By 2025, studies show that brands in the top 25% for web mentions are getting 10× more AI visibility than their peers. ( Ahrefs) Meanwhile, off-site brand signals like mentions — more than just backlinks — now correlate more strongly with AI Overview presence than classic SEO factors.

Add to that: Gartner predicts that organic search traffic could decline as much as 50% by 2028 as AI systems replace click-based search behaviors. (Michael Brito)

So what does this mean for brands that want to remain visible — not just to people, but to machines? It means your content must be structured, your brand must be mapped as an entity, and your external credibility must be engineered so that AI platforms “understand” who you are. The tactics that once pushed you to page one must now evolve to push you into AI-generated answers.

How Berland Solves for This Shift

At Berland, we see GEO not as a tactic but as the architecture of brand presence for the new paradigm. Here’s how we build with future visibility in mind:

Entity structuring & knowledge mapping

We build a canonical identity for brands via structured data (schema), knowledge graph integrations, and cross-platform consistency. This ensures that AI systems interpret your brand as a coherent ‘thing’ — not just a collection of pages.

Canonical content for AI citation

We create “AI-friendly” content — clear, answer-oriented, structured with question/answer blocks, summaries, and data — optimized for LLMs to cite. We test sample prompts to see if the brand gets referenced.

Reputation & external signal engineering

Because AI favors third-party sources, we engineer the brand’s credibility via targeted press, creator partnerships, and web mentions that feed into AI signal networks. We treat PR as infrastructure, not fluff.

Continuous feedback & prompt optimization

Visibility in AI is dynamic. We monitor which prompts, citations, and content get picked up — then refine in real time. Brands evolve; we evolve with them.