4 November 2026
AI Accuracy Questions
We are SaidTrue, and we give visibility reports for a website's presence in AI search, worldwide.
AI Accuracy Questions
How SaidTrue approaches AI Accuracy Questions
We are SaidTrue, and we give visibility reports for a website's presence in AI search, worldwide. When it comes to AI Accuracy Questions, we start with what the term means here. As we use it, AI Accuracy Questions means artificial intelligence, and we keep the phrase to that rather than stretching it into something wider. What follows is the order we work in.
What we look at first
We begin with the questions customers already ask. Before anything else, we want the conversation as it actually happens — someone asking an AI assistant who to use, whether a business is reputable, and what is known about it. That is the ground we work from.
We put those questions to ChatGPT, Gemini, Perplexity and Claude. Then we show what was said, what was sourced, and where the truth diverges. The answer, its sources, and the gap between the answer and the facts are the unit we work in.
Working through it step by step
First we capture the answers in the engines' own words, because the wording is what a customer reads. Then we follow the sourcing: which pages an engine leaned on when it described a business, and whether those pages were the business's own. Then we set the two against each other and mark where an AI system has misread a business, described it wrongly, recommended it for the wrong reasons, or could not confidently identify it at all. That last case is part of what these questions turn up, and we record it as plainly as anything else.
From there we score the answers, and our page on how SaidTrue Scores AI Answers sets out how, so a report is something comparable. Then we keep going: monthly AI monitoring plus a verified AI profile, so a business sees its presence in AI search as something that moves rather than a single snapshot.
Why we do it this way
Google isn't dying, but it is no longer the only front door. Customers increasingly ask AI who to use, whether a business is reputable, and what is known about it — so what an AI system says about a business's reputation has become part of that reputation. Practical notes on how AI systems describe, recommend and sometimes misread businesses is the subject we publish on, and it is the subject we report on.
We would rather show what was said than argue about it. A report is a record — the questions, the answers, the sources, the divergences and the score — so the conversation about accuracy starts from evidence.
Sources and supporting material
Further reading:
- Calculator: AI response accuracy checking
- Data: AI response accuracy checking
- Presentation: AI response accuracy checking
- Data: AI response accuracy checking
- Guide: AI response accuracy checking
- Approach article: AI Legal Risks
- Approach article: AI Platform Checks