Background

The intended thing to measure is not merely whether an investing app has many users, but whether a large number of consumers are actively using an AI agent for investing-related workflows. Because product-level “agent users” may not be fully disclosed, this question uses public evidence that specifically ties active users to an AI investing-agent feature or product.

Resolution Criteria

This question resolves YES if, on or before 2027-12-31, there is public evidence that at least 1 million users in a single calendar month actively used a consumer-facing AI investing agent.

For resolution purposes, an “AI investing agent” must satisfy all of the following:

• It is consumer-facing rather than advisor-only or institutional-only.

• It is primarily used for investing, trading, portfolio management, wealth management, or investment research.

• AI or agentic interaction is a central product experience rather than an incidental feature.

• It can perform at least one personalized, investment-related workflow such as portfolio analysis, security or fund research, trade idea generation, allocation suggestions, risk analysis, watchlist construction, tax-aware analysis, or execution assistance.

The 1 million-user threshold may be established by any of the following forms of public evidence:

1. A company disclosure that the AI investing agent, AI investing feature, or AI investing product had at least 1 million monthly active users.

2. An earnings call, investor presentation, regulatory filing, or executive statement giving an equivalent monthly active usage figure.

3. A credible third-party analytics estimate showing at least 1 million monthly active users for a standalone AI investing product whose core user experience is agentic.

4. A public company disclosure that allows the number to be directly inferred, such as reporting both total MAUs and the percentage of MAUs using the named AI investing agent, if the product of those figures is at least 1 million.

Examples of products or features that could qualify include named consumer AI investing agents launched by brokerages, fintech platforms, or AI-native finance products, provided the public evidence is specific enough to establish active AI-agent usage rather than general app usage.

Public-Data Rule

General app MAUs do not count unless the public source specifically indicates usage of the AI investing agent or AI investing feature.

For example:

• “Brokerage App X has 10 million MAUs” is insufficient.

• “Brokerage App X says 15% of MAUs used its AI investing assistant this month” counts if 15% of app MAUs is at least 1 million.

• “Product Y, an AI investing assistant, has 1.2 million MAUs” counts if the product’s core use case is investing-agent interaction.

• “Company Z has 1 million users and recently launched an AI investing assistant” is insufficient unless active use of the assistant itself is established.

Fine Print

The following do NOT count:

• Generic LLM products with incidental investing usage;

• General brokerage, fintech, or trading-app MAUs without AI-agent usage disclosure;

• Traditional robo-advisors lacking AI-agent or conversational functionality;

• Institutional-only systems;

• Internal advisor tooling;

• Non-investing finance assistants;

• Waitlist signups, downloads, registered accounts, cumulative users, or page views;

• Marketing claims such as “millions of investors can access the assistant” unless actual active usage is reported.

• If a product has both general app usage and a named AI investing agent, only active usage of the AI investing agent counts. If multiple public sources conflict, company disclosures and regulatory filings take precedence over third-party estimates.