Key Highlights

  • Global X Artificial Intelligence ETF (ASX: GXAI) had a fund size of $270.55 million and 16,094,333 units outstanding in the latest ASX market snapshot provided.
  • The portfolio comprised 89 companies, with technology accounting for 68.52% of the portfolio and the United States representing 71.04% of geographic exposure.
  • The ETF held 98.94% in stocks and 1.06% in cash, while companies with market capitalisations above $1 billion accounted for 94.99% of the portfolio.
  • GXAI's management fee was 0.57%, and its latest listed final distribution was $0.804 per unit, with the ex-date on 2 July 2026.

The Global X Artificial Intelligence ETF (ASX:GXAI) provides exposure to companies associated with the development and use of artificial intelligence and big-data technologies. Global X states that the fund seeks to track, before fees and expenses, the Indxx Artificial Intelligence & Big Data Index. The ETF commenced on 8 April 2024 and is classified within the Equity Global Technology category.

The latest ASX data supplied for the fund shows 89 companies in the portfolio. Stock holdings represented 98.94% of assets, while cash represented 1.06%. No bonds or other asset categories were recorded. This allocation leaves GXAI predominantly exposed to movements in the equity securities of companies participating in the artificial-intelligence and technology ecosystem.

Sector and Geographic Exposure

Technology represented 68.52% of GXAI's sector allocation, below the 90.93% category figure shown in the supplied Morningstar comparison. Communication Services accounted for 13.89%, compared with 5.01% for the category, while Consumer Cyclical represented 9.69%, compared with 0.97%. Industrials contributed 6.98%, and Healthcare accounted for 0.66%.

Geographically, the United States represented 71.04% of the portfolio. China accounted for 7.57%, South Korea for 5.67%, Taiwan for 4.69%, Germany for 4.90%, Canada for 1.92%, Japan for 1.79%, Finland for 0.77%, and India and the Netherlands each represented 0.34%. The fund is unhedged for currency exposure, meaning non-Australian-dollar holdings can affect the fund through exchange-rate movements.

Major Holdings and Market-Capitalisation Mix

The supplied ASX snapshot lists Microsoft at 3.55%, Amazon at 3.39%, Alphabet at 3.27%, Oracle at 3.15% and Tencent at 3.11% among the largest holdings. Netflix represented 3.03%, Cisco Systems 3.00%, Samsung Electronics 2.91%, Palantir Technologies 2.91% and Broadcom 2.89%.

Large companies dominate the portfolio. Businesses with market capitalisations above $1 billion accounted for 94.99%, while the $500 million-to-$1 billion segment represented 2.40% and companies below $500 million represented 2.61%. The fund therefore has most of its exposure concentrated in established listed companies rather than smaller capitalisation businesses.

Fund Size, Costs and Distribution

The ASX data places GXAI's fund size at $270.55 million. Global X's official fund page reported Assets under management of approximately $249.37 million as of 17 July 2026, illustrating a difference between the two reported dates and measurement points.

The management fee is 0.57% per annum. The latest distribution information supplied by ASX records a final distribution of $0.804 per unit, with an ex-date of 2 July 2026, Record Date of 3 July and payment date of 16 July. The distribution amount was higher than the $0.212 figure shown for July 2025 in the supplied historical distribution data. Global X separately reports the July 2026 distribution at 80.455567 cents per unit.

Conclusion

Global X Artificial Intelligence ETF (ASX: GXAI) provides a diversified portfolio of 89 companies across the global artificial-intelligence and big-data ecosystem, while retaining a high allocation to technology stocks and large-cap businesses. Its portfolio is predominantly invested in equities, with the United States accounting for the largest geographic share. The fund size, unit count, management cost and distribution data provide measures of its structure and operating profile, while the differences between reporting dates highlight the importance of using the relevant date when comparing fund statistics.