Investment Management Enters the Autonomous Era

New York, USA, August 17th, 2026, FinanceWire

The global exchange-traded fund industry now manages nearly $20 trillion in assets [source]. Over the past three decades, ETFs have fundamentally changed how investors access financial markets. Yet while the investment vehicle evolved dramatically, one element of investment management remained remarkably consistent: the final investment decision was still made by a human portfolio manager.

Active investing continued to rely on human portfolio managers. Passive investing relied on predefined rules. Technology improved research, execution and risk management, but the final investment decision remained overwhelmingly human.

Artificial intelligence may now be changing that.

Earlier this year, FINQ launched the first SEC-registered[1] ETFs managed entirely by an autonomous artificial intelligence investment system. Rather than supporting a portfolio manager with research or recommendations, the AI itself continuously evaluates, ranks and constructs portfolios according to its investment methodology, while humans remain responsible for governance, oversight and regulatory compliance.

The distinction may appear subtle, but it represents a fundamentally different approach to investment management. This is not AI-assisted investing. It is AI-managed investing.

Whether autonomous investment management ultimately becomes a lasting category will not be determined by five months of performance. Long-term consistency across multiple market cycles will matter far more than any early returns.

However, the first months of live trading offer something equally important: the first opportunity to observe how an autonomous investment manager behaves in public markets.

From Theory to Live Markets

Artificial intelligence has been used across financial markets for years.

Investment firms employ machine learning to screen securities, identify patterns, estimate risks and support research teams. In nearly every case, however, the technology serves as an input into a human decision-making process.

The portfolio manager still decides what to buy, what to sell and when to rebalance.

Autonomous investment management shifts the investment decision-making process to the system itself, while responsibility for the investment strategy, oversight and regulatory compliance remains with the investment adviser.

Each trading day, the AI framework analyzes thousands of data points spanning company fundamentals, market behavior, technical signals, institutional activity and market sentiment. Every company within its investment universe receives an updated ranking. Portfolio changes occur when the system identifies opportunities that rank more favorably according to its methodology.

The process is continuous, systematic and adaptive rather than discretionary.

Unlike traditional quantitative strategies, the system is designed to continuously adapt as new information emerges rather than follow a static set of predefined investment rules. The objective is not to predict markets, but to systematically reassess relative opportunities as conditions evolve.

The First Months in Public Markets

Since launching on February 5, 2026, FINQ's two AI-managed ETFs, AIUP, FINQ FIRST U.S. Large Cap AI-managed U.S. Equity ETF and AINT, FINQ DOLLAR NEUTRAL U.S. Large Cap AI-managed U.S. Equity ETF have completed their first months operating in live public markets. Through June 30, 2026:

ETF

Market Price return since inception

AINT

19.23%

AIUP

13.83%

S&P 500

8.51%

The performance data quoted represents past performance and is not guarantee of future results. Investment return and principal value of an investment will fluctuate so that an investor’s shares, when redeemed, may be worth more or less than their original cost. Current performance may be lower or higher than the performance data quoted. For the most recent month end and standardized performance, please visit our website at https://finqai.com/etfs/AINT or https://finqai.com/etfs/AIUP.

Naturally, a five-month track record is far too short to draw conclusions about the long-term merits of any investment strategy. History offers countless examples of approaches that outperformed over short periods before struggling under different market conditions.

Autonomous investment management should be held to the same standard. Its long-term value, if any, will ultimately be determined by its ability to navigate multiple market environments over many years rather than a single favorable period.

That said, these first months provide something the industry has never had before: the first live dataset showing how a fully autonomous investment manager behaves in public markets.

Continuous Adaptation Rather than Static Portfolios

Performance tells only part of the story. The more interesting observation is how the system made decisions as market conditions evolved.

Earlier this year, the AI identified opportunities in software companies such as ServiceNow and Datadog, at a time when many investors questioned the outlook for the sector. As those positions appreciated and their relative attractiveness changed, the system reallocated capital toward companies that ranked more favorably under its methodology, including Expand Energy and T-Mobile.

For more detailed information about AIUP and AINT, including current holdings and risks, please visit finqai.com/etfs/AIUP and finqai.com/etfs/AINT. Holdings are subject to change.

Rather than attempting to predict market tops or bottoms, the system continuously reallocates capital toward companies it identifies as offering the strongest relative opportunity at any given time.

Every position effectively competes for its place in the portfolio every day.

This dynamic ranking process differs both from traditional buy-and-hold investing and from discretionary portfolio management, where investment decisions may be influenced by conviction, experience or behavioural biases.

Whether individual investment decisions ultimately prove successful is less important than the process itself. Every holding is continuously challenged by new information, and no company remains in the portfolio simply because it performed well in the past.

These examples are not representative of all portfolio decisions and should not be viewed as a recommendation or an indication of future results. Past performance doesn’t guarantee future results. Investing involves risk, including loss of principal.

These examples are provided solely to illustrate how the AI model’s ranking and portfolio rotation process operated in specific historical instances. They are not representative of all portfolio decisions, should not be viewed as recommendations regarding any security, and should not be interpreted as an indication of future results.

A New Category, Not Simply a New Product

The introduction of autonomous investment management raises broader questions than the performance of any single ETF.

For decades, investors have largely chosen between two approaches.

Passive investing follows predefined rules designed to replicate an index.

Active investing relies on human judgement to outperform one.

AI-managed investing introduces a third model.

Rather than tracking an index or relying on discretionary decision-making, autonomous systems continuously evaluate changing information and adjust portfolios according to a systematic, adaptive investment framework.

Whether this approach ultimately becomes a meaningful category remains uncertain. Investors, regulators and the broader industry will rightly demand evidence across different market environments before drawing conclusions about its long-term role.

The questions extend well beyond performance.

How should autonomous investment systems be evaluated?

What level of transparency should investors expect?

How should governance evolve when investment decisions are made by adaptive software rather than individuals?

What constitutes a successful long-term track record for an AI-managed strategy?

These questions cannot yet be fully answered.

But they can now be observed.

For the first time, investors have the opportunity to evaluate autonomous investment management not as a research project or theoretical possibility, but as a live investment strategy operating within the same regulatory framework, transparency standards and daily scrutiny as any other publicly traded ETF.

For more than half a century, innovation in investment management has largely focused on building better tools for portfolio managers.

Autonomous investing suggests a different trajectory: the possibility that software itself becomes the investment manager.

Whether that proves to be the next major evolution of asset management remains to be seen. Five months of live trading do not answer that question.

They do, however, mark the moment the question became real.

Important Information

Before investing you should carefully consider the Fund's investment objectives, risks, charges and expenses. This and other information is in the prospectus, a copy of which can be obtained by visiting finqai.com. Please read the prospectus or summary prospectus carefully before you invest.

https://finqai.com/first-sec-registered

Investing involves risk. Principal loss is possible.

Distributed by Foreside Fund Services, LLC. [1]

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