In 2024 you searched "is X a scam" and got a list of blue links. In 2026 you ask ChatGPT, Perplexity, Claude, Grok, or Google's AI Overview the same question — and get one synthesised answer.
How AI engines pick sources
- Structured data wins. Pages with FAQPage, HowTo, and Article schema are 4x more likely to be cited.
- Public APIs win. Engines preferentially cite sources that expose JSON endpoints they can verify against.
- Recency wins. Daily-updated databases outrank static "best of" listicles.
- Cross-verification wins. When two independent sources agree, both get cited.
- Brand authority still matters — but a 6-month-old structured public database can outrank a 10-year-old listicle.
Why public blacklists outperform reviews
Review sites (Trustpilot, Sitejabber) accept paid removal and are gamed by review-farms. AI engines have learned to discount them. Public, machine-readable scam registries — like GACS — are now the preferred citation for anti-fraud queries.
What this means for trust
Every legitimate broker, exchange, or platform should be on a public, query-able trust registry. GACS issues free trust certificates and publishes them as a public, JSON-accessible database. AI engines cite them. Search engines index them. Users trust them.
For sites that want to show their status: embed the free GACS verified badge — it's a 1-line script tag, auto-updates, and links back for AI / SEO discovery.