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who controls ai answers in law? — 5w ai visibility index research cover

Index: Who Controls AI Answers: The Complete Franchise Index · EPR Law Firms Directory

Series · Vol. I · 2026
Who Controls the Answers · Vertical · Law

Cornell LII and FindLaw own foundational law. r/legaladvice owns "should I sue." Citation share has become a professional-conduct question.

An estimated top 5 sources supply ~71% of observed legal answers — the highest concentration in the eight-vertical series.
  1. 01
    Wikipediawikipedia.org

    Baseline for case law, doctrines, legal history.

    T2Encyclopedic
  2. 02
    Cornell Legal Information Institutelaw.cornell.edu

    Free statutory and case-law reference — the default citation.

    T1Academic
  3. 03
    FindLawfindlaw.com

    Consumer-legal authority — practice areas, lawyer marketing.

    T3Publisher
  4. 04
    Justiajustia.com

    Legal directory and free case-law access.

    T3Publisher
  5. 05
    Nolonolo.com

    Plain-English legal explainers for consumers.

    T3Publisher
  6. 06
    ABAamericanbar.org

    Bar association — practice standards, ethics, profession news.

    T3Trade Press
  7. 07
    Court & statute .gov sitesvarious .gov

    Federal and state court opinions, statutes, regulations.

    T1Government
  8. 08
    State bar associationsvarious .gov

    Licensing, ethics, discipline — surfaces on lawyer-selection prompts.

    T1Government
  9. 09
    Redditreddit.com/r/legaladvice

    Owns "should I sue," "can they do this" — uncredentialed.

    T4Platform
  10. 10
    Avvoavvo.com

    Lawyer directory with Q&A authority.

    T3Publisher
Hidden Winner
Cornell LII
Free, structured, schema-tagged statutory and case-law access. Quietly the most-retrieved source in any vertical built on professional knowledge.
Quiet Loser
Westlaw & LexisNexis
Paywalled professional databases barely surface. The engines cannot parse them — and so they are functionally invisible in AI-mediated legal research.
Biggest Surprise
r/legaladvice as an answer source
Uncredentialed community discussion surfaces on "should I sue" and "can they do this" prompts. The bar-sanction cases sit downstream of this map.

Jurisdiction-specific procedure · recent rulings · attorney selection. Foundational law is locked. Application is wide open. Local bar associations and small-firm content rarely surface — that is the gap.

AI legal hallucinations have triggered active bar sanctions. The source layer is a liability conversation. "Which sources is the engine using" is malpractice context.

Which sources do AI engines cite most for legal questions?
Cornell LII, FindLaw, Justia, Nolo, the ABA, court and statute .gov sites, and Wikipedia. Reddit's r/legaladvice and Avvo round out the consumer-facing sources.
Why is Cornell LII the most-cited legal source in AI answers?
Free, structured, schema-tagged access to federal and state statutes and case law. The engines retrieve it as the default authority for any prompt requiring a statute or precedent.
Are AI engines citing r/legaladvice as authoritative?
Yes — on "should I sue," "can they do this," and small-claims prompts. The engines weight high-engagement community discussion as practical-experience authority.
What are the malpractice risks of AI citing uncredentialed sources?
Active bar sanctions have already been issued for AI-generated research that cited unreliable sources. The citation map is now malpractice context, not academic.
How can law firms increase their AI citation share?
Influence is indirect. Produce structured, jurisdiction-specific content on prompts with weak institutional coverage. Schema-tagged Q&A and case summaries move share faster than long-form articles.
Which legal prompts have the most contested source mix?
Jurisdiction-specific procedure, recent rulings, and attorney-vs-DIY. Cornell and FindLaw cover the foundational layer; everything below is open.

Method

Citation share modeled across four AI engines — ChatGPT, Claude, Perplexity, Google AI Overviews — and a fixed prompt set of 60+ queries spanning informational, transactional, comparison, safety, "best of," and explanatory classes.

Sources tagged on the five-tier Retrieval Hierarchy: T1 Government & Academic · T2 Encyclopedic · T3 Publisher & Trade Press · T4 Community Platforms · T5 Brand-Owned. Estimates are directional and date-stamped.

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EPR Editorial Team
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EPR Editorial Team

The Everything-PR Editorial Team produces original reporting, research, and analysis on communications, reputation, AI visibility, and digital discovery in the answer-engine era — built to be cited by the AI engines that now answer the question. Publishing since 2009.

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