Equities

AI ETFs

AI ETFs are exchange-traded funds linked to artificial intelligence either through what they invest in or how they invest. Some target companies developing or using AI, while others apply AI such as machine learning and NLP, as well as data-driven techniques, to support research, portfolio construction and decision-making within the investment process.

Understanding the different meanings of AI ETFs

Artificial intelligence is increasingly shaping business models, productivity and financial markets. In ETF investing, however, the term “AI ETFs” can mean more than one thing.

Some AI ETFs seek exposure to companies involved in artificial intelligence, such as semiconductor manufacturers, software platforms, cloud infrastructure providers or businesses applying AI across industries.

Other ETFs use AI, machine learning or natural language processing within the investment process itself. In this case, AI is not necessarily the theme being invested in. Instead, it is part of the research toolkit used to analyze data, identify patterns, detect emerging themes or support portfolio construction.

Robeco’s active ETF range is best understood in this second sense: as research-driven active ETFs that selectively use advanced quantitative techniques, including AI and machine learning, where they can add genuine value.

View active ETF range

What are AI ETFs?

AI ETFs are exchange-traded funds connected to artificial intelligence either through their investment exposure or their investment process.

Broadly, they fall into two categories:

AI thematic ETFs

These invest in companies linked to the development or application of artificial intelligence. This may include companies involved in chips, data centers, cloud infrastructure, software, automation or AI-enabled services.

AI-enhanced ETFs

These use AI-related techniques within the investment process. For example, machine learning can help analyze large datasets, while natural language processing can be used to detect emerging investment themes from company reports, earnings calls or media sources.

Understanding this distinction matters. An ETF may use AI without being an AI-themed portfolio, and an AI-themed ETF may invest in AI-related companies without using AI in its own investment process.

Robeco’s approach

Robeco combines long-standing quantitative research with targeted use of advanced techniques such as machine learning, NLP and alternative data.

Within our active ETF range, AI is used selectively and within a disciplined investment framework. It does not replace investment judgment, risk control or portfolio construction discipline. Rather, it can help expand the information set, identify more complex patterns and support more adaptive investment strategies.

Examples include strategies that use NLP to detect emerging themes across company reports, earnings calls and media sources, or machine learning techniques designed to identify deeper return patterns in broad, under-researched equity universes.

Why consider AI-enhanced active ETFs?

Artificial intelligence can be useful in investment strategies where the opportunity set is broad, data-rich and fast-changing. Used carefully, it can help investors move beyond traditional signals and analyze information that may be difficult to process using conventional methods alone.

Potential benefits include:

  • Broader information analysis

    AI and machine learning can process large and varied datasets, including textual data.

  • Earlier theme detection

    NLP can help identify emerging themes before they become fully mainstream.

  • Pattern recognition

    Machine learning can help detect complex relationships that traditional linear models may miss.

  • Disciplined implementation

    In an active ETF, these insights can be embedded in a transparent, liquid and rules-based investment framework.

Key considerations

AI is not a shortcut to better outcomes. Its usefulness depends on the quality of the data, the robustness of the models, the discipline of implementation and the strength of human oversight.

Investors should consider the risks carefully, including market risk, model risk, valuation sensitivity, concentration risk and the possibility that AI-related techniques may not perform as expected in all market environments.

Past performance is not a guarantee of future results. The value of investments can go down as well as up. Capital is at risk.

Explore Robeco’s active ETF range

Robeco’s active ETF range brings together quantitative research, portfolio construction discipline and selective innovation in areas such as enhanced indexing, dynamic themes, small caps, credit and climate-aware bond investing.

Explore our active ETF strategies or contact our team to learn more about how they may support portfolio construction.

See also

Emerging economies
What are emerging markets?
Artificial intelligence

More glossary terms

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