Learn to check what AI search says about your brokerage.
Develop a factual review process for services, locations and professional information in AI answers. Turn a confusing recommendation into a specific investigation.
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Separate identity, service and offer claims
An AI description can contain several kinds of information that require different checks. Identity claims concern the brokerage, adviser, location and licensing references. Service claims concern the work the brokerage actually handles. Offer claims include rates, fees, lender access or statements about likely approval. Break the response into these categories before deciding whether it is accurate. A correct address does not validate the rate or service statement beside it.
Build a current reference using approved public information and a named internal reviewer. Link each fact to the page or record that supports it. For variable information, record the effective date and who maintains it. Keep a separate category for statements you cannot verify, rather than treating them as true because they sound favorable. The review should give the brokerage a precise description of the issue and its source, not a vague score for how well AI understands the business.
Investigate a mismatch without inventing its cause
Save the question, answer, date and the links shown by the system. If the answer describes a former adviser as currently working for the brokerage, inspect the relevant biography and directory pages. If it quotes a rate, check whether a page under your control still displays that number and whether the answer omitted its context. The visible source may support only part of the description. Record what it actually says before asking anyone to change it.
A worked review might find an accurate brokerage name, an outdated office address and an unsupported claim that approvals are guaranteed. Those require separate actions: preserve the correct identity, update the address wherever it is wrong, and investigate the unsupported promise. Do not reproduce the promise in new promotional copy to try to correct it. If no source can be established, retain the observation and use an available feedback channel without alleging that a particular publisher caused the error.
Close the loop through reviewed changes and later observations
Turn each confirmed issue into a short change request: what is wrong, the correct public wording, the affected page or profile, the evidence and the owner. Prioritize information that could misdirect a borrower or misrepresent a service. Route professional claims through the brokerage's normal approval process. Correct the page text and associated metadata, including descriptions used for social previews, so outdated wording is removed from the material you control. Recheck search snippets separately after the changes are processed; search engines can generate their own descriptions, and updating a meta description does not guarantee immediate replacement.
Record the publication date and repeat the original scenario later. Report source correction and answer correction as separate events. An external platform may continue to surface older information or produce different wording, and the review cannot guarantee its future behavior. Keep unresolved findings visible with a next review date. This creates a manageable accuracy process that staff can maintain when advisers, offices, services or promotional information change.
Questions and answers
What should we do if AI quotes an old mortgage rate from our website?
Locate the exact source if it is shown, then check whether the old rate is still published on a page, downloadable document or summary that the brokerage controls. Have the responsible professional decide whether to update or remove it and ensure the surrounding conditions are accurate. Check related page descriptions and internal links so the old offer is not still promoted elsewhere. Save the original answer and the correction date, then observe again later. A corrected source does not guarantee an immediate change in every AI response. Avoid issuing a new rate statement solely to influence the answer unless it belongs to your normal reviewed publication process.
How should we handle an AI claim that we guarantee approval?
Treat it as a high-priority unsupported claim until it has been investigated. Save the exact statement, review the sources shown and search the brokerage's own public pages for language that might be read as a guarantee. Ask the brokerage's appropriate reviewer to approve any correction. If the claim originates in a directory or other external page, request a factual update with the relevant evidence. If no source is visible, use the platform's feedback process where available and retain the observation. Do not repeat the claim as a marketing benefit, and do not report the situation resolved merely because one later response omits it.
Who should own a brokerage's AI accuracy log?
A marketing or operations team member can maintain the log, capture observations and track corrections. A designated professional should confirm statements about the brokerage's role, service scope, qualifications, rates and other financial claims. Assign technical website updates to the person who can implement them and external-profile changes to the account owner. Every finding should have one accountable coordinator so it does not disappear between teams. Keep the log focused on public information; borrower applications are not needed. A simple record of claim, evidence, decision, owner and recheck date is more useful than a large dashboard with no clear correction process.
Is an unsupported claim the same as a false claim?
No. Unsupported means the review has not found enough evidence to establish the statement. False means it conflicts with a verified fact. Keep those labels separate. For example, a claimed service may be incorrect because the brokerage confirms it does not offer it, while a claimed award may remain unverified until someone checks the issuing organization. A missing citation does not automatically prove a statement false, and a citation does not automatically prove it true. The distinction helps staff choose the right action: confirm the fact, correct a source, request an external update or continue monitoring without making an accusation they cannot support.
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