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Best Practices in Courts & Administration

Using GenAI to streamline HR tasks in courts

Natalie Runyon  Director / ESG content / Thomson Reuters Institute

· 5 minute read

Natalie Runyon  Director / ESG content / Thomson Reuters Institute

· 5 minute read

The integration of GenAI tools in court operations can significantly reduce the workload associated with human resources duties, and in some cases achieve time savings of up to 60% for smaller jurisdictions with limited HR staff

In the ever-evolving landscape of court operations, especially in smaller jurisdictions that may employ fewer human resources (HR) professionals, the integration of generative AI (GenAI) tools presents a transformative opportunity. The National Center for State Courts (NCSC) and the Thomson Reuters Institute hosted a recent webinar that demonstrated how innovative court systems are using GenAI to improve human resources.

From small municipal courts to large county court systems, leveraging AI to significantly reduce the workload associated with HR duties can achieve time savings of up to 60%, according to Tiffany Totah, Municipal Court Administrator for the City of Victoria, Texas.

Case study for small courts

For smaller courts with limited HR staff, time-consuming HR tasks can be particularly burdensome; however, publicly available GenAI tools like ChatGPT are a promising solution to streamlining these processes. For example, Totah noted that there are several immediate benefits and use cases for GenAI in the HR space, including:

Time savings in crafting job descriptions — Rapidly evolving court roles with increasing technical requirements often make traditional job descriptions obsolete. However, updating job descriptions is a time-consuming process. In fact, before using GenAI, Totah would request samples from other courts and organizations just to keep her court’s job descriptions current.

During the webinar, Totah showed how GenAI can dramatically expedite this task. By uploading existing job descriptions into an AI tool and prompting it to suggest updates based on current trends, she was able to quickly generate improved descriptions that incorporated sought-after skills like technical ability, adaptability, and innovation.

Reduced time requirements in performance-improvement plans — Similarly, GenAI can improve efficiency in performance-improvement plans, which are used to help upgrade team members who may be struggling in their work performances. In many cases, these performance-improvement plans lack objective and data-driven metrics. GenAI can be used to produce performance-improvement plan templates that can incorporate modern court responsibilities and key performance indicators.

Totah emphasized the importance of crafting detailed prompts when using AI for HR tasks, recommending that users include specific categories required by HR standards and clearly outlining the desired structure and components of the job description. The more information provided in the prompt, the more tailored and useful the AI-generated content will be.

Use case for larger court systems

In the webinar, Darren Dang, Chief Financial & Administrative Officer for the Orange County Superior Court, showed how his teams are using GenAI AI to aid employees with HR-related inquiries, including questions about vacation time. He showcased a chatbot called EMI, which has access to the court’s HR policies, procedures, and employee-specific information like paid-time-off balances. By using this tool, employees can quickly get personalized answers about their vacation accruals and balances without having to contact HR directly.


Join us in the next NCSC-TR Institute webinar Tech for All: Applications of AI to Increase Access to Justice


Dang explained that EMI uses retrieval augmented generation to pull relevant information from HR databases and documents and provide correct, employee-specific responses. He noted that this AI assistant helps streamline HR processes, reducing the workload on HR staff and allowing employees to get immediate answers to common questions.

In the future, EMI will be enhanced by equipping supervisors and managers with relevant information on their employees to help managers further reduce their workload of administrative duties.

Important points for implementation

When implementing GenAI for HR tasks in court systems, Dang and Totah highlighted several crucial considerations and best practices that users should keep in mind for successful adoption and integration, including:

      • Ensure a human-in-the-loop approach — Totah stressed the critical role of human oversight. For example, when crafting job descriptions Totah recommended reviewing and refining the AI outputs and involving frontline staff to ensure accuracy and relevance. This human-in-the-loop approach combines the efficiency of AI with the nuanced understanding of human experts.
      • Start small and implement gradually — As court professionals further explore AI applications, both Dang and Totah suggested that they start with internal, lower-risk use cases, like those in HR functions. This allows for experimentation and learning internally before potentially expanding to public-facing tools. Likewise, focusing on internal-facing applications initially allows staff the time to work out issues and build confidence in the system before expanding access.
      • Automate the boring stuff — Courts should also focus on using AI for tasks that staff find tedious or time-consuming. Duties, such as searching through procedures or extracting information from invoices, are best suited for AI assistance, according to Dang. This helps with adoption by reducing friction and allowing staff to focus more on work they enjoy.

While AI tools offer exciting possibilities for improving court operations, it’s important to remember they are assistive technologies, not replacements for human judgment. The most effective implementation of AI in court settings combines the efficiency and analytical capabilities of AI with the contextual understanding, ethical insights, and decision-making skills of court professionals.

To get started, Totah and Dang both agreed that the NCSC AI Sandbox — which offers a platform to practice and refine AI prompts without exposing sensitive data — provides a safe environment for courts to begin this journey.


You can find more about how courts are using AI-driven technology here

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