Sparse disclosure on how the index defines and measures AI exposure.
When “narrow” can be useful (and when it can’t)
If your goal is to tilt specifically toward the nuts and bolts of AI infrastructure—HBM memory, advanced packaging, optical interconnects, silicon carbide power, liquid-cooling vendors—then a carefully chosen AI fund can do something different from a broad tech ETF. But verify this in the holdings: names linked to chips (NVDA/AVGO/AMD), semicap, optics, power/thermal should be present and sized to matter. Otherwise, the fund may be AI-by-marketing, tech-by-exposure.
Practical, non-advisory checklist
- Open the PDF. Read the methodology and caps. (AIQ’s index: 3%/1% caps, 0.3% min; semiannual rebalance.) (assets.globalxetfs.com)
- Map the overlap. Check how much your AI fund duplicates VGT/XLK/QQQ or any semi ETF you already hold. (etfrc.com)
- Compare fees. Anchor against VGT (0.09%), XLK (~0.08–0.10%), SOXX (0.34%), SMH (0.35%). (Vanguard, SSGA, BlackRock, ETF & Mutual Fund Manager | VanEck)
- Look for true differentiation. Are there infrastructure names (packaging, optics, power) or AI adopters you won’t get in broad tech?
- Size your expectations. Thematic funds often launch around hype cycles and underperform over time; fees compound the drag. (Financial Times)
Bottom line
“AI-thematic” doesn’t automatically mean new, purer, or better exposure. For many products, it means costlier exposure to the same megacaps you already own elsewhere. That doesn’t make them useless—just redundant unless the methodology genuinely bends the portfolio into less obvious parts of the AI stack.
If you want broad platform winners, broad tech/semis often deliver that at a fraction of the cost. If you want “pure-play AI,” insist on transparent selection rules tied to revenue or product intensity—and confirm the holdings tell a different story than the Nasdaq-100.
Sources (selected)
- AI & big-data fund assets (~$38 bn) and Europe’s lead; Nvidia in ~89% of AI funds. (etf.com, MarketWatch)
- BOTZ fee 0.68%; AIQ fee 0.68% and index; WTAI fee 0.45% (U.S.) / UCITS 0.40%; ROBT fee 0.65%; CHAT fee 0.75%. (Global X ETFs, WisdomTree, justetf.com, ftportfolios.com, Roundhill Investments)
- AIQ index 3%/1% caps and schedule (Indxx methodology summary). (assets.globalxetfs.com)
- Overlap example (VGT vs. AIQ ~33% by weight; snapshot varies). (etfrc.com)
- Broad tech and semi ETF costs: VGT 0.09%, XLK (~0.08–0.10%), SOXX 0.34%, SMH 0.35%. (Vanguard, SSGA, BlackRock, ETF & Mutual Fund Manager | VanEck)
- Thematic ETF underperformance patterns. (Financial Times)
Disclosure
The information above is for general informational and educational purposes only and does not constitute investment, financial, legal, or tax advice. Markets, products, fees, and methodologies change quickly—please verify all facts and figures directly from the cited fund providers, prospectuses, and regulatory filings before relying on them. We do not recommend buying, selling, or shorting any security or fund. If you need advice tailored to your circumstances, consult a qualified professional in your jurisdiction.