Four popular myths about AI optimization (GEO) and practical tips: why paid campaigns or one-off tricks are not enough and how to build credible brand visibility through external sources.
Brand in AI Blog
On the BrandInAI blog, we cover topics related to brand visibility in the world of artificial intelligence and AI-generated answers produced by large language models. We analyze trends, data, and real-world examples to show how AI is reshaping branding, content, and communication strategies. All of this is designed to help brands consciously build their presence in the AI-first era.
How malicious publications and content farms can falsify AI model knowledge and damage a company's reputation. This guide explains data poisoning mechanisms, risk areas, and practical tests and defensive strategies for immediate implementation.
What AI crawlers are, their main types and how the indexing pipeline works: chunking, tokenisation and vectorisation. We also explain control tools (robots.txt, LLMs.txt, metadata) and practical steps to protect your brand from misattribution.
A guide to reputation management in the generative AI era. Explains how GEO, RAG, and provenance affect brand narrative and offers practical steps: source correction, knowledge base synchronisation, reranking, and experimental KPIs for PR, Legal, and ML teams.
A guide to entities in the LLM era: what entities are, why traditional SEO weakens in AI assistants and how to build a coherent, canonicalized brand profile through name control, semantic context and zero-shot testing to increase visibility in language models.
What is LLM model temperature and how does it affect AI creativity and brand consistency in generated content. Learn when to set a low vs. high temperature and how it influences company name usage and control over marketing communication.