What happened
Virginia Lawyers Weekly reports that several Virginia law schools are expanding AI education for law students. Regent University School of Law is giving students access to Claude Enterprise and AI tools in major legal-research platforms. The University of Virginia is launching an AI and Legal Tools Lab focused on building and documenting tools for real legal workflows, while William & Mary continues a multi-year program covering AI, legal research, and professional responsibility.
Virginia Lawyers Weekly reports that Regent University School of Law will provide students with access to Claude Enterprise for the first time this fall, alongside AI features available through Westlaw, Lexis, and Bloomberg Law. The report says Regent is also adding upper-level electives on AI in patent law, legal practice, and legal writing, integrating AI instruction into skills and writing courses, and including an AI Bootcamp in first-year orientation. At the same time, many first-year courses prohibit or limit AI use so students can learn to read cases, analyze them, and develop their own legal reasoning. The article presents this as a dual approach: broader access to AI tools paired with continued emphasis on foundational lawyering skills.
Virginia Lawyers Weekly reports that the University of Virginia School of Law will begin a new AI and Legal Tools Lab on Aug. 26. Students’ grades will be based on two principal work products: a lab notebook documenting the design and development process for an AI tool, and a formal memorandum explaining the tool’s use cases and limitations. According to the report, the course is intended to examine how AI is used in legal practice and to give students practical experience thinking about edge cases, test cases, and ways to break a system that appears to work. The course is described as practical rather than programming-focused, with students expected to understand enough about how a tool works to assess it responsibly.
The report says William & Mary has offered an AI-focused law course since 2018 and has updated it as the technology changed, particularly after ChatGPT’s 2022 release. Professor Iria Giuffrida teaches the course and emphasizes that AI should enhance students’ work without replacing their ownership of the underlying thinking. Virginia Lawyers Weekly also reports that William & Mary offers additional courses involving generative AI in legal research and the broader implications of AI for law and legal practice. The University of Richmond is described as having offered its first AI-focused course with instruction from attorney Justin Ritter and his law partner, Chris Sullivan. The article does not provide enrollment figures, syllabi, tool-evaluation data, or independent confirmation from the schools beyond the reporting it cites.
Read the primary source: valawyersweekly.com ↗
Why it matters
The changes show AI moving from an optional topic into professional training for lawyers. Students are being taught both how to use AI tools and how to test their limitations, preserve independent judgment, and protect core skills such as legal writing and case analysis. The report does not independently verify the schools’ implementation, outcomes, costs, or the performance of any tools described.
Virginia Lawyers Weekly’s reporting matters because legal professionals work in a field where inaccurate citations, misunderstood authorities, confidentiality breaches, or poorly reasoned documents can directly affect clients and courts. Training that treats AI as a tool requiring verification and judgment could help future lawyers understand where automated assistance is useful and where it is unsafe. The reported U.Va. lab is especially notable because students are expected to document limitations and test failure cases, rather than treating an AI system’s output as self-validating.
The schools’ approach also reflects a tension between two educational goals. Students need enough exposure to current tools to function in workplaces where clients and employers may expect AI-assisted work, but they also need durable skills that remain necessary when systems produce errors or change rapidly. The report quotes U.Va. officials saying the course is designed to help students adapt as tools evolve, while Regent’s program combines access to AI with restrictions intended to preserve traditional legal analysis. These are reported institutional aims, not evidence that the programs have already improved student performance or professional outcomes.
The development has practical implications beyond law schools. Law firms, courts, clients, and regulators will increasingly depend on lawyers who can explain how AI-assisted work was produced, identify unsupported claims, and decide when human review is required. Virginia Lawyers Weekly reports that practicing lawyers are already facing client pressure to demonstrate savings through these tools. However, the article does not establish how firms are measuring those savings, whether AI reduces total legal-work costs, or whether the reported benefits persist after verification and supervision are included. Those missing details limit what can responsibly be concluded about the broader economic impact.
What to watch next
The main test will be whether these programs produce measurable improvements in legal work without weakening students’ ability to reason, write, and verify sources independently. Important unknowns include how schools handle confidential client information, hallucinated authorities, assessment and academic-integrity rules, and the quality of the tools students build. It is also not yet clear how widely similar programs will spread across Virginia or what results graduates and employers will report.
Future reporting should examine whether students’ lab projects are tested against realistic legal tasks and whether the schools publish evaluation methods or results. Useful evidence would include error rates, the kinds of cases or documents used for testing, how often human review changes an AI-generated result, and whether students can identify fabricated authorities or unsupported reasoning. The current report describes course structure and institutional goals but does not provide those measurements.
Privacy and professional-responsibility safeguards will also require attention. The source does not say what data students may enter into Claude Enterprise or other legal tools, whether exercises use real or synthetic client information, how retention and access are controlled, or what rules apply when a tool generates confidential or legally sensitive material. It also does not explain whether the schools have common standards for documenting AI assistance, checking citations, or disclosing its use in academic and professional work.
Finally, it will be important to track whether the programs become durable parts of legal education or remain isolated courses shaped by rapidly changing products. Virginia Lawyers Weekly reports that the U.Va. class filled quickly and that tools used now could look substantially different within two or three years. That creates a continuing curriculum challenge: schools may need to teach transferable practices such as verification, testing, data governance, and professional judgment rather than training students around one vendor or interface. The article does not report graduate outcomes, employer assessments, or comparable implementation data from all eight Virginia law schools.
