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| Lindsey Bradshaw |
There’s a new question showing up in boardrooms, founder meetings, and marketing strategy sessions: “How do we show up in ChatGPT?” Or Gemini. Or Claude. Or Perplexity.
As AI-powered search continues to reshape how people discover information, many brands are scrambling to figure out what “AI SEO” actually means. The answer is simpler than many people realize: The same expertise-driven content that earns media coverage is increasingly helping shape AI visibility.
And that’s creating a major opportunity for founders, operators, consultants, and consumer brands already investing in thought leadership.
AI Search doesn’t work like traditional search
Traditional search engines primarily returned links. AI search engines generate answers.
Platforms like ChatGPT, Perplexity, Gemini, and Google’s AI Overviews synthesize information from multiple sources to answer questions directly.
That means visibility increasingly depends on whether AI systems view your content as:
- Helpful
- Credible
- Relevant
- Authoritative
- Frequently referenced
Google has repeatedly emphasized these principles through its E-E-A-T framework: Experience, Expertise, Authoritativeness, and Trustworthiness (Google Search Central: “Creating Helpful, Reliable, People-First Content”). Google explicitly states that its systems prioritize content created to help people—not content created primarily to manipulate rankings. (Google for Developers). In other words: AI visibility increasingly rewards expertise signals over keyword stuffing.
AI systems are learning from more than company websites
One of the biggest misconceptions about AI search is that visibility comes primarily from your homepage. AI systems often learn about expertise through the broader ecosystem surrounding your name and brand.
Recent research on generative AI search systems found that they rely heavily on news, media, and business publications, as well as digital media sources, when constructing answers. (Cornell University). This means your thought leadership doesn’t just influence people. Increasingly, it influences the systems answering people’s questions.
Why article archives matter more than ever
Most founders think about thought leadership one article at a time.
AI systems don’t. They evaluate patterns. If someone repeatedly publishes useful content on a specific topic, AI systems begin to associate that person with that area of expertise.
For example, if someone consistently publishes articles about:
- Prime Day strategy
- Seasonal commerce PR
- Holiday gift guide pitching
- Consumer brand visibility
- Commerce media trends
The emerging signal becomes: This person is an authority on commerce PR. That’s why article archives are becoming increasingly valuable. They create a visible expertise footprint. Instead of one isolated article, AI systems see a body of work.
Thought leadership is becoming AI training data
This is where things get interesting. Several major publishers have already entered partnerships with AI platforms that use published content to help power AI-generated answers. For example, Le Monde announced a multi-year agreement allowing Perplexity to reference and surface its journalism within AI-generated answers, while Perplexity launched a publisher revenue-sharing program that compensates publishers whose content appears in AI answers. Published expertise is becoming part of the AI information ecosystem. The more credible content attached to your name, the more opportunities exist for that expertise to be surfaced.
Journalists are already using AI
This trend isn’t happening in isolation. According to Muck Rack’s 2026 State of Journalism report:
- 82% of journalists now use AI tools
- 86% say PR pitches inspire at least some of their stories
- Journalists continue to prioritize expert sources, relevance, and original information. (Muck Rack)
That means thought leadership is influencing two audiences simultaneously: The journalists creating coverage, and the AI systems synthesizing information.
The articles most likely to earn AI visibility
Not all thought leadership contributes equally to AI visibility. The content most likely to appear in AI-generated answers tends to demonstrate genuine expertise, firsthand experience, and original insight. Articles that explain industry trends, share lessons learned, analyze emerging developments, or provide practical guidance often create stronger signals of authority than generic marketing content.
This closely mirrors what journalists have always valued. Both reporters and AI systems are increasingly looking for credible sources that offer unique perspectives rather than recycled information. A founder sharing real-world experience, a consultant breaking down industry shifts, or a brand publishing original research is more likely to be viewed as a trusted source.
The takeaway is simple: the most effective thought leadership isn’t promotional. It’s useful. Consistently publishing content that educates, explains, and contributes meaningful expertise helps build the kind of authority that can influence both media coverage and AI-generated answers over time.
The future of PR isn’t just media coverage
For years, the goal of thought leadership was visibility. Today, visibility has expanded. The article you publish today might influence a reporter, earn media coverage, rank in Google, appear in AI search results, or become part of future AI-generated answers.
That’s a very different content ecosystem than the one brands operated in five years ago.
The companies building recognizable expertise now are creating digital authority that extends beyond traditional search.
And increasingly, the brands that consistently publish useful, experience-driven insights are the ones most likely to be recognized by both journalists and AI systems. The future of discoverability isn’t just about ranking. It’s about becoming the source AI systems learn to trust.
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Lindsey Bradshaw is an 18-year PR specialist and founder of lab.Comms, a boutique PR consultancy helping Series A-D startups get discovered through earned media. Connect with her on LinkedIn.
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