AI Visibility & Journey Check

Check how your brand shows up where buyers increasingly start: AI assistants, AI-enriched search and shopping agents. Ask the tools yourself, trace what they cite, and fix what you can reach.

Consulting practice, marked as such: McKinsey's State of the Consumer survey (2026: a growing share of consumers use generative AI in shopping, and brands' own sites are a small part of the sources AI models cite; not checked against the original here) and BCG's CMO work on agentic AI (2026: AI tools rank among the most influential touchpoints for the consumers who use them, and agents judge brands on observable performance). The firms have an interest in the topic and the numbers move; treat direction, not digits, as the finding.

Use it when:

• Your marketing assumes buyers find you by searching, and you suspect that is changing.
• You sell a product or service people compare before buying, and you have never asked an AI assistant about yourself.
• You are about to launch a chatbot or agent on your own site.

Skip it when:

• You have no clear brand assets or buying situations yet: start with 6.20 Brand Building Basics.
• You want to map the whole customer journey, not only the AI part: use 6.3 Customer Journeys Map.

The working claim: more discovery, comparison and checking is handed to AI assistants and agents, and those systems build answers largely from third-party and structured sources rather than from your own site, so the place that decides whether you are found has moved outside your channels (McKinsey, 2026). A second claim follows for buyers who already use these tools: the AI layer ranks among their most influential touchpoints, and agents judge brands on observable performance, meaning specifications, prices, policies and reviews, not taglines (BCG, 2026).

Both claims are consulting practice: surveys with a stated method but an interest in the conclusion, in a field so new that numbers change between reports. The mechanism underneath is older than AI: intermediaries that summarize you from what others say reward brands whose facts are accurate, easy to find and confirmed by third parties. The check is therefore primary research you can run in an afternoon: the actual answers and the sources they cite.

Ask in a fresh session, phrased as a customer would, using only public information. Record the answers in your own notes, not here, if they contain personal data.

Strong answer: a row with the claim and its source: "Asked 'best induction pans': not mentioned; competitor recommended, citing a comparison site. Asked about us directly: repeats a withdrawn oven-safety claim from a 2022 blog review." Not: "AI says some things about us."

Why third parties decide this: answers draw heavily on reviews, comparison sites, forums, press and structured data, and little on your own site (consulting practice, McKinsey, 2026). Your reputation surface is the input.

Illustrative example: the company is made up.

A kitchenware brand from Småland runs Section 1 and finds it absent from "best induction pans" answers, while a competitor is recommended with a citation to a comparison site the brand never engaged with. One answer repeats a withdrawn claim about oven safety, citing a 2022 blog review. Fixes: the product data feed gets corrected temperatures and materials; the brand sends updated test samples to the two most-cited comparison sites; the FAQ is rewritten to answer category questions in quotable sentences; and the author of the stale review is asked for a correction. At the rerun the brand appears in two of three answers. The gain came from third-party surfaces, not from the brand's own site.