Alabama Supreme Court Dismisses Appeal Over Lawyer’s Use of Fake Case Citations

A family in Alabama lost a trust dispute in April 2026 because their lawyer filed citations to cases that do not exist. The Alabama Supreme Court dismissed their appeal that month, calling the conduct egregious. The court also barred the lawyer from filing in that court again without co-counsel sign-off.

In the same month, a federal judge in Oregon sanctioned two lawyers $110,000 after they submitted 23 fabricated citations and eight invented quotations. The $110,000 sanction is the largest AI hallucination penalty in American legal history. The case in Oregon was dismissed following the sanction.

A judge in Manhattan ruled that a defendant who used a general-purpose AI chatbot to help prepare his case had waived attorney-client privilege. According to a database compiled by lawyer and data scientist Damien Charlotin, there have been more than 1,300 cases globally where a court or tribunal has commented on AI-generated hallucinations in legal filings.

Anthropic released a legal plug-in for Claude.

The release contributed to a roughly $285 billion selloff in technology stocks. Fortune reported the incidents as part of a broader pattern of lawyers using artificial intelligence to write briefs and prepare for court. The American Bar Association has identified five of its Model Rules of Professional Conduct directly impacted by AI use: competence, confidentiality, candor toward the tribunal, and supervisory responsibility.

When a lawyer submits a hallucinated citation, they fail their client and the court, corrupting the record the entire system depends on. General-purpose large language models like ChatGPT and Claude have been trained on the open web, in contrast to industry-specific legal AI tools plugged into databases lawyers have used for decades.

Wall Street has struggled to tell the difference, Fortune reported.

The author has practiced law across three jurisdictions and now serves as General Counsel of LexisNexis. The obligation in law runs to the client and to the court simultaneously. General-purpose AI is designed to produce text that looks like the right answer.

In law, the model cannot verify that the case it cited exists, that the case says what the brief claims, or that the case remains controlling authority. Lawyers get sanctioned, claims get dismissed, and defendants get handed to the prosecution. The question to ask of any legal AI tool is not how it performs on a benchmark, but what it is built on, and whether a lawyer can trace, verify, and stand behind the output in open court.

AI changes the practice of law through compression, the same work faster, and expansion, work that was never possible before. AI’s expansion potential in law is enormous, but it can only rest on a foundation that does not fabricate the underlying law. Litigation strategy built on decades of judge-specific outcome data is not a faster version of an existing task.