The AI Efficient Frontier

AI Is Potentially Becoming A Structural Allocation, Not Simply A Thematic Investment

The increasing technological dominance of artificial intelligence over the past several years has begun to shift the investment conversation significantly. Instead of asking whether AI will transform the economy, investors now want to know how AI should fit within a diversified portfolio.

Artificial intelligence is evolving from a single technology trend into a foundational platform that is reshaping industries across the global economy. We believe Cloud computing, semiconductors, robotics, autonomous systems, digital assets, and intelligent software are converging into one vast innovation ecosystem. As that ecosystem expands, investors could benefit from thinking about AI not only as a source of growth, but also as a structural component of modern portfolio construction.

AI Is Moving From Prospect To Deployment

Cloud providers have continued to increase their AI infrastructure spending; enterprise adoption has accelerated across industries; and demand for AI chips and computing infrastructure has remained exceptionally strong. Companies are deploying AI to automate workflows, to improve productivity, to reduce costs, and to create entirely new products and services.

Those broad developments suggest that AI is moving beyond a single technology trend. Like electricity, the internet, or cloud computing before it, artificial intelligence increasingly functions as a general-purpose technology with applications across nearly every sector of the economy.

As a result, instead of asking whether AI represents an attractive investment theme, investors are getting the message that AI has likely become a foundational component of long-term equity portfolios.

We Believe Portfolio Construction Matters More Than Individual Stock Selection

While many investors evaluate AI investments based on the potential appreciation of individual companies—and company selection does certainly matter—portfolio construction may be equally important.

The objective of diversification has always been clear: combine investments with different return drivers to improve long-term, risk-adjusted returns.

Modern Portfolio Theory formalizes that practice through the concept of the “efficient frontier,” the combination of investments expected to generate the highest possible return for each level of portfolio risk.

As illustrated below, portfolios below the efficient frontier are inefficient because they deliver less return for similar or greater levels of risk. Portfolios positioned on the frontier represent a more optimal balance between risk and return.

Historically, diversification has focused primarily on geography, sectors, and market capitalization. Now, innovation itself appears to have become an additional dimension of diversification.

AI's Role in Portfolio Optimization

To evaluate AI's contribution to portfolio construction, we have updated our previous hypothetical portfolio analysis—Revisiting The Role Of Artificial Intelligence In Portfolio Optimization.

In the updated analysis, which considers data through June 30, 2026, we compare four global equity portfolios beginning in October 2014:

• A traditional 60% US,  a 30% international developed, and a 10% emerging market equity portfolio
• The same portfolio with a 5% allocation to AI
• The same portfolio with a 10% allocation to AI
• The same portfolio with a 15% allocation to AI

Artificial intelligence exposure was represented separately by either the ARK Next Generation Internet ETF (ARKW) or the ARK Autonomous Technology & Robotics ETF (ARKQ), while traditional equity allocations were represented by broad-market ETFs.

The charts show the structural dynamics of four model portfolios (inception September 30, 2014) — a Reference Portfolio lacking exposure to artificial intelligence, and three with increasing allocations to artificial intelligence.

For informational purposes only and should not be considered investment advice, or a recommendation to buy, sell or hold any particular security. Past performance does not guarantee future results. The Global Equity Portfolio scenarios shown are hypothetical and based on model portfolios constructed by ARK, and form the basis of the hypothetical performance calculations shown on the following slides. Each asset class is represented by an ETF as described below. The Reference Portfolio allocations were chosen based on what ARK believes would be a typical allocation in a global equity portfolio for most investors (60% Domestic Equity, 30% International Developed Markets Equity, and 10% Emerging Markets Equity), and the Index ETFs used to represent each asset class were chosen because they represent a broad investment across each asset class without a high concentration in what are considered innovation stocks. Each of the other model portfolios represent an incremental allocation to innovation stocks, as represented by the ARK Innovation ETF, with the remaining balance prorated among the initial asset classes based on the 60%-30%-10% allocation.

Source: ARK Investment Management LLC. As of June 30, 2026. Data Source: Bloomberg. Note following market representations: Domestic Equity: iShares Core S&P Total US Stock Market ETF (ITOT; Expense Ratio: 0.03%); International Equity (Ex US & Canada): iShares MSCI EAFE ETF (EFA; Expense Ratio: 0.32%); Emerging Markets: iShares MSCI Emerging Markets ETF (EEM; Expense Ratio: 0.70%); Artificial Intelligence (AI): ARK Next Generation Internet ETF (ARKW; Expense Ratio: 0.76%, Inception: September 30, 2014) or ARK Autonomous Tech & Robotics ETF (ARKQ; Expense Ratio: 0.75%, Inception: September 30, 2014).

ARK selected a single fund manager as the consistent brand to represent the broad US market, international developed markets, and emerging markets respectively so as not to imply ARK conducted due diligence among several or many fund managers. ARK selected Blackrock, and their brand iShares specifically because iShares is one of the largest, most respected, and most trusted passive ETF providers globally that historically offers low tracking error to target exposure, has low fees relative to the industry, and has high liquidity given their scale. This research and report is a hypothetical experiment conducted to understand if an artificial intelligence strategy, as represented by the ARK Next Generation Internet ETF (ARKW) or ARK Autonomous Tech & Robotics ETF (ARKQ), is value accretive in a total equity portfolio.

For informational purposes only and should not be considered investment advice, or a recommendation to buy, sell or hold any particular security. Past performance does not guarantee future results. The performance data quoted represents past performance and current returns may be lower or higher. The investment return and principal will fluctuate so that an investor's shares when redeemed may be worth more or less than the original cost. For the Fund's most recent month end performance, please visit www.ark-funds.com or call 212.426.7040. Returns for less than one year are not annualized. As stated in the ARK ETFs' current prospectuses, the expense ratio for ARKW is 0.76% and for ARKQ is 0.75%.

Extraordinary performance is attributable in part due to unusually favorable market conditions and may not be repeated or consistently achieved in the future.

For the most recent month end performance for ITOT, EEM, and EFA visit www.ishares.com or call 1-800-474-2737.

Additional information about fees and expense levels can be found in the ARK ETFs' prospectuses. Net asset value (“NAV”) returns are based on the dollar value of a single share of an ARK ETF, calculated using the value of the underlying assets of the ARK ETF minus its liabilities, divided by the number of shares outstanding. The NAV is typically calculated at 4:00 pm Eastern time. Market returns are based on the trade price at which shares are bought and sold on the exchange using the last share trade. Market performance does not represent the returns you would receive if you traded shares at other times. Total Return reflects reinvestment of distributions on ex-date for NAV returns and payment date for Market Price returns. The market price of ARK ETF shares may differ significantly from their NAV during periods of market volatility. ARK's actively managed ETFs are benchmark agnostic. Index performance provided as a general market indicator.

Source: ARK Investment Management LLC. Data Source: Bloomberg. Note following market representations: US Market: iShares Core S&P Total US Stock Market ETF (ITOT; Fee: 0.03%); International Developed Market (Ex US): iShares MSCI EAFE ETF (EFA; Fee: 0.32%); Emerging Markets: iShares MSCI Emerging Markets ETF (EEM; Fee: 0.70%); Artificial Intelligence (AI): ARK Next Generation Internet ETF (ARKW; Expense Ratio: 0.76%, Inception September 30, 2014) or ARK Autonomous Tech & Robotics ETF (ARKQ; Expense Ratio: 0.75%, Inception: September 30, 2014).

Of those data, we asked a simple question: could adding a dedicated AI allocation improve portfolio efficiency?

Our research suggests that it can.

AI Improved Historical Risk-Adjusted Returns

Using ARKW as the AI allocation, every incremental increase in AI exposure improved the hypothetical portfolio's historical return and Sharpe Ratio.

What is the Sharpe Ratio?

The Sharpe Ratio measures how much return an investor earns per unit of risk in their portfolio. A higher Sharpe Ratio indicates better risk-adjusted performance: investors are wringing the most reward from every unit of risk they take. In this way, the Sharpe Ratio complements the concept of the efficient frontier, which maps the highest possible return achievable for a given level of risk. Portfolios with higher Sharpe Ratios tend to lie closer to the efficient frontier, signaling that the investor is using diversification and allocation in the most efficient manner possible.

The unconstrained optimization allocated nearly 19% to AI while producing a 15% annualized return and the highest observed Sharpe Ratio of 0.75.

Note: Measurement of returns of a market against its risk (in this case, volatility). International Equity and Emerging Markets are calculated out of these optimal portfolios given their low participation in maximizing risk-adjusted returns relative to the other asset classes included in this table. Market representations: Domestic Equity: iShares Core S&P Total US Stock Market ETF (ITOT; Expense Ratio: 0.03%); International Equity (Ex US & Canada): iShares MSCI EAFE ETF (EFA; Expense Ratio: 0.32%); Emerging Markets: iShares MSCI Emerging Markets ETF (EEM; Expense Ratio: 0.70%); Artificial Intelligence (AI): ARK Next Generation Internet ETF (ARKW; Expense Ratio: 0.76%, Inception September 30, 2014). The performance used to represent each market asset class reflects the net asset value (NAV) performance of each ETF/fund for the time periods shown. This simulation, also known as an “efficient frontier,” is a set of theoretical portfolios expected to provide the highest returns at multiple levels of risk. The data under the efficient frontier in the chart represents portfolios comprised of a single ETF/fund. October 2014 to June 2026 was used since it is the longest available time horizon for common inception across each ETF.

Sources: ARK Investment Management LLC, 2025, based on data and calculation from PortfolioVisualizer.com, as of June 30, 2026. For informational purposes only and should not be considered investment advice or a recommendation to buy, sell, or hold any particular security or cryptocurrency. Past performance is not indicative of future results.

The results were similarly compelling using ARKQ.

Historical returns improved from 11.6% to 13.0% as AI allocations increased from 0% to 15%, while the optimized portfolio allocated nearly 25% to AI and achieved the strongest risk-adjusted performance in the analysis.

Note: Measurement of returns of a market against its risk (in this case, volatility). International Equity and Emerging Markets are calculated out of these optimal portfolios given their low participation in maximizing risk-adjusted returns relative to the other asset classes included in this table. Market representations: Domestic Equity: iShares Core S&P Total US Stock Market ETF (ITOT; Expense Ratio: 0.03%); International Equity (Ex US & Canada): iShares MSCI EAFE ETF (EFA; Expense Ratio: 0.32%); Emerging Markets: iShares MSCI Emerging Markets ETF (EEM; Expense Ratio: 0.70%); Artificial Intelligence (AI): ARK Autonomous Tech & Robotics ETF (ARKQ; Expense Ratio: 0.75%, Inception September 30, 2014). The performance used to represent each market asset class reflects the net asset value (NAV) performance of each ETF/fund for the time periods shown. This simulation, also known as an “efficient frontier,” is a set of theoretical portfolios expected to provide the highest returns at multiple levels of risk. The data under the efficient frontier in the chart represents portfolios comprised of a single ETF/fund. October 2014 to June 2026 was used since it is the longest available time horizon for common inception across each ETF.

Sources: ARK Investment Management LLC, 2025, based on data and calculation from PortfolioVisualizer.com, as of June 30, 2026. For informational purposes only and should not be considered investment advice or a recommendation to buy, sell, or hold any particular security or cryptocurrency. Past performance is not indicative of future results.

While these results are hypothetical and do not guarantee future outcomes, they do suggest that AI historically contributed more than incremental returns and improved the overall efficiency of diversified equity portfolios.

Why We Believe AI Improves Diversification

Many investors assume that adding AI simply increases exposure to large technology companies, but today's AI ecosystem extends far beyond software. ARKW provides exposure across cloud computing, digital wallets, cryptocurrencies, intelligent devices, neural networks, and internet infrastructure. ARKQ complements those exposures through robotics, industrial automation, autonomous transportation, advanced manufacturing, reusable rockets, battery technologies, and AI-enabled infrastructure.

Although artificial intelligence powers both strategies, each captures different parts of the innovation value chain.

That distinction matters, because different AI allocations introduce differentiated return drivers that have behaved differently than traditional global equity benchmarks that are dominated by vanilla exposure to large-cap technology companies.

In our view, that differentiation helps to explain why more fine-grained AI allocations have shifted portfolios closer to the efficient frontier.

We Believe AI Has Become Broader Than Technology

The convergence of innovation platforms could represent one of the defining investment themes of the coming decade.

Artificial intelligence increasingly intersects with robotics, autonomous transportation, semiconductor design, cloud infrastructure, precision medicine, digital finance, and energy systems. The companies driving these technologies are connected not only through technological innovation but also through shared economic drivers, including falling computing costs, accelerating productivity, and expanding demand for intelligent systems.

As we argued in ARK’s Big Ideas 2026 research report,¹ these converging platforms have the potential to reshape productivity growth while exerting downward pressure on costs across large segments of the economy.

For investors, this suggests that AI should be viewed less as a sector allocation and more as an investment platform with applications across nearly every major industry.

AI Bubble Concerns

Rapid investment and rising market enthusiasm have prompted understandable comparisons between today's AI boom and the dot-com bubble. The scale of the current buildout certainly is significant. Hyperscaler capital spending has climbed above $700 billion,² while information technology and communications capital expenditures as a share of Gross Domestic Product (GDP) have returned to levels last seen during the technology and telecom boom.

We believe that comparison is only part of the story.

Unlike the late 1990s, today's investment cycle is being accompanied by measurable improvements in the economic fundamentals. As shown in the chart below, the price-to-earnings ratios for major technology companies remain well below dot-com peaks, even as capital spending has accelerated.

Note: “Mag 6” includes Alphabet, Apple, Amazon, Meta, Microsoft, and Nvidia. Source: ARK Investment Management LLC, 2026, based on data from Bloomberg 2025a, Bloomberg 2025b, Bloomberg 2026, FRED 2025, and S&P 2025 as of January 6, 2026.³ In addition to those sources, certain information presented may be the result of ARK’s internal analyses, which draw on various additional sources of information. For informational purposes only and should not be considered investment advice or a recommendation to buy, sell, or hold any particular security. Past performance is not indicative of future results.

At the same time, commercial adoption continues to gain momentum. Anthropic's annualized revenue run rate reportedly increased from $9 billion to $47 billion in roughly six months,⁴ highlighting what we believe is rapidly expanding enterprise demand for AI.

The economics of AI also are improving rapidly. By some measures, the cost of using AI models has fallen by more than 99% over the past year, while requests processed through one of the largest AI model platforms increased 25-fold during 2025 and nearly 7-fold since mid-January, as shown below.  Together, these trends suggest that lower costs are driving broader adoption, increasing usage, and expanding commercial demand. In other words, investment is supported by fundamentals, not by empty speculation.

ARK Investment Management LLC, 2026, based on data from Artificial Analysis 2025a and OpenRouter 2026 as of August 1, 2026.⁵ For informational purposes only and should not be considered investment advice or a recommendation to buy, sell, or hold any particular security. Past performance is not indicative of future results.

In our view, comparisons to the dot-com bubble also overlook the crucial distinction between winners and losers. Periods of technological transformation inevitably create both winners and losers, and we do not expect every company associated with AI to succeed. Instead, we believe value creation will be uneven across the AI ecosystem, underscoring the importance of active research, disciplined valuation, and selective exposure to the companies that may be best positioned to benefit from AI's long-term adoption.

For long-term investors, the more important question is not whether every AI company will succeed, but whether artificial intelligence deserves a permanent place in a diversified equity portfolio in virtue of the likelihood that a meaningful set of companies will succeed. Our research suggests that the answer is yes. Over the past 12 years, portfolios with a dedicated AI allocation generated stronger returns than traditional global equity portfolios. They also improved risk-adjusted performance better than traditional global equity portfolios. Both data points support our case for AI as a long-term portfolio allocation.

Important Information

Neither ARKW nor ARKQ hold cryptocurrencies directly.

Investors should carefully consider the investment objectives and risks as well as charges and expenses of an ARK ETF before investing. This and other information are contained in the ARK ETFs’ prospectuses and summary prospectuses, which may be obtained by visiting www.ark-funds.com. The prospectus and summary prospectus should be read carefully before investing. 

Investing in securities involves risk and there's no guarantee of principal.

Fund Risks: The principal risks of investing in the ARKW include: Equity Securities Risk. The value of the equity securities the Fund holds may fall due to general market and economic conditions. Information Technology Sector Risk. The information technology sector includes companies engaged in internet software and services, technology hardware and storage peripherals, electronic equipment instruments and components, and semiconductors and semiconductor equipment. Information technology companies face intense competition, both domestically and internationally, which may have an adverse effect on profit margins. Information technology companies may have limited product lines, markets, financial resources or personnel. The products of information technology companies may face rapid product obsolescence due to technological developments and frequent new product introduction, unpredictable changes in growth rates and competition for the services of qualified personnel. Failure to introduce new products, develop and maintain a loyal customer base, or achieve general market acceptance for their products could have a material adverse effect on a company’s business. Companies in the information technology sector are heavily dependent on intellectual property and the loss of patent, copyright and trademark protections may adversely affect the profitability of these companies These companies may also be exposed to risks applicable to sectors other than the disruptive innovation theme for which they are chosen. Disruptive Innovation Risk. Companies that ARK believes are capitalizing on disruptive innovation and developing technologies to displace older technologies or create new markets may not in fact do so. Companies that initially develop a novel technology may not be able to capitalize on the technology. Companies that develop disruptive technologies may face political or legal attacks from competitors, industry groups or local and national governments. These companies may also be exposed to risks applicable to sectors other than the disruptive innovation theme for which they are chosen, and the securities issued by these companies may underperform the securities of other companies that are primarily focused on a particular theme. 

Cryptocurrency Risk. Cryptocurrency (notably, bitcoin), often referred to as ‘‘virtual currency’’ or ‘‘digital currency,’’ operates as a decentralized, peer-to-peer financial exchange and value storage that is used like money. The Fund may have exposure to bitcoin, a cryptocurrency, indirectly through an investment in the Bitcoin Investment Trust (‘‘GBTC’’), a privately offered, open-end investment vehicle. Cryptocurrency operates without central authority or banks and is not backed by any government. Even indirectly, cryptocurrencies may experience very high volatility and related investment vehicles like GBTC may be affected by such volatility. As a result of holding cryptocurrency, the Fund may also trade at a significant premium to NAV. Cryptocurrency is also not legal tender. Federal, state or foreign governments may restrict the use and exchange of cryptocurrency, and regulation in the U.S. is still developing. Cryptocurrency exchanges may stop operating or permanently shut down due to fraud, technical glitches, hackers or malware. Detailed information regarding the specific risks of ARKW ETF can be found in the prospectus. Additional risks of investing in ARKW include foreign securities, market, management and non-diversification risks, as well as fluctuations in market value and NAV. 

The Fund’s exposure to cryptocurrency may change over time and, accordingly, such exposure may not always be represented in the Fund’s portfolio. Many significant aspects of the U.S. federal income tax treatment of investments in bitcoin are uncertain and an investment in bitcoin may produce income that is not treated as qualifying income for purposes of the income test applicable to regulated investment companies, such as the Fund. GBTC is expected to be treated as a grantor trust for U.S. federal income tax purposes, and therefore an investment by the Fund in GBTC will generally be treated as a direct investment in bitcoin for such purposes. See ‘‘Taxes’’ in the Fund’s SAI for more information. 

The principal risks of investing in ARKQ: Equity Securities Risk. The value of the equity securities the Fund holds may fall due to general market and economic conditions. Foreign Securities Risk. Investments in the securities of foreign issuers involve risks beyond those associated with investments in U.S. securities. Consumer Discretionary Risk. Companies in this sector may be adversely impacted by changes in domestic/international economies, exchange/interest rates, social trends and consumer preferences." Information Technology Sector Risk. Companies may face rapid product obsolescence due to technological developments and frequent new product introduction, unpredictable changes in growth rates and competition for the services of qualified personnel. Detailed information regarding the specific risks of ARKQ ETF can be found in the prospectus. Industrials Sector Risk. Companies in the industrials sector may be adversely affected by changes in government regulation, world events and economic conditions. In addition, companies in the industrials sector may be adversely affected by environmental damages, product liability claims and exchange rates. Disruptive Innovation Risk. Companies that ARK believes are capitalizing on disruptive innovation and developing technologies to displace older technologies or create new markets may not in fact do so. Companies that initially develop a novel technology may not be able to capitalize on the technology. Companies that develop disruptive technologies may face political or legal attacks from competitors, industry groups or local and national governments. These companies may also be exposed to risks applicable to sectors other than the disruptive innovation theme for which they are chosen, and the securities issued by these companies may underperform the securities of other companies that are primarily focused on a particular theme. 

Additional risks of investing in ARKQ or ARKW include market, management and non-diversification risks, as well as fluctuations in market value and NAV. 

Shares of ARKW and ARKQ are bought and sold at market price (not NAV) and are not individually redeemed from the ETF. ETF shares may only be redeemed directly with the ETF at NAV by Authorized Participants, in very large creation units. There can be no guarantee that an active trading market for ETF shares will develop or be maintained, or that their listing will continue or remain unchanged. Buying or selling ETF shares on an exchange may require the payment of brokerage commissions and frequent trading may incur brokerage costs that detract significantly from investment returns

Portfolio holdings will change and should not be considered as investment advice or a recommendation to buy, sell or hold any particular security. Please visit www.ark-funds.com for the most current list of holdings for the ARK ETFs. 

Moore's Law is the observation and prediction that the number of transistors on an integrated circuit (microchip) doubles approximately every two years, leading to exponential growth in computing power and efficiency while costs decrease, a principle that has guided the semiconductor industry for decades, though it faces physical limits and is evolving. It's an empirical trend, not a physical law, first described by Intel co-founder Gordon Moore in 1965.

A hyperscaler is a large-scale cloud service provider, like Amazon Web Services (AWS), Microsoft Azure, or Google Cloud, that offers massive, highly scalable computing resources (compute, storage, networking) through vast data centers, enabling on-demand access to services for everything from AI and big data to basic internet, platforms and software.

The information herein is general in nature and should not be considered financial, legal or tax advice. An investor should consult a financial professional, an attorney or tax professional regarding the investor’s specific situation. Certain information was obtained from sources that ARK believes to be reliable; however, ARK does not guarantee the accuracy or completeness of any information obtained from any third party. 

ARK Investment Management LLC is the investment adviser to the ARK ETFs.

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