It is the last week of budget season. Before a board meeting, your CEO asked ChatGPT about the company, then forwarded you the answer with a single line: "Can we fix this?"
By Friday, three proposals sit in your inbox. A reputation agency promises to take control of what AI says about you. An AI visibility startup demos a dashboard full of scores. Your PR platform vendor announces a new GEO module. Prices range from a few hundred to ten thousand dollars a month.
All three claim to deliver AI reputation management, yet they do not solve the same problem. This guide explains what each model really delivers, how to compare vendors, what to budget and which combination fits a corporate communications team.
|
Why read this article 💡 |
Three AI reputation management models at a glance
| Model | What it does | Best for | Typical budget | Main limit |
|---|---|---|---|---|
| AI reputation management agency | Audits AI answers, then works on earned media, content and consistent facts | Teams without bandwidth to act, or facing a reputation issue | $1,500 to $10,000 per month (estimate) | Results depend on sources it does not control; methods can be opaque |
| AI visibility software | Runs prompt panels on ChatGPT, Gemini or Perplexity and scores mentions, sentiment and citations | Teams that already run strong PR and need measurement | $19 to $499 per month at entry level, $2,000 to $5,000+ for enterprise | Measures without changing anything; methodologies differ |
| PR tech platform | Publishes, distributes and proves official content, then measures coverage and AI visibility | Listed and regulated companies that need a single source of truth | Annual SaaS contract | Requires adoption by the PR team; AI features vary by vendor |
The demand starts with a measurement gap. The Semrush 2026 AI Visibility Index, built on 126 million AI search prompts, found that 45% of marketing leaders cannot accurately measure their brand visibility in AI answers. Only 9% have the tools to track every relevant metric.
PR teams face the same gap. Muck Rack's State of PR 2026, based on 971 usable responses, shows that:
Meanwhile, vendors have rushed in. According to a 2026 market landscape by ThriveStack, pure play AI visibility vendors have raised more than $500 million in disclosed funding. Profound alone reached a $1 billion valuation with a $96 million Series C in February 2026, as reported by Fortune, then raised a $180 million Series D at $1.8 billion in September.
The result is a crowded market where agencies, software vendors and PR platforms all use the same words. Our guide to AI reputation management for communications teams explains why reputation is now decided inside AI answers. This article helps you decide who to work with.
Behind the same label, you will find three very different business models. Understanding them first saves weeks of demos.
Agencies sell a service: audit, strategy and execution. The best ones work on what LLMs actually read, namely earned media, expert content and consistent facts across directories and profiles.
Their strength is execution. Their weakness is dependency: when the contract ends, the method and the history often leave with the agency.
These platforms send a fixed panel of prompts to ChatGPT, Gemini, Perplexity, Claude or Copilot, collect the full answers and turn them into indicators:
The supply is abundant, with more than 50 vendors counted in ThriveStack's landscape. Costs can stay modest. Writing in IR Impact, Lydia Prexl, head of corporate communications at the payment provider Unzer, estimates that organizations can expect to spend between €200 and €600 a month depending on the provider, far below a traditional reputation study.
A PR tech platform sits where official content is produced: newsroom, press release distribution, media contacts and coverage measurement. Several now add AI visibility measurement, like Muck Rack with Generative Pulse.
This position matters because of what LLMs read. Muck Rack's analysis of more than 25 million cited links shows that earned media drives 84% of AI citations, against 0.3% for paid content, and that ChatGPT cites sources in 96% of its answers. In other words, the platform that publishes and distributes your content shapes the raw material of AI answers.
This is the first question to ask every vendor, because measuring is not the same as improving.
Practitioners confirm these limits. At Unzer, Lydia Prexl contacted authors and site owners each time she found outdated information, until the effort outweighed the impact. She also notes that many tools generate hundreds of recommendations every month, which can trap teams in a race for GEO content.
Because AI answers are probabilistic. SparkToro and Gumshoe ran 2,961 prompts with 600 volunteers, and their January 2026 study is clear: the odds of getting the same brand list twice are under 1 in 100, and closer to 1 in 1,000 for the same list in the same order. Lydia Prexl illustrates the trap with scores: ask a model several times for a reputation score and you may get 72, then 68, then 81, although nothing has changed.
A serious vendor therefore reports how often your brand appears across many runs, with a margin of error. Our article on the 4 LLM brand visibility KPIs details this method.
Use the same grid for agencies, software and platforms, so that proposals become comparable:
Monitoring tells you what AI says. However, it cannot tell a journalist, an investor or a model which document really comes from your company when a fake press release circulates. That proof sits upstream, in your publishing chain.
This is what Digital Provenance brings. Wiztrust Protect, for example, gives every corporate or financial content a proof of origin that anyone can verify publicly and that can be relied on in a disinformation crisis. Our article on building a corporate trust stack against disinformation shows how provenance and monitoring work together.
Prices are rarely public, but 2026 market data gives clear orders of magnitude. According to ThriveStack's landscape of more than 50 vendors, published entry plans for AI visibility platforms range from $19 to $499 a month, while enterprise contracts run from $2,000 to $5,000 or more. For full service agencies, the AI tools directory Stork estimates $1,500 to $10,000 a month.
Two remarks before you sign. First, a price per prompt misleads when vendors run each prompt a different number of times. Second, for a large group, the real cost often sits in the team time needed to act on the findings, not in the licence.
Some promises should stop the conversation immediately:
The warning is not theoretical. In June 2026, Google updated its guidance on hiring an SEO: it now lists optimizing for generative AI among typical services and, for the first time, encourages businesses to report deceptive providers to the US Federal Trade Commission.
There is no universal answer, but your situation points to a clear starting point.
For most corporate communications teams, the answer is a mix: a platform that publishes and proves, measurement plugged into it, and expertise to turn data into a media plan.
Blueprint GEO, built by Wiztrust with GetMint after one year of collaboration, follows this logic. It measures the gap between how LLMs portray a brand and its objectives, then realigns the PR strategy sector by sector. Eight leading companies adopted it at launch. In the company's 2026 study of the 40 CAC 40 newsrooms, the newsrooms it powers scored 77.3 out of 100 in visibility, against 58.8 for other solutions, and 80% of them were cited as a source by AI engines.
AI reputation management is not one purchase but three jobs: measuring, influencing and proving. With Gartner expecting PR and earned media budgets to double by 2027, according to its Predicts 2026 research, the choice deserves the same rigor as any media investment.
To choose well:
Next step: list the ten questions your stakeholders ask AI about your company, run them on three engines, then bring the grid above to your next vendor meeting.
What is the difference between an AI reputation management company and an AI reputation management tool?
A company, usually an agency, sells a service: it audits AI answers, then works on the sources LLMs read through media relations and content. A tool is software that queries LLMs with a panel of prompts and measures mentions, sentiment and citations. The tool tells you where you stand; the agency helps you move. Many corporate teams combine both, with their PR platform as the source of official content.
What tools allow Dircoms to measure their brand's visibility in LLMs?
Two families work together. AI visibility platforms regularly query ChatGPT, Gemini, Perplexity or Copilot with a fixed list of prompts, then measure brand presence, answer accuracy and cited sources. Media monitoring tools show which articles feed those answers. The real value lies in connecting the two, to see which PR actions change what AI says. Wiztrust, for example, makes this possible thanks to its partnership with GetMint.
Can an agency guarantee what ChatGPT says about our company?
No. LLM answers are probabilistic and change from one run to the next, and no vendor has a paid placement or a submission form with OpenAI, Google or Anthropic. A serious agency commits to actions and to a measurement method, not to an output.
Is there a method to improve brand reputation and visibility in AI answers?
Yes, and it works in three stages. First, measure the gap between how LLMs portray the brand and its objectives. Then, identify the outlets that feed those answers in your sector. Finally, adjust the PR strategy accordingly. This is the approach behind Blueprint GEO, the offer built specifically for communication teams by Wiztrust with GetMint. It is used by companies such as Malakoff Humanis, Business France, Schneider Electric, Macif, Groupama, Gecina and BPCE.
Which media should we target to influence AI answers in our sector?
It depends heavily on the sector, which is why a generic media list is not enough. The Wiztrust and GetMint barometer shows, for example, that in banking a single outlet captured 52.7% of AI citations. Start from the outlets that LLMs actually cite on your topics, then build your media plan around them.
How long does it take to see results in AI answers?
Expect weeks to months rather than days, because you are changing the sources that AI engines read and waiting for them to pick up new material. Set a baseline in the first month, measure monthly, and review the strategy every quarter with your executive committee.