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The Bench & Bar AI Brief | Issue 009 | July 21, 2026

AI-Assisted Litigation Is a Court-Capacity Question

NCSC's court-capacity webinar and Tennessee's July 22 AI meeting point to a practical need: measure demand, simplify process, govern data, and keep people accountable.

Tennessee Edition

Welcome to Issue 009 of The Bench & Bar AI Brief, Tennessee Edition.

Planned publication date: July 21, 2026.

Courts have spent good time warning lawyers that artificial intelligence can invent authorities. The next challenge is larger. If AI makes legal drafting faster and cheaper, courts may face more filings, new kinds of self-represented assistance, and a wider range of quality. That is not yet proof of a filing surge. It is a capacity question worth measuring before it becomes a crisis.

The National Center for State Courts put that question at the center of a July 15 webinar titled The coming wave: How courts can prepare for AI-assisted litigation. The program examined what AI-assisted filings may mean for court operations and access to justice. Its stated operational subjects included measuring baseline filing trends, simplifying processes, applying existing procedural tools, and investing in the right technology.

The careful word is may. The event page does not prove that filing volume has already increased because of AI. Its value is that it moves the conversation from headlines to court administration. A court cannot manage a trend it does not measure, and it should not buy a technology before it knows which problem the technology is meant to solve.

NCSC's earlier implementation guides, dated March 2024, supply a useful foundation. They recommend starting with simple, low-risk tasks that use public information and favoring internal work before public-facing output. They call for human subject-matter review, training for judges and staff, controlled pilots, and careful examination of contracts and data practices.

The platform guide also recommends a team-based approach. Information technology, legal counsel, the bench, and court operations should evaluate a tool together. Courts should know what data will be entered, who can access it, how it will be stored, whether prompts or outputs may train a model, and who has authority to accept the terms.

That advice matters because AI can enter a courthouse through many doors. It may arrive in a filing prepared by counsel, a self-represented litigant's draft, a vendor feature added to an existing product, or an internal experiment by court staff. One office may see a writing tool. Another may see a records, security, procurement, access-to-justice, or workload issue. All may be right.

Tennessee has a timely local reason to ask these questions. The Tennessee Artificial Intelligence Advisory Council will hold a public meeting on Wednesday, July 22, from 1:30 to 3:30 p.m. Central in Nashville, with online viewing available. The official notice describes a statewide mission to advance AI use in an ethical, adaptable, collaborative, and beneficial manner.

The notice does not identify a judiciary-specific agenda. Courts and lawyers should not claim otherwise. But the meeting is still a useful reminder that statewide AI planning and court-specific readiness are different jobs. Judicial systems have distinct duties involving records, due process, independence, access, security, and accountable decision-making. Those duties need a court-owned plan.

Three verified source signals.

  1. 1The National Center for State Courts framed possible AI-assisted filing growth as a court-capacity and access-to-justice question.
  2. 2NCSC implementation guides recommend low-risk pilots, human review, training, team-based evaluation, and careful contract and data review.
  3. 3Tennessee has scheduled a public AI Advisory Council meeting for July 22, while the official notice identifies no judiciary-specific agenda.

A six-part court readiness check.

  1. 1Measure the baseline. Track filing volume, filing types, correction demands, processing time, and other workload signals before assigning changes to AI.
  2. 2Simplify before automating. Remove needless steps and clarify forms, instructions, and procedures before adding a new tool.
  3. 3Use existing rules wisely. Address defective or abusive filings with ordinary procedural tools while avoiding unnecessary barriers for good-faith court users.
  4. 4Govern data and contracts. Review retention, access, model training, security, vendor changes, and click-through terms before use.
  5. 5Train the people who must review the work. Judges and staff need enough understanding to test output, recognize limits, and preserve human accountability.
  6. 6Pilot, measure, and revisit. Begin with bounded low-risk work, record what happens, and expand only when evidence supports it.

Bench & Bar takeaway.

AI-assisted litigation may increase access, increase workload, or do both at once. Courts do not need to guess which future will arrive. They need a baseline, a governance structure, and a way to learn without surrendering the duties only people can perform.

The question for this week: if AI changed your court's workload tomorrow, would you have the data to see it and the plan to respond?

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