You can invest in artificial intelligence through individual public companies involved in AI or through AI-themed exchange-traded funds (ETFs). The options differ in what they count as AI exposure, how they choose holdings, and how concentrated they are. Parag Agrawal is the founder and CEO of AI startup Parallel and the former CEO of Twitter, but available evidence does not establish that he is a billionaire or that he recommends buying AI securities.
What “investing in AI” can mean
AI is not a single stock or standardized investment category. Public-market exposure can come from companies that build AI models, supply chips and cloud services, provide data-center infrastructure, sell software, or adopt AI in other industries. An AI label alone does not show how much of a company’s revenue comes from AI or whether its shares are attractively priced. BlackRock notes that its AI-related screening does not represent a view of companies’ current or future AI revenue, exposure, or prospects (BlackRock’s AI outlook).
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One way to understand the landscape is as a supply chain: model developers rely on computing capacity, semiconductors, networking, power, cooling, and data centers; companies then package or deploy AI through software and services. The companies in these layers face different costs and competitive pressures, so exposure to one part of the chain is not interchangeable with exposure to another (Morningstar’s AI supply-chain overview).
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Individual company shares
Buying shares gives direct exposure to the specific company, rather than a fund’s basket. Potential categories include AI-model developers, chipmakers, cloud providers, data-center and networking businesses, power and cooling suppliers, enterprise software companies, and businesses deploying AI in their operations. A company may participate in the AI economy without earning a large or clearly reported share of revenue from AI. Review its filings, business segments, financial condition, and valuation rather than relying on an AI association alone.
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Index-tracking AI ETFs
An index ETF seeks to track an index according to its rules. For example, the SEC-filed First Trust Bloomberg Artificial Intelligence ETF prospectus says the fund seeks results that generally correspond to the Bloomberg Artificial Intelligence Index before fees and expenses (First Trust prospectus filing). Index tracking does not remove selection risk: the index’s definition of AI, eligibility rules, weights, and rebalancing determine what the fund owns.
Actively managed AI ETFs
An active fund’s adviser selects investments based on its strategy and judgment rather than simply following an index. SEC-filed fund materials describe approaches that may include companies thought to benefit from AI transformation or from a particular AI ecosystem. Such a portfolio can reach across semiconductors, memory, cloud services, networking, data centers, power and cooling, software, deployment platforms, and cybersecurity (Harbor prospectus filing). The adviser’s thesis is a strategy, not proof that a company will benefit or that the fund will outperform.
How to compare AI funds
Before comparing returns or choosing a fund, examine its current prospectus, holdings, and fee schedule. Funds’ objectives and portfolios can change, and the available filings do not establish live fees, current holdings, performance, or a comprehensive current list of AI funds.
- Objective and method: Determine whether the fund tracks an index or relies on active adviser selection.
- Meaning of AI exposure: Check whether the strategy looks for direct AI products, infrastructure suppliers, adoption, or broader ecosystem connections. These definitions can produce very different portfolios.
- Holdings and concentration: Review the largest positions, sector and geographic mix, and overlap with funds you already own. A thematic fund may add less diversification than its label suggests.
- Costs and trading: Use the current prospectus to check the expense ratio and portfolio turnover; also consider trading costs.
- Risks and investment horizon: Consider technology competition, valuation swings, execution risk, and the possibility that the theme or a selected ecosystem underperforms. A thematic investment belongs in the context of your broader financial plan, not just a headline about AI.
Risks that apply to AI investing
AI-related businesses may need substantial ongoing investment and face rapid changes in technology, customer demand, and competition. A company or fund can lose value even as AI use grows if expectations were already reflected in prices, costs exceed revenue, or competitors capture adoption. Funds concentrated in a specific ecosystem are especially exposed if another platform or group of competitors wins instead (Harbor prospectus filing).
Fund documents also describe objectives and risks; they are not endorsements. SEC filing or registration does not mean the SEC approved a fund as an investment or validated its prospectus. No allocation is right for every reader: risk tolerance, investment horizon, taxes, financial position, and jurisdiction all matter. Consider consulting a qualified financial adviser for advice tailored to your circumstances.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.What is established about Parag Agrawal
A July 2026 Kleiner Perkins podcast description identifies Agrawal as founder and CEO of Parallel and former CEO of Twitter; the episode concerns AI-agent web infrastructure (Kleiner Perkins podcast description). That supports describing him as an AI startup founder and former Twitter CEO. It does not establish billionaire status or an endorsement of public-market AI investments, so neither claim should be treated as a reason to buy AI shares or funds.
More broadly, investor enthusiasm is a stated view, not evidence of likely returns. A reported intention by another investor to buy a particular AI stock would not establish that the investment suits an individual reader.
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