Article
August 20, 2025
By Ellie Tuck
We are living through another fundamental shift in how people discover brands. But we’ve seen this pattern before: the move from analog to web, from search to social. Each time, the brands that adapted early gained lasting advantages. Now we are seeing the rise of LLM-powered answer engines and the emergence of Generative Engine Optimization (GEO), a strategy that leverages AI to optimize a brand’s visibility and reputation in answer engine results.
The numbers tell the story: over half of Google results now include a generative response. AI agents and chatbots are increasingly becoming the first stop for people seeking recommendations, advice or information. If your audience is already there and you are not auditing how your brand shows up, you are missing a critical piece of the discovery puzzle.
How we are navigating the shift
While the fundamentals of trust and quality content remain, GEO redefines how they are executed. Analysing tools like ChatGPT, Gemini and Perplexity shows that these models lean heavily on what is already in the public domain, especially high-trust, earned media sources.
In response, we have had to build custom tools to get under the hood of how a brand is being interpreted. These tools allow us to see where a client is showing up, how they are being described, and how that compares to others in their space.
This new landscape also demands a new level of precision from our creative campaigns. We are asking more specific questions. Is our messaging backed by the right expert validation? Is our content tailored for the types of media AI models trust? Is our phrasing distinctive enough to be picked up by both machines and people?
This is where creativity and technical precision now overlap. Our teams are building synthetic AI audiences to test ideas earlier and using our FH Fusion platform to assemble virtual focus groups that inform smarter, faster decision-making.
A practical framework for influence
Our approach is led by audience behavior. That has always been our starting point in PR, and it is no different in the world of AI.
To influence how LLMs respond, we focus on a few key levers:
- Earned coverage in high-trust sources
- Structured storytelling to make key messages clear
- Cross-channel reinforcement of the right signals
- Consistency, because LLMs rely on pattern recognition
This work is complex, and the environment is not static. But an adaptable, audience-led strategy puts us in the best position to succeed.
What this means for our industry
The implications are broad. Business leaders need to get smart about how these models make decisions, guided by real data, not guesswork. Answer engine visibility should become a core KPI, not just for communications teams, but for growth.
But reputational risk is a major factor. We are already seeing AI tools surface outdated or outright false content about brands. Because what an LLM says feels factual to users, our role shifts from defending a single source of truth to shaping the entire ecosystem that AI learns from. This is nuanced work, but it is also where we can have the most significant impact.
No one has all the answers yet. The models are evolving, the sources they trust are shifting, and the tactics that work today may not work tomorrow. But the brands that start auditing their answer engine presence now will have a significant advantage over those who wait.
The communications industry has adapted to every major shift in how people consume information. This one is no different, except for the speed at which it is happening. The question is not whether your brand will need a GEO strategy; it is how quickly you can build one that works. We’ve adapted before, and we’ll do it again.
Ellie Tuck is an SVP & Partner and Executive Creative Director based in New York.
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