Building Trust in an AI-Driven Search Environment

AI-driven search now accounts for more than half the volume of traditional search engines. According to a 2026 study from Graphite.io, AI platforms generate roughly 45 billion search sessions a month worldwide, equal to 56% of global traditional search volume. 

This seismic shift is reshaping how a growing share of people perceive your organization. It means your audience is now asking an AI platform a question about your organization, and the platform answers with a synthesized summary, pulled from all the sources it considers authoritative on the topic. 

That summary is often the entire interaction. There is no scrolling through 10 blue links, no comparing sources, no independent judgment call about what to believe. The AI platform has already made that call. 

For communications practitioners, this changes what building trust actually means. It is no longer enough to have the right message. The sources AI is reading must carry that message too, or the audience never encounters it at all.

Recognizing AI search patterns

How AI platforms decide what to retrieve and cite remains largely a black box. But a growing body of research is making the pattern easier to understand.

Muck Rack’s Generative Pulse team has tracked AI citation behavior across ChatGPT, Claude and Gemini through three editions of its “What Is AI Reading?” study, and the finding has held steady each time: Earned media drives the overwhelming majority of what AI cites. 

In the most recent edition, earned media accounted for 84% of all AI citations, while paid and advertorial content made up just 0.3%. Journalism alone represented 27% of cited sources. The rest was split across corporate blogs and owned content, encyclopedic and aggregator sources like Wikipedia, and government or academic material. 

The pattern is consistent enough to build a strategy around: AI is reading what independent, credible sources say about you, along with what you say about yourself. Echoing your message across all these platforms might be key to affecting how accurately AI platforms describe your organization and your work. 

Creating a platform-wide strategy

To build trust through accurate information, you need a strategy that spans every platform at your disposal. No single channel or platform can carry this alone.

For years, communications functions ran earned media, paid media, owned content and social as separate disciplines, with separate teams and separate calendars. Nobody noticed or changed this because no one was reading all of their content side by side. 

Now, AI platforms do exactly that, synthesizing everything into one answer. The first step, then, for communicators as they’re trying to build trust in their brand is a core message and a clear set of priorities that hold steady across every platform. 

Once that core message is set, platform-specific strategies should be put in place to echo that message and priorities. Basically, think about how to get each channel to echo it in the form AI actually reads. 

Here are a few ways to think about it: 

• Earned media: Identify which outlets AI treats as authoritative in your category, not just the outlets you’d instinctively pitch, and confirm they reach your audience too. Then place your message there deliberately: op-eds and features in the specific publications AI already trusts on your topic.
• Website and owned content: The goal with websites when it comes to affecting responses on AI platforms shifts from ranking your web page high in Google Search to extractability. AI platforms extract information from webpages through clear headers, direct answers near the top, FAQ formatting, and consistent naming for your organization and its programs.
• Social and LinkedIn: Semrush’s analysis of 325,000 prompts found
  LinkedIn now ranks ahead of Wikipedia and YouTube as a cited source on ChatGPT, Google AI Mode and Perplexity. Posting on LinkedIn at a regular cadence can meaningfully reach your audience on the platform, while affecting what shows up on these AI platforms when asked about you.
• Wikipedia and reference sources: Encyclopedic and aggregator sources made up roughly 17% of citations in the Muck Rack analysis referenced earlier, and most organizations do not manage that share at all. Have a strategy to build the third-party coverage Wikipedia requires as sourcing, and to correct what’s already there when it’s wrong. 

Staying in control of your story

These four levers are a starting point that can be expanded on. The specific tactics will keep evolving as AI platforms do. 

What won’t change is the underlying shift: You have to think about these opportunities comprehensively, not as separate workstreams competing for budget and attention. Trust with our audiences is earned the same way it always has been: through consistent, accurate, accessible information. 

What’s different now is that you have to think about what your audience’s AI is reading, not just what your audience is finding and reading directly. That means treating your AI presence as something you check regularly, not something you audit once a year and forget.

The organizations that show up consistently, across every platform, including the ones reading on your audience’s behalf, are the ones who stay in control of their own story.