Do investors and analysts actually use AI to research companies

Yes. Investors, sell-side analysts, partners, journalists, and acquirers increasingly use AI platforms to form a first understanding of a company before any direct contact. In a 2024 CFA Institute survey, 16% of respondents reported using generative AI for industry and company analysis, and adoption has climbed since. That synthesized answer becomes the prior that frames every later interaction, including your earnings call.

What is pre-engagement discovery

Pre-engagement discovery is the research a stakeholder does before reaching out, now often a question typed into ChatGPT, Perplexity, or Google AI Overviews. It happens in a place your traffic reports and media monitoring cannot see, and it shapes the shortlist of credible companies before you know you're being evaluated.

Can what AI says influence an investment or partnership decision

It can shape the starting assumptions. If AI presents an outdated strategy, a stale pipeline stage, or an unfavorable peer comparison, the stakeholder arrives already anchored to it, and you spend the conversation correcting rather than advancing.

How do I see what AI is telling investors before my next earnings call

Run the questions an investor or analyst would ask across the major AI platforms and compare the answers to your intended narrative. A Narrative Drift Scan does this systematically and flags material divergences ahead of a sensitive window.

Why is a quiet period the riskiest window for AI narrative drift

Because the model still answers even when you cannot. With no new authoritative disclosure to weight, AI anchors to the last thing said about you, which may be a superseded guidance range or a competitor's comparative framing. The drift compounds silently for the length of the blackout, and you inherit the full correction backlog the moment it lifts.

How often should an IR team check what AI says about the company

At minimum before every event that changes the correct answer: earnings, guidance updates, leadership changes, readouts, and transactions. Between those events a quarterly recheck is enough for most issuers, because AI descriptions age gradually as sources go stale rather than flipping overnight.

Narrative Intelligence

Your Investors Are Asking AI About You Before the Earnings Call

July 3, 2026•5 min read•Michael Etheredge, VP of Product Development

Michael Etheredge is VP of Product Development at QuestionFuel, where he leads how the firm measures and corrects the way AI answer engines describe companies. He was featured by the Southern Economic Development Council on how AI is changing the way companies research communities and regions.

Investors, analysts, partners, and acquirers increasingly form their first impression of your company from an AI answer, assembled in seconds, delivered before any direct contact, and invisible to your traffic and monitoring tools. By the time they reach your earnings call, that AI-shaped prior is already set.

The reliance is now measurable. When ChatGPT goes down, investor trading volume drops, especially for firms with recent news. The question for IR is no longer whether stakeholders are using AI to research you. It's what AI is telling them, and whether it matches the story you intend to tell.

Key takeaways

Investors, analysts, and acquirers increasingly form their first impression of a company from an AI answer, before any direct contact.
That impression sets the prior your earnings call either confirms or has to fight.
The reliance is measurable: trading volume drops during ChatGPT outages, especially for firms with recent news.
Quiet periods are the highest risk window, because AI anchors to whatever was last said when you can least correct it.
Treat AI's current description of your company as a disclosure input and check it before earnings, readouts, or raises.

Quick answer: Investors, analysts, partners, and acquirers now routinely form their first impression of a company from an AI generated answer, weeks before any direct contact. Research on ChatGPT outages in 2025 found investor trading volume fell while the tool was down, particularly for firms with recent news. By the time a stakeholder reaches your earnings call, the AI shaped prior is already set, which makes checking what AI currently says about you a disclosure input rather than a marketing task.

Why does the invisible research phase matter for IR?

Here is the part of the investor research cycle most IR programs have not caught up with. Before an analyst initiates coverage, before an investor takes a meeting, before an acquirer opens diligence, they have already formed an impression of your company. Increasingly, that impression is assembled by an AI platform synthesizing the public record in seconds, and it forms in a place your tracking and monitoring tools cannot reach.

The reliance is now measurable. Researchers studying ChatGPT service outages in 2025 found that investor trading volume dropped noticeably while the tool was down, particularly for firms with recent news, which is direct evidence that investors lean on generative AI to process information about specific companies. By the time a stakeholder reaches your earnings call or your data room, the AI shaped prior is already in place. The call does not create the first impression. It either confirms or fights one that was set weeks earlier.

Why can't IR measurement see this phase?

Traditional IR measurement is built around the visible phase: who attended, who covered, what traffic moved. The decisive phase now happens earlier and quieter, in a question asked of a model, answered with a confident synthesis, leaving no public trace. If that synthesis is accurate, it works in your favor. If it has drifted, you are starting every conversation a step behind, and you may never learn why.

Why do quiet periods make this worse?

The windows when you communicate least, including quiet periods, pre readout stretches, and transaction blackouts, are exactly when AI's description of you ages fastest and matters most. With no fresh authoritative signal, the model anchors to whatever was last said: an old guidance range, a superseded strategy, a competitor's framing. The perception gap opens precisely when you have the least ability to see or correct it.

What should IR do before the next call?

Treat AI's current description of your company as a disclosure input, not an afterthought. Before an earnings call, readout, or raise, establish what the major platforms are saying, where it diverges from your intended narrative, and which sources are driving the divergence. That is the function of a Narrative Drift Scan, which shows you what the market is already hearing while you still have time to act. For the full picture of how AI assembles that description, see our pillar on the five signals that decide how AI describes your company. You can also see how AI currently describes your company with an AI visibility snapshot.