California Leads an AI Investing Index, but the Sample Matters

Investing.com has published a state-level view of AI-related investment research among its U.S. audience, placing California first, with Ohio and Colorado tied in second place. Florida and Texas complete the top five, while New York ranks 13th.

The headline finding is less about a definitive map of American investor behaviour than about a more specific and useful question: where are Investing.com users most actively engaging with the platform’s AI research assistant and AI-focused stock content?

That distinction matters. The index offers a timely example of the value of first-party behavioural data, but also of the care required when turning platform activity into a broader market narrative.

What the index actually measures

The Investing.com analysis covers anonymised and aggregated user activity between 1 September 2025 and 31 August 2026. It combines two measures: interactions with WarrenAI, the company’s AI-powered market-research assistant, and views of content relating to AI-focused stocks.

Both measures were normalised per 1,000 unique Investing.com users in each state, converted into percentile scores and given equal weight. Only states with at least 10,000 unique Investing.com users were eligible; 37 states made the final ranking.

On that basis, California’s lead reflects consistently high engagement across both components. Florida recorded the highest rate of WarrenAI interactions, at about 451 per 1,000 Investing.com users. Pennsylvania, meanwhile, led in engagement with AI-stock content, at roughly 6.83 page views per 1,000 users.

The ranking captures behaviour within one financial-information platform, rather than AI adoption across each state’s investing population.

This is not a minor methodological footnote. It sets the proper boundary for interpreting the result. A state’s position may reflect who chooses to use the platform, the kinds of investing information they seek there, and how the platform presents its tools and content. It cannot, by itself, establish that investors in that state are more likely than others to use AI generally.

A useful split between researching with AI and investing in AI

The index’s two components point to an important difference that can disappear in headline discussion of “AI investing”. Using an AI tool to investigate a company, a chart or an economic event is not the same behaviour as researching companies associated with AI.

Florida’s strong showing on WarrenAI use and Pennsylvania’s lead on AI-stock content suggest that investors may be adopting the technology in different ways. One group may be using conversational tools to make research quicker or more accessible; another may be focused on a thematic investment proposition.

For financial platforms, this is a practical segmentation question. Usage data should distinguish between tool adoption, subject-matter interest and any subsequent investment action. Combining them can create a compelling index, but it can also obscure the customer need being served.

The wider evidence on AI and financial guidance is similarly sensitive to definitions and samples. A Gallup study, published in August 2026, found that 18% of U.S. adults who had sought financial guidance in the previous year had used an AI tool. That is not directly comparable with Investing.com’s index, which is based on activity within a self-selecting platform audience, but it underlines why adoption figures need their population and question wording made clear.

Better access does not remove the need for judgement

Investing.com’s findings support the view that AI-assisted research is reaching well beyond the traditional centres of technology and finance. Its data puts Utah, Hawaii, Michigan and Minnesota in the top 10, while New York and New Jersey sit outside it.

For product teams, that geographic spread is commercially relevant. Investors do not need to live close to a financial district to access market data, company filings, news and analytical tools. The competitive task is increasingly about making those inputs understandable, traceable and useful at the moment a user is deciding what to investigate next.

But research assistance should not be confused with personalised advice. The SEC’s investor education site warns that AI-generated information can be inaccurate or fabricated, and advises investors to validate underlying sources and use more than one source before making decisions. Its warning is particularly relevant where a fluent interface can make incomplete evidence feel settled.

That creates a clear design standard for providers of AI-enabled financial research. They should show the source material behind an answer, distinguish facts from interpretation, explain relevant limitations and avoid presenting a probabilistic output as a recommendation. Where a tool has commercial affiliations, limited coverage or material assumptions, those constraints need to be visible rather than buried.

The research lesson for platforms

The strongest contribution of Investing.com’s index may be methodological rather than geographical. It demonstrates how a business can turn product telemetry into a readable public insight, while publishing enough detail for readers to understand what the measure includes.

There is still room to go further. An index of this kind could become more decision-useful with longitudinal results, clearer evidence of how use differs by task, and additional indicators of whether users verify AI-generated outputs. Those additions would help separate curiosity, repeat use and informed decision-making.

For now, the ranking is best read as evidence of where AI-related engagement is concentrated within a sizeable investing platform’s U.S. customer base. That is a meaningful signal for a financial-information business. It is not a census of American investors — and it should not be used as one.

---

This article is based on a supplied announcement. It has been edited by Expert View Media for clarity, context and length.