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AI ETFs are diversified by ticker count, but many remain concentrated by theme. A fund may hold dozens of companies and still depend heavily on the same forces: semiconductor demand, cloud and data-center spending, and large technology companies’ AI businesses. To judge an AI ETF’s diversification, look beyond its holding count at its largest positions, sector and country exposures, investment method, costs, liquidity, and overlap with funds you already own.
What does diversification mean for an AI ETF?
Diversification has two dimensions. Security diversification asks how many stocks a fund owns and how much of the portfolio sits in its largest positions. Economic diversification asks whether those companies rely on meaningfully different sources of revenue and face different business risks.
An AI fund can score well on the first measure without being broadly diversified on the second. A portfolio may include chipmakers, cloud platforms, software companies and businesses that use AI, yet still be sensitive to a shared set of outcomes: data-center investment, demand for computing capacity, cloud budgets and the pace at which AI products are adopted. If those drivers weaken together, owning more tickers does not necessarily provide much protection.
That is why “50 holdings” or “73 holdings” is a starting point, not a verdict. Investors should also ask how much the leading positions weigh, whether the companies’ business drivers differ, and how much the fund duplicates investments elsewhere in the portfolio.
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How many stocks do AI ETFs hold, and does that make them diversified?
Holding counts vary, and a higher count does not automatically mean a fund has less concentrated exposure. Two funds with different numbers of stocks can still have many of the same large technology and semiconductor companies near the top.
| Fund | Reported holdings | Largest-position information | Expense ratio |
|---|---|---|---|
| FAI | 50 | Top five totaled about 39.2% on September 25, 2026 | 0.65% |
| AGIX | 73 | Top ten totaled about 32.9% on September 30, 2026 | 1.00% |
The FAI figures show why count alone can mislead: 50 securities coexist with nearly two-fifths of the portfolio in its top five. AGIX’s top ten account for about one-third, a more even weighting than FAI’s top five, but its leading names still include major technology and semiconductor companies. These figures are dated snapshots, not permanent portfolio characteristics.
Counts also do not reveal how much holdings overlap. A fund can own a long list of companies while giving substantial weight to the same few names that already dominate a broad-market or technology fund. Check the actual holdings and weights rather than assuming a larger portfolio is automatically more balanced.
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No, but those companies can be significant positions, and many AI funds also hold other large technology, cloud and semiconductor businesses. The relevant question is not whether a fund owns two familiar names; it is how much of the portfolio is concentrated in its leaders and how much its companies share underlying business drivers.
FAI: a concentrated top five within 50 holdings
FAI’s reported holdings as of September 25, 2026, included Microsoft at 9.54%, NVIDIA at 8.33%, Amazon at 7.42%, Broadcom at 7.06% and Alphabet at 6.89%. Together, those five positions represented about 39.2% of the fund. The next five were Palantir at 5.29%, Meta at 4.65%, AMD at 4.39%, Micron at 4.00% and Taiwan Semiconductor Manufacturing at 3.67%.
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This mix reaches across platforms, cloud infrastructure, chips and software, but the largest positions still tie a substantial share of the portfolio to a relatively narrow technology-and-AI investment theme. The holdings snapshot is not a promise that these weights will remain unchanged.
AGIX: a lower top-ten share, with overlapping themes
AGIX reported 73 holdings and a 1.00% total annual operating expense. Its top ten on September 30, 2026, were Meta at 4.83%, NVIDIA at 3.83%, Alphabet at 3.73%, Microsoft at 3.52%, Apple at 2.87%, Amazon at 2.80%, TSMC at 2.79%, AMD at 2.27%, Tesla at 2.26% and Palantir at 2.25%. Those positions added up to roughly 32.9%.
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What is the difference between active and index AI ETFs?
An actively managed fund’s portfolio is selected by a manager, while an index fund follows rules designed to track a specified index. Neither approach, by itself, establishes that the fund is more diversified, less risky or more likely to perform well.
Active management: BAI
BlackRock’s BAI fact sheet describes an actively managed portfolio spanning three parts of the AI technology stack: infrastructure, intelligence, and applications and services. A manager can change positions as their view changes. That flexibility does not guarantee lower concentration or better performance, so investors still need to inspect the actual holdings and weights.
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Index tracking: AIQ
AIQ’s SEC-filed summary prospectus, dated April 1, 2025, says the fund seeks results corresponding generally to the price and yield performance, before fees and expenses, of the Indxx Artificial Intelligence & Big Data Index. An index fund’s eligibility rules and weighting method shape what it owns. Read the index methodology for its revenue screens, rebalancing schedule and any limits on position sizes; an index label alone does not explain how concentrated the resulting portfolio may be.
When comparing funds, put the method beside the portfolio evidence. For an active fund, consider what mandate guides the manager and how its holdings reflect that mandate. For an index fund, understand the index rules and their effect on eligibility and weights. In either case, the portfolio you actually own—not the description on the label—is what determines your exposure.
How can you evaluate an AI ETF’s diversification?
Use a checklist that looks at both portfolio construction and the role the fund would play alongside your other investments. Investor.gov advises investors to examine fees, risks, how an index is constructed and the fund’s actual holdings.
- Check the largest positions. Review the single biggest holding and the combined weight of the top five and top ten. A high combined share means a small group of stocks can have an outsized influence on results.
- Look at sector and country exposure. Review how much is invested in technology, semiconductors or other relevant sectors, and where the companies are based. A longer list of company names does not necessarily imply a broad mix of industries or geographies.
- Identify shared business drivers. Ask whether holdings depend on different revenue sources or are tied to similar conditions, such as semiconductor demand, cloud investment or AI adoption. This helps distinguish a portfolio with many securities from one with a broader spread of economic risks.
- Read the fund’s construction method. For an index fund, examine eligibility criteria, weighting and rebalancing rules. For an actively managed fund, examine its stated scope and then check whether the current portfolio matches it.
- Compare actual holdings for overlap. If you already own broad-market or technology funds, compare their positions with the AI ETF’s holdings. Repeated exposure to the same large companies can add to your concentration even when the fund names and ticker counts differ.
- Include fees and liquidity in the comparison. Check the expense ratio, assets and bid-ask spread. A fund’s stated portfolio breadth does not tell you what it costs to hold or how much trading may cost when buying or selling.
- Use dated figures carefully. Holdings, weights, assets, spreads and expense ratios can change. Consult the latest fact sheet, prospectus and holdings file when making a decision rather than relying on an older snapshot.
How much do AI ETF fees matter?
Fees reduce the return left for an investor, so compare the fund’s expense ratio with both other funds and appropriate category benchmarks. The SEC’s Investor.gov guidance puts it plainly: “Fees and expenses reduce the value of your investment return.”
The Investment Company Institute reported 2024 asset-weighted average expense ratios of 0.14% for index equity ETFs and 0.44% for actively managed equity ETFs. Those are broad category averages, not required prices or predictions for any particular fund. In the cited fund information, FAI listed a 0.65% expense ratio and AGIX listed a 1.00% total annual operating expense—both above those respective broad reference points.
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A higher expense ratio creates a larger performance hurdle: the fund must earn more before fees to leave the same return after fees, all else equal. Fees are only one part of the decision, however. Compare the charge with the fund’s strategy and portfolio, and do not infer that a higher fee means better diversification or results.
Should you buy an AI ETF or a broad-market index fund?
They serve different purposes. A broad-market index fund is intended to provide exposure across a wider market, while an AI ETF focuses on companies selected for a specific theme. Whether either belongs in a particular portfolio depends on the investor’s goals, risk tolerance and existing holdings; the available fund facts do not establish a universally best choice.
Before adding a thematic fund, work out what exposure it would add rather than relying on the theme name. If your existing funds already hold the AI ETF’s largest companies, the new fund may increase the weight of those positions instead of adding much economic diversification. Compare the fund’s top holdings and weights with your current portfolio, then decide whether the added concentration is intentional.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.What can these examples tell you—and what can’t they?
The dated holdings demonstrate that AI ETFs can differ in holding count and top-position concentration. They do not establish which fund is best, how either will perform, or what its portfolio will look like after the reported date. FAI’s cited holdings are as of September 25, 2026; AGIX’s are as of September 30, 2026. BAI’s fact sheet is dated March 31, 2026, and AIQ’s cited prospectus is dated April 1, 2025.
Use those figures as examples of how to analyze a portfolio, not as live trading data. Before investing, verify current holdings, costs, index or management rules and liquidity from the fund’s latest published documents. That date check matters especially for a thematic fund, because the names and weights that shape its exposure can change.
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Frequently Asked Questions
Can an AI ETF lose money even if it owns dozens of stocks?
Yes. A fund’s value can fall even when it holds many securities, particularly if its largest holdings or the businesses those holdings depend on decline together. Holding count alone does not guarantee protection from losses.
Do AI ETF holdings change after I buy shares?
They can. Fund holdings and weights change over time; for example, FAI reports quarterly rebalancing. Review the fund’s latest published holdings rather than assuming a past list remains current.
How do I check whether two ETFs own the same stocks?
Compare their latest holdings files, including each company’s portfolio weight, rather than comparing only the funds’ names or total holding counts. A repeated company can contribute meaningfully to your overall exposure when it is also held in other funds you own.
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Not by itself. For an index-tracking fund, look up the index methodology and prospectus to understand eligibility screens, weighting and rebalancing rules.
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