Syntharis Group releases free 200-page GEO guide

Syntharis Group has published a free 200-plus-page book on generative engine optimization, arguing that companies should treat AI visibility as an extension of search, not a replacement for it. The guide also warns about reputation risks in AI answers and lays out ethical rules for brands trying to appear in systems like ChatGPT, Gemini, Claude and Perplexity.

Why it matters: - The guide challenges some of the loudest claims around Generative Engine Optimization, a field that is drawing attention as brands try to show up in AI-generated answers. - The book argues that companies need a broader AI visibility strategy, not just tactics built around one chatbot or one platform. - The playbook says reputation errors in AI answers can spread fast, which raises the stakes for brands, publishers and search teams.

What happened: - Syntharis Group, a Dubai-based consultancy focused on AI visibility and search, released The AI Visibility Playbook by founder and CEO PhDr. Oliver Scharfenberg. - The book is available as a free download at more information. - The playbook runs more than 200 pages and reviews common claims about Generative Engine Optimization, or GEO. - GEO refers to making companies visible in answers generated by AI systems such as ChatGPT, Gemini, Claude and Perplexity.

The details: - The book says search engines are not disappearing, even if AI is changing how people find information. - It cites a Graphite analysis of Similarweb data covering more than 40,000 large U.S. websites, which found organic search traffic down about 2.5% year over year. - The book contrasts that figure with much steeper 25% to 60% declines that are often repeated in industry conversations. - It says GEO builds on search engine optimization rather than replacing it, because crawlable pages, clear structure and useful content still matter for both AI answers and traditional rankings. - The book warns against optimizing for a single AI platform. - It references a 2026 Goodie report based on 41 B2B brand websites, where ChatGPT’s share of measurable AI referrals fell from 89% to 63% over about eight months. - The same report found Claude’s share rose from 1.4% to 18.5% over that period. - The book says other studies using different methods still show ChatGPT ahead overall. - Scharfenberg says companies should track multiple AI engines rather than one. - The book also examines AI reputation risk. - It describes an Ahrefs experiment in which a researcher created a fake company, published fabricated stories about it online and found that most tested AI tools repeated the claims as fact. - It cites a May 2026 ruling by the Regional Court of Munich I in case 26 O 869/26, which issued an injunction in summary proceedings against Google over AI Overviews statements about two Munich publishers. - The court treated the generated text as Google’s own content, and an appeal is pending. - For companies facing inaccurate AI descriptions, the book outlines a nine-step response that starts with documenting the answer and fixing the company’s own sources, with legal action as the last step. - The playbook also draws ethical lines for GEO work. - It rejects fake reviews, networks of websites built only to promote a brand, borrowed credentials and invented statistics. - The book says AI-assisted content creation is acceptable when the result is accurate and useful to readers.

Between the lines: - The release positions GEO as a discipline that still depends on classic search fundamentals, which suggests AI visibility work may be more iterative than revolutionary. - The emphasis on testing, documentation and multi-platform monitoring points to a more cautious playbook than the hype around fast AI growth often implies. - The legal example signals that AI-generated brand claims are becoming a reputational and regulatory issue, not just a marketing issue. - Scharfenberg frames trust as the core asset in AI visibility, which reflects a broader shift from pure ranking tactics toward credibility management.

What's next: - The book recommends that companies test changes on a small scale before broad rollout. - It advises brands to monitor several AI systems as referral patterns shift. - It suggests companies should correct their own source material first if AI systems misstate facts about them. - The guide implies that legal escalation should come only after documentation and source cleanup fail.

The bottom line: - Syntharis Group is betting that winning in AI search will depend less on tricks and more on trustworthy content, disciplined testing and broad monitoring across multiple AI engines.