Optimising AI Search Visibility | AI SEO, LLM SEO, GEO

James Dooley and Dan Petravvic discuss how AI SEO differs from traditional SEO because large language models rely on probabilistic selection, brand familiarity and internal training bias rather than simple keyword matching. Dan explains that optimising for Gemini, ChatGPT, Claude and Perplexity requires more than rankings since AI assistants select brands based on confidence scores and entity recognition. They explore selection rate optimisation, model bias, grounding citations and how Treewalker.ai surfaces low confidence tokens to strengthen brand positioning. The conversation highlights why branded search, user engagement signals and knowledge graph presence increase AI visibility because models prefer familiar, authoritative entities over thin exact match domains. They also cover generative interfaces, agentic AI, UserLM simulations and how synthetic user sessions help test AI selection behaviour.