If you’re getting citations in AI, something about your marketing and SEO foundations is working. But the next step is to ensure that those citations are accurate and up to date. Inspired Marketing has worked with brands who urgently needed to fix outdated AI brand info because their existing citations were misleading audiences.
Before reading further, it is worth checking that you have an “outdated” result rather than a “ghost” or “commodity” one. The distinction matters because the fix is different.
- A ghost company does not appear in AI results at all.
- A commodity company appears but is described in language so generic it could apply to anyone.
- An outdated company appears and is described specifically. But the specific things the AI model is saying are no longer true. The product names might be old, or important company details may be out of date. Or it may be prioritizing a use case you’ve deprecated.
The Outdated result is the most insidious of the three because it can masquerade as good AI visibility right up until someone acts on it. A prospect may arrive on a sales call after researching you with AI. This looks like a win. But the prospect is referencing a product you no longer sell or a problem you no longer prioritize.
They may be a poor fit for what you actually do now, which will waste your sales team’s time and damage your credibility.
If AI is describing a version of your company that is accurate but out of date, this is your starting point.
Making sense of outdated AI search results
The outdated result has a specific cause: it is almost always the result of older content outperforming newer content in the signals AI models give the most weight to.
This seems counterintuitive. You have published new content about your current positioning, and your website reflects where you are today. So why is the AI still reaching for the old version?
Authority accumulation can outweigh newness
Content that has been indexed for longer and has more external sources linking to it may carry more weight with AI models. Even if your newer material is accurate and well-written, it may be hidden by the signal the older content is sending.
The problem compounds after rebrands, pivots, funding rounds, and product launches. Each of these moments generates a burst of new content, but that content rarely accumulates authority fast enough to displace the older material. All of this drives a wedge between the company you are and the company AI thinks you are.
How to fix outdated AI brand info
Fixing this result requires two things working in parallel:
- Reducing the authority of the old content.
- Accelerating the authority of the new content.
Neither alone is sufficient. If you delete old content without building new signals, you risk reducing your visibility (and becoming a ghost).
Publishing new content without addressing the old leaves the AI with two conflicting versions of you, which usually produces an output that blends and confuses things.
1. Audit what is driving your current AI description
Before changing anything, identify the specific content assets that are producing the outdated result. Run the prompt test across multiple models and note the language that keeps appearing. Then trace that language back to its source: which pages, articles, or external references use those exact terms?
This audit tells you what you are actually dealing with. Is the outdated signal coming from:
- your own site?
- A press release that got widely syndicated?
- A G2 profile that has not been updated?
- A trade publication feature that ran at your Series A and still ranks well?
Each source requires a different response, and knowing which ones are driving the problem is more useful than guessing.
2. Update or redirect the highest-authority old assets
For content on your own domain, the priority is updating rather than deleting. A page that has accumulated authority is an asset. If you delete it, you’re killing the signal it has built. The better approach is to update it in place: rewrite the content to reflect your current positioning while preserving the URL and the inbound links.
This means going back to your most-visited older pages and rewriting them from scratch if necessary.
For third-party content you cannot edit, the strategy is more complex. You cannot change what that content says, but you can dilute its relative authority by building a larger, more recent body of content that eventually outweighs it. This takes time, but it is the only lever available for external sources.
3. Create high-authority new content around your current positioning
The fastest way to shift an outdated result is to produce new content that accumulates authority quickly. This means targeting the channels and formats that build signal fastest:
- Earned media in credible trade publications.
- Detailed G2 and Capterra reviews from current customers that describe your current product and use cases.
- Long-form articles that address the specific problems your current ICP faces.
The content needs to be specific about what has changed and why. If you have pivoted from serving SMEs to enterprise clients, that shift should appear explicitly and repeatedly across your new content.
AI models can only work with what you write. If your new positioning is only communicated in sales conversations and pitch decks, it will not improve your AI description.
4. Refresh your structured profiles immediately
G2, Capterra, Crunchbase, and LinkedIn company pages are among the first sources AI models draw from for company descriptions. If your profiles on these platforms still describe your company as it was two years ago, updating them is the fastest single action you can take to shift an Outdated result.
- Start up by updating the description, adding in some language about your evolution if you can.
- Then update your category, ICP, and primary use cases. These are critical for users to navigate, especially when they’re in the consideration phase.
- Be intentional about the language you use to describe your differentiation.
Treat every field in your profile as a signal, and assign ownership of the project to someone who understands your latest messaging and positioning.
Make the transition explicit in public-facing content
Companies instinctively avoid being explicit about their old identity because they don’t want to amplify it. But with AI models specifically, that instinct backfires. The model already has the old version locked in. So, vague forward-looking language (“we’re excited to announce a new chapter”) gives the model nothing to update on. It can’t resolve the contradiction between its training data and what you’re saying now.
Instead, publish content that uses explicit evolution language:
- naming the shift
- dating it
- framing what changed and why
This is functional content for AI retrieval, and it creates the kind of citable signal that lets a model replace an old association with a new one.
Subtle and clever do not work
Two examples of pre-AI marketing pivots are instructive here. One was explicit, the other was more subtle.
Wise
When Wise dropped the “Transfer” from TransferWise, they launched a new name and explained the old one. Their communications stated that “TransferWise” had become a limitation, that the product had grown beyond money transfers, and that “Wise” reflected what it actually was now. That bridging language appeared consistently across their own channels and in third-party coverage. This gave AI models had clear, citable signal to update on, so the company has almost no risk of getting an outdated result in AI search in 2026.
Jaguar
Jaguar did the opposite. Their 2024 rebrand erased their social archive, replaced automotive imagery with abstract fashion visuals, and offered slogans (“Delete ordinary,” “Copy nothing”). This gives humans (and AI models) nothing to work with. The old brand remained the dominant signal because the new one was never explicitly connected to it.
The moral of the story: be Wise.
| How long before the new positioning takes hold? Longer than you want, and faster than you fear. Search-augmented models like Perplexity can begin reflecting updated content within weeks if the new material comes from high-authority sources. Pure LLMs update on training cycles and may take considerably longer. The most reliable approach is to treat AI visibility as a lagging indicator of your content programme. The work you do today will show up in AI results in weeks or months, not days. Treat it as a sustained content and positioning investment, and you will succeed in getting your AI search results up to speed. |
Old content needs attention, too
The most common mistake when brands make an effort to fix outdated AI brand info is focusing entirely on the new content and ignoring the old. It feels right. You want to move forward, not backwards. But it leaves the high-authority old material in place, still generating the outdated but heavily weighted signal.
The fix a sustained audit-and-refresh programme that does three things at once:
- Works backwards from the content assets currently driving your AI description,
- updates the highest-authority ones in place,
- and builds a body of new material that reflects your current positioning with enough depth and specificity to eventually outweigh the old.
We do the unglamorous work to fix outdated AI brand info before it starts to impact pipeline
This is a different kind of content investment to what most marketing teams are used to making. And it’s not very glamorous. It takes long-term discipline to identify the specific assets that are causing the problem and fix those first. Publishing new content and hoping the old content fades will not work.
If AI is describing a version of your company that no longer exists, Inspired Marketing is the people with the red pen and the patience to fix it.
