Addressing Staffing Challenges Through Strategic AI Integration in State Courts

Addressing Staffing Challenges Through Strategic AI Integration in State Courts

According to an article by Thomson Reuters, persistent staffing challenges continue to burden US state courts, threatening their ability to operate efficiently. The article cites a recent 2025 survey on staffing, operations, and technology, highlighting the widening gap between operational demands and available resources, particularly for clerk and administrative roles. As experienced staff retire and recruitment struggles persist, courts are increasingly looking to technology, especially generative AI to help mitigate these issues.

While many courts have adopted basic automation tools, the adoption of AI remains slow. Just 17% of the survey respondents report using GenAI, although over half believe it will have a transformational impact within the next five years. Projected efficiency gains are notable: courts estimate saving nearly three hours weekly within a year and up to nine hours per week over the next five years. However, without policies, protocols, and training programs in place, courts risk missing the opportunity to harness these tools effectively.

The survey also shows that delays and inefficiencies already impact many courtrooms, with over three-quarters of professionals reporting regular disruptions. Courts that do not adopt AI may find themselves further behind, compounding delays and increasing resource strain.

For law firm leaders who work closely with state courts, these findings underscore the importance of advocating for well-governed AI integration to strengthen court capacity and reduce friction in legal proceedings. While AI will not replace court professionals, it can empower them to do more with limited resources. 

As GenAI tools become more refined and accessible, strategic adoption, guided by clear metrics for both efficiency and accuracy, can help courts navigate persistent staffing pressures and build stronger, more resilient systems for the future.