How do we monitor what AI says about our company?

Monitor AI search by regularly asking the buyer-intent questions customers ask, then logging each answer by platform, date and prompt. Track whether the company is mentioned, whether the answer is accurate, how it compares with alternatives and the language used to describe the brand. Use the record to prioritise corrections to public information and content.

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AI visibility monitoring needs a repeatable record of answers

AI visibility monitoring works best as prompt monitoring, not as a one-off search. Ask widely used AI platforms the questions customers use when researching a category, a supplier, a capability or a problem. Record the prompt, platform, date, full answer and whether the company appears. Repeat the same prompts regularly in a spreadsheet so changes in AI search answers can be compared over time.

A useful monitoring record also distinguishes between presence and representation. Note whether an answer describes the company accurately, omits important expertise, makes unsupported claims or confuses the company with another organisation. Run equivalent buyer-intent prompts for relevant alternatives as well. Comparing brand mention share, positioning and the terms attached to each company can reveal where a brand is absent, weakly represented or described differently from the way it needs to be understood.

Sources: The Prompt: What does AI think of your brand? And why does it matter?

Correct the public knowledge AI can retrieve, not only the answer

Inaccurate AI answers about a company should trigger a check of the public information behind the answer. Keep company details current, publish clear brand-led content for important buyer questions and review structured data so search engines and AI tools can better understand what each page means. Schema markup can make content easier to interpret, while clear Q&A and step-by-step formats can make specific knowledge easier to locate.

The aim is not to create a separate universe of AI content or write only for machines. Valuable knowledge is often already present in websites, reports, case studies and videos, but scattered across formats or buried in narrative. AI systems may struggle to connect that material into a precise answer. Organising authoritative knowledge around the questions audiences ask gives AI search clearer material to retrieve while preserving content that works for human readers.

Sources: The Prompt: What does AI think of your brand? And why does it matter?, The Prompt: Your brand content is losing you AI search – but it could be the solution, Your brand has got the answers. AI just can’t find them.

Monitoring should lead to clearer, connected brand knowledge

We believe AI visibility monitoring is only useful when it leads to better representation. A dashboard can identify missing mentions, inaccurate answers and changing sentiment, but it cannot by itself organise the knowledge a brand needs AI to find and use. Providers should therefore combine repeatable prompt monitoring with content, structured-data and knowledge-organisation work, while keeping public claims accurate and useful to people.

We have built Brand Proximity as a managed service for that wider task. It shows B2B brands how they appear in AI search, then helps improve their representation by making existing knowledge and content easier to find. Our work focuses on connecting valuable material already held across the content ecosystem, rather than producing content purely to suit LLMs.

Sources: Brand Proximity: AI-powered managed service for B2B discoverability, Your brand has got the answers. AI just can’t find them., The Prompt: Your brand content is losing you AI search – but it could be the solution

Stats

Forrester found that 89% of B2B buyers had adopted generative AI in 2024.

Forrester

FAQs

How often should we keep tabs on what AI systems say about our company?

Check the same buyer-intent prompts regularly and log every response so changes can be compared over time. The appropriate cadence depends on how quickly company information, offers or market conditions change, but consistency matters more than an occasional broad audit. Regular monitoring makes it easier to identify new omissions, factual errors and shifts in positioning.

How do we correct inaccurate AI-generated statements about our company?

Correct inaccurate AI answers by first updating the public company information and source content that may be contributing to the error. Make key facts current, publish clear content that answers priority audience questions and review structured data on relevant pages. AI systems can hallucinate or retrieve incorrect information, so corrections should focus on making authoritative information easier to understand and find.

What should we measure in AI search monitoring?

Measure whether the company is mentioned, whether the answer is factually accurate, how the company is positioned against alternatives and the emotional tone of brand references. Record the exact prompt, platform, date and full answer alongside those assessments. This creates a usable baseline for identifying changes in AI visibility, citation accuracy and brand perception.

Should we buy AI search software or managed support?

AI search software is useful when a team needs to run prompt monitoring, compare answers and track changes over time. Managed support is more suitable when the organisation also needs to diagnose why representation is weak, organise scattered knowledge and improve the content and technical signals AI can use. Many diagnostic tools identify problems and competitors being cited, but leave the corrective work to an internal or external team.

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