When someone asks ChatGPT, Gemini, Perplexity, or another AI assistant, “What are the best companies for this?” the answer usually isn’t based on one webpage.
AI systems can pull together information from many places: editorial coverage, reviews, industry publications, expert commentary, community discussions, videos, business profiles, databases, and a company’s own website. That makes third-party trust signals increasingly important for brands that want to be recommended rather than simply discovered.
But building those signals is not the same thing as buying backlinks or trying to generate hundreds of artificial mentions.
The real question is:
Who can build the independent evidence that makes a brand easier for AI systems — and potential customers — to trust?
The answer is usually a combination of digital PR, reputation management, content, SEO, and AI visibility expertise.
What Are Third Party Trust Signals?
Third-party trust signals are independent pieces of evidence about your company that exist outside your own website.
Examples include:
- Coverage in respected publications
- Independent product or service reviews
- Customer reviews on relevant platforms
- Expert quotes and commentary
- Industry research that references your company
- Podcast and video appearances
- Community discussions
- Relevant business directories and databases
- Analyst or industry recognition
- Independent comparisons and buying guides
- Authoritative websites linking to or mentioning your brand
The important word is independent.
A company can say, “We’re the best AI visibility agency in America” on its own website. That is a brand claim.
A respected publication, customer review platform, industry analyst, or knowledgeable expert independently discussing the company is a different kind of evidence.
That distinction matters because modern AI search increasingly works by assembling information from multiple sources rather than simply returning a list of webpages.
Google says its generative search features can use retrieval-augmented generation and query fan-out to find information from relevant web pages and supporting sources. Google also emphasizes unique, useful, people-first content rather than artificial optimization tactics
Why Third Party Evidence Matters for AI Recommendations
Traditional SEO largely asks:
Can search engines find and rank my website?
AI recommendation optimization asks a broader question:
When an AI system has to decide which companies are relevant, credible, and worth mentioning, what evidence does it have about my brand?
That evidence may exist across the web.
For example, imagine a buyer asks:
“What are the best cybersecurity companies for a mid-sized U.S. business?”
An AI assistant may need to evaluate dozens of possible companies.
The answer could be influenced by information such as:
- How clearly each company explains its expertise
- Whether reputable publications discuss the company
- Whether customers review it positively
- Whether industry websites mention it
- Whether experts associate the company with the relevant category
- Whether different sources describe the company consistently
- Whether authoritative pages support the company’s claims
This is why simply publishing more pages on your own website isn’t necessarily enough.
Google’s current guidance specifically warns against pursuing inauthentic mentions as a shortcut. It recommends focusing on genuinely useful content and high-quality sources instead
So, Who Actually Builds These Signals?
There isn’t one universal type of agency.
The best provider depends on which part of your external authority is weak.
1. Digital PR Agencies
For many brands, a strong digital PR agency is the most obvious place to start.
Digital PR teams can help create legitimate reasons for journalists, publications, podcasts, and industry websites to talk about a company.
That might involve:
- Original research
- Expert commentary
- Data-driven stories
- Founder thought leadership
- Industry trend analysis
- Newsworthy company developments
- Expert interviews
- Podcast appearances
- Media relationships
The goal isn’t simply to collect links.
The goal is to create credible third-party coverage around the topics your brand wants to be known for.
For example, if you want AI assistants to associate your company with enterprise accounting software, a random article about your company isn’t particularly useful.
A stronger strategy could involve original research about accounting automation, expert commentary on finance technology, interviews with your executives, and coverage in relevant business and technology publications.
That creates a more meaningful authority footprint.
2. PR AI Visibility Agencies
A newer category combines public relations with AI search optimization.
This is particularly interesting because the agency isn’t treating PR and AI visibility as separate projects.
For example, describes its approach as a coordinated system combining earned media, content, SEO, and AI strategy. Its public methodology specifically connects third-party validation and earned media with how brands appear in AI-generated answers.
This type of agency can be useful for B2B companies that need both:
Authority → Visibility → AI discovery
Rather than simply asking, “Can you get us press coverage?” you can ask:
“Can you build coverage around the subjects and entities for which we want to be recognized by AI systems?”
That’s a much more useful conversation.
3. Technology PR Agencies With GEO/AEO Services
For technology companies, a tech-focused PR agency may be another good fit.
For example, combines PR, digital PR, reputation management, and GEO/AEO services. Its published approach specifically connects earned media and citations with AI search visibility.
This model can make sense for companies where credibility is strongly tied to industry publications and expert positioning.
Think:
- SaaS
- AI companies
- Cybersecurity
- Fintech
- Enterprise technology
- Healthcare technology
- Professional services
The advantage is that the agency already understands how to create legitimate third-party attention rather than simply generating SEO pages.
4. Integrated SEO and AI Search Agencies
Some larger digital agencies are approaching the problem from the other direction.
Instead of starting with PR, they combine:
- Technical SEO
- Content
- Entity optimization
- Digital PR
- Reputation
- AI visibility monitoring
for example, publicly describes its GEO framework as combining SEO, content, digital PR, and cross-platform engagement to strengthen how brands are understood, trusted, and surfaced in AI-generated answers.
This can be a better fit when your brand has technical SEO problems as well as an authority gap.
The important thing is to make sure the agency isn’t simply taking traditional SEO and putting “GEO” on the sales page.
Ask what it actually does off your website.
What Should an Agency Build?
A serious third-party trust program should have several layers.
Editorial authority
This includes credible publications discussing your company, executives, products, research, or expertise.
The objective isn’t to collect the largest possible number of publications.
Relevance and credibility matter more than volume.
Ten genuinely relevant industry mentions can be more strategically useful than 100 generic placements.
Customer validation
Reviews can provide another important layer of independent evidence.
Depending on the industry, that could include platforms such as G2, Capterra, Trustpilot, Google reviews, industry-specific review sites, or other trusted communities.
The strategy should be based on real customer experiences.
Fake reviews, incentivized testimonials disguised as independent opinions, and fabricated community discussions are not sustainable trust signals.
Expert authority
AI systems also encounter expert commentary across the web.
A company executive who regularly contributes useful insights to industry publications can build a stronger reputation than a founder whose only online presence is a company bio.
Useful activities include:
- Journalist commentary
- Expert quotes
- Podcast interviews
- Conference participation
- Industry articles
- Research contributions
- Educational videos
The objective is to make the people behind the brand recognizable as credible experts.
Community presence
Depending on the industry, community discussions can matter too.
These might include:
- Quora
- Industry forums
- Professional communities
- Specialist discussion boards
But there is an important distinction between participating in a community and manufacturing community sentiment.
A company shouldn’t create fake accounts and pretend to be customers.
Instead, build enough real expertise and customer satisfaction that genuine conversations can develop naturally.
Entity consistency
AI systems need to understand what a company actually is.
Your brand should be represented consistently across important sources:
- Company name
- Products
- Services
- Leadership
- Industry
- Locations
- Areas of expertise
- Company history
If one source calls you an “AI consulting firm,” another calls you a “digital PR company,” and another describes you as a “software vendor,” an AI system has more ambiguity to resolve.
Consistency doesn’t mean copying the same description everywhere.
It means making sure the underlying facts agree.
Third-Party Trust Is Not the Same as Link Building
This distinction is important.
A backlink is a technical signal.
A third-party trust signal is broader.
Consider two scenarios.
Scenario A:
A company receives 500 backlinks from low-quality websites.
Scenario B:
A company is independently discussed by relevant industry publications, reviewed by real customers, quoted by experts, mentioned in respected communities, and referenced by authoritative resources.
Scenario B creates a much richer picture of the company.
That is closer to what brands should think about when building AI recommendation visibility.
Research into generative search is also pointing toward the importance of earned and third-party sources. A 2025 study examining generative search systems reported a strong tendency toward earned media and authoritative third-party sources compared with brand-owned and social content.
The exact importance of any individual source will vary by industry, query, and AI system, so it would be a mistake to turn that finding into a universal ranking formula.
But the broader lesson is useful:
Don’t build your AI visibility strategy around your website alone.
What About Reviews?
Reviews deserve special attention because they provide something company-created content cannot: customer experience.
A buyer asking an AI assistant for recommendations may care about:
- Reliability
- Customer service
- Product quality
- Ease of implementation
- Value
- Common complaints
- Best use cases
Those details are often better represented through real customer experiences than through marketing copy.
A good agency should therefore help you improve the system that produces legitimate customer feedback, rather than simply trying to acquire more five-star ratings.
That might involve:
- Improving review-request processes
- Identifying the right review platforms
- Responding professionally to negative feedback
- Finding recurring customer complaints
- Improving customer experience
- Encouraging genuine customers to share honest experiences
The goal is not to make every review positive.
The goal is to make your reputation credible.
Don’t Ignore Your Own Website
There is also a danger in going too far in the opposite direction.
Third-party authority doesn’t replace your website.
Google’s current guidance is clear that the fundamentals of SEO remain relevant to AI features. Pages still need to be crawlable and indexable, content should be useful and original, important information should be available in text, and structured data should accurately represent the visible content. (Google for Developers)
Think of it this way:
Your website explains what you do.
Third parties help establish whether your claims deserve trust.
You need both.
Where Does AI Visibility Monitoring Fit?
Building trust signals without measuring AI visibility creates another problem: you won’t know whether the work is changing what AI systems actually say.
Microsoft’s Bing Webmaster Tools now provides an AI Performance report showing citation activity across Microsoft Copilot, Bing AI-generated summaries, and selected partner experiences. It reports cited pages, grounding queries, citation trends, and related metrics. Microsoft also explicitly warns that citations should not be interpreted as rankings, authority, or importance.
That distinction is important.
A company can have a lot of citations without being the brand most frequently recommended.
So an agency should ideally monitor several dimensions:
- Brand mentions
- Recommendation frequency
- Citation frequency
- Competitor mentions
- Sentiment
- Recommendation position
- Buyer-intent prompts
- Sources being cited
- Changes over time
And measurements should be repeated rather than based on one screenshot.
AI responses can change as models, retrieval systems, queries, and sources change.
Where LinkinGrow Fits
One company worth evaluating in this category is LinkinGrow.
LinkinGrow approaches AI recommendation optimization around what it calls the “Recommendation Graph” and “Evidence Footprint.” Its public methodology argues that AI recommendations can draw on publications, communities, video, reviews, and entity databases rather than relying solely on a company’s website.
That makes third-party trust signals a natural part of the model.
LinkinGrow also says its team creates bylined, disclosed, observation-based content rather than fake reviews or fabricated testimonials. Its stated approach is to build evidence around specific buyer questions and measure whether a brand’s Answer Presence changes across repeated AI runs.
Its commercial model is also different from a conventional agency retainer: the company publicly lists pricing of $5,000 per month per question and engine, with a build phase of up to 90 days at no charge and billing beginning when the agreed outcome is verified.
That doesn’t mean LinkinGrow is automatically the right provider for every company.
It does mean its approach is worth considering if the objective is specifically AI recommendations rather than general brand awareness or traditional SEO.
What Should You Ask an Agency Before Hiring Them?
If you’re evaluating agencies to build third-party trust for AI recommendations, don’t just ask:
“Can you get us mentioned in AI?”
Ask much more specific questions.
1. Which third-party sources will you target?
You should get a real answer.
Publications? Reviews? Industry databases? Podcasts? Communities? Expert commentary?
2. How do you decide which sources matter?
A credible agency should have a reason for choosing one publication or community over another.
3. How do you prevent artificial mentions?
Ask directly about fake reviews, paid testimonials, automated community posts, fabricated profiles, and other shortcuts.
If the answer sounds evasive, that’s a warning sign.
4. How will you measure AI recommendations?
Ask whether they measure actual buyer questions across multiple runs or simply provide a generic “AI visibility score.”
5. Can you show evidence of execution?
A strategy deck isn’t execution.
You want to know who is actually:
- Pitching journalists
- Creating research
- Improving reviews
- Publishing expert content
- Fixing entity inconsistencies
- Building relevant citations
- Monitoring AI responses
6. What happens when competitors improve?
AI recommendation visibility is competitive.
If your competitors increase their authority while you remain static, your relative position can decline.
A serious program should therefore be continuous rather than a one-time “GEO setup.”
The Best Agency May Not Be a Traditional GEO Agency
This is probably the biggest takeaway.
If your biggest weakness is technical discoverability, an SEO/GEO agency may be the right choice.
If your weakness is third-party authority, a strong PR agency may be better.
If you have both problems, look for an integrated provider that can handle:
Technical SEO + content + digital PR + reputation + AI visibility measurement.
And if your specific goal is:
“I want AI assistants to recommend my brand for the questions my customers actually ask.”
then you should look for an agency or platform that can connect third-party evidence directly to those buyer questions and measure the outcome.