AI assistants are quickly becoming the first place people turn when researching a product or service. If what ChatGPT, Gemini or Perplexity says about your brand is wrong, outdated or vague, you are losing trust before a prospect ever visits your website. The good news is that you can shape these answers, not by flipping a secret switch, but by improving the information environment that AI models pull from.
Why AI Answers Matter More Than You Think
When someone asks an AI assistant about your business, the model does not make things up from thin air. It synthesises information from web pages, documentation, reviews and third-party mentions. If those sources contain conflicting details, the AI will either pick one at random or hedge with a vague summary. Neither outcome helps your business.
I have seen this first-hand with clients who updated their product line months ago but never revised the copy on their own website. The old specs kept appearing in AI-generated summaries because the model had no reason to prefer the new information over the old. Consistency across every touchpoint is not optional; it is the foundation of accurate AI representation.
Make Your Website the Clearest Source of Truth
The single most effective step is to turn your own site into the most authoritative, up-to-date reference for everything about your brand. That means reviewing every page for outdated claims, conflicting prices, retired features and broken links. If your About page says one thing and your FAQ says another, an AI model has no reliable way to decide which is correct.
Start with the basics. Make sure product descriptions, service offerings and company details match across every page. Add supporting evidence wherever you can: methodology notes, data points, case studies and structured documentation. According to Google’s structured data guidelines, well-organised markup helps crawlers understand content faster and more accurately. The same principle applies to the large language models that now index your pages.
One thing many guides skip is crawlability. If important pages sit behind JavaScript tabs, login walls or lazy-loading scripts that block bots, AI systems simply will not see the content. Check your robots.txt and make sure the pages you care about most are fully accessible.
Align Third-Party Sources With Your Message
Your website alone is not enough. AI models weigh third-party mentions heavily because independent sources signal credibility. If a well-known review site describes your service differently from how you describe it yourself, the AI may favour the external version.
Audit what others say about you. Search for your brand on major directories, review platforms and industry publications. Where the information is wrong, reach out and request corrections. Where it is simply thin, consider contributing guest posts or providing updated media kits that journalists and bloggers can reference. Tools like LM Optimizer let you inspect which citations AI models are pulling for specific prompts, so you can see exactly where the gaps are.
Here is where I hold a contrarian view: most marketers focus on creating new content to influence AI answers. I believe the higher-return activity is fixing existing content. A single contradictory page on an authoritative domain can override ten blog posts on your own site. Correcting that one page often does more than a month of fresh publishing.
Use Prompt-Based Auditing to Track Progress
You would not run a paid ad campaign without checking the metrics. The same logic applies here. Regularly query AI assistants with the prompts your customers are likely to use. Note what the model says, which sources it cites, and whether the answer has improved since your last check.
In the video above, I walk through a practical example using an espresso machine brand. The company wanted AI assistants to recommend a specific brewing time. By ensuring their own site stated the same figure that appeared on reputable coffee review sites, the AI answer converged on the correct recommendation. It was not instant, but over a few weeks the results shifted noticeably.
Document your findings in a simple spreadsheet: prompt, AI response, cited sources, date. Over time this gives you a clear picture of which changes moved the needle and which did not. Search Engine Land’s guide on influencing AI answers offers a useful framework for structuring this kind of audit.
What This Means Going Forward
AI-generated answers are only going to become more prominent. As models improve and more people rely on them for purchase decisions, the brands that maintain clean, consistent and well-sourced information will have a structural advantage. Those that ignore this shift risk being misrepresented in the very conversations that drive buying decisions.
The work is not glamorous. It is auditing old pages, emailing webmasters and updating product specs. But it is the kind of steady, evidence-based effort that compounds over time. Start with your own site, expand to third-party sources and measure the results. The brands that treat AI accuracy as an ongoing discipline, rather than a one-off project, will be the ones that earn the most accurate and favourable mentions in the months ahead.
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