What is a good consensus score?

A score above 80 means AI models largely agree about your brand and present consistent information. Scores between 50-80 indicate some deviations that should be addressed. Below 50 means significant inconsistencies that actively damage the brand experience.

How often do AI models change their answers?

AI models are updated continuously. Major updates typically happen monthly, but smaller adjustments can happen daily. Therefore we recommend weekly testing to catch changes quickly. Some changes are positive (the model learns about you), others negative (the model forgets or misrepresents).

Can I influence what AI models say about me?

Yes, but indirectly. AI models pull information from the web, so by optimizing your content — authoritative sources, consistent information across platforms and structured data as a supporting signal — you increase the probability that models present correct information about you.

Does this work for personal brands?

Absolutely. Personal brands are especially vulnerable to AI misinformation because there are fewer authoritative sources. AI Consensus helps you identify and correct errors before they affect your career or business.

AI & Searchscout

AI Consensus

What it does

Compares answers from multiple AI models on identical questions to calculate a consensus score — reveals misinformation, missing visibility and inconsistencies that affect how users perceive your brand through AI search.

Each AI model tells a slightly different story about you — and you have no idea which version users get

When a potential customer asks ChatGPT, Gemini or Perplexity about your industry, they get a direct answer. But these answers are rarely identical. One model may recommend you as a market leader, another may ignore you completely, and a third may present outdated information. This inconsistency means your brand experience is random — depending on which AI model the user happens to use.

Random brand experience — users get different information about you depending on which AI they ask, creating confusion and weakening trust
Undetected misinformation — an AI model can spread wrong facts about your products without you knowing, because you only check one platform
Competitor advantage — if competitors have higher consensus than you, it means AI models consistently recommend them over you across platforms
No baseline — without measuring consensus you do not know if your content changes actually improve AI visibility or just affect one model

Get a quantified consensus score showing exactly how much AI models agree about you — and where deviations lie

AI Consensus sends identical questions to all major AI models and analyzes answers to calculate a consensus score from 0 to 100. High score means models agree and present consistent information. Low score means deviations that need to be addressed. You get a detailed report showing exactly where deviations lie and what you can do to increase consensus.

Consensus score: a single number from 0-100 summarizing how much AI models agree about your brand — easy to understand and track over time
Deviation report: identifies exactly which models deviate and on which questions — so you can prioritize fixes where it matters most
Fact check: compares AI answers with your actual information and flags errors — outdated prices, wrong product names, missing services
Trend tracking: run tests weekly and see how the consensus score changes over time — verify that optimization work gives results

Features

Automatic testing: set up weekly automatic tests so you get alerts when the consensus score drops — catch problems before they affect traffic
Industry benchmark: compare your consensus score with industry average and competitors — understand if you are ahead or behind
Question templates: pre-made question sets for different industries so you test the questions that actually matter for your audience
Action recommendations: for each deviation you get concrete recommendations for how to increase consensus — from content changes to schema markup updates

How it works

Select questions from templates or write your own — the tool sends them to GPT-4, Claude, Gemini and Perplexity and collects answers
Get a consensus score with detailed deviation report showing where models agree and disagree — including fact check against your actual information
Use recommendations to optimize content and technical foundation — rerun the test to verify that the consensus score increases

Use cases

Brand managers — monitor brand representation across AI platforms and react quickly when misinformation is discovered
PR teams — identify and correct inaccurate AI answers before they spread to journalists and influencers who use AI for research
SEO teams — measure the effect of content optimization on AI visibility with a concrete, trackable KPI instead of subjective assessments

Why use AI Consensus?

Consensus is the new trust. In a world where users ask AI before they ask Google, it is not enough to be visible — you must be consistently visible. If ChatGPT recommends you but Gemini ignores you, you lose half of AI search traffic. AI Consensus gives you the numbers you need to ensure broad, consistent visibility.

Misinformation spreads fast. When one AI model presents wrong information about you, it can affect other models over time because they learn from overlapping sources. AI Consensus catches these errors early so you can correct them before they become the "truth" in the AI ecosystem.

Measurable ROI on AI optimization. The consensus score gives you a concrete KPI you can report to management or clients. Instead of vague statements like "we are working on AI visibility" you can say "the consensus score increased from 62 to 84 this month" — that is a language decision-makers understand.

FAQ

What is a good consensus score?: A score above 80 means AI models largely agree about your brand and present consistent information. Scores between 50-80 indicate some deviations that should be addressed. Below 50 means significant inconsistencies that actively damage the brand experience.
How often do AI models change their answers?: AI models are updated continuously. Major updates typically happen monthly, but smaller adjustments can happen daily. Therefore we recommend weekly testing to catch changes quickly. Some changes are positive (the model learns about you), others negative (the model forgets or misrepresents).
Can I influence what AI models say about me?: Yes, but indirectly. AI models pull information from the web, so by optimizing your content — authoritative sources, consistent information across platforms and structured data as a supporting signal — you increase the probability that models present correct information about you.
Does this work for personal brands?: Absolutely. Personal brands are especially vulnerable to AI misinformation because there are fewer authoritative sources. AI Consensus helps you identify and correct errors before they affect your career or business.

Try AI Consensus free