State courts across the United States are at a turning point. They face the challenge of adopting artificial intelligence (AI) responsibly while protecting the core values of justice, fairness, and public trust.
To support this transition, the National Center for State Courts (NCSC) and the Thomson Reuters Institute recently co-hosted a webinar, Building AI Readiness in State Courts. The session introduced the AI Readiness Guide for State Courts, a resource developed by a multidisciplinary team of court leaders, practitioners, technologists, and legal experts.
The guide is designed to meet courts where they are. It offers tailored guidance for courts just beginning to build foundations, those ready to launch their first AI project, and those looking to integrate lessons from completed initiatives. To make the process concrete, the guide also provides practical tools, including an AI Readiness Assessment Tool that helps courts identify their starting point and an AI Governance Tool that maps out a 12-month plan for building effective oversight.
Three Levels of AI Readiness
Not every court begins in the same place when it comes to AI. Some are just starting to ask what AI might mean for their work, while others are already testing tools in daily operations. To reflect this range, the AI Readiness Guide is built around a three-level model. It creates a structured path that helps courts move forward step by step, avoiding the common mistake of rushing into projects without first laying the groundwork.
- Level 1 – Building Foundations: For courts beginning to explore how AI could fit into their internal operations.
- Level 2 – Implementing a Project: For courts that have completed the basics and are ready to test their first AI integration.
- Level 3 – Learning and Preparing for the Next: For courts that have already completed a project and want to fold lessons learned back into their policies and practices.
To help courts figure out where they stand, the guide includes an AI Readiness Assessment Tool. By answering a few short questions, a court receives a customized readiness report that shows its status across six key areas. This tailored report highlights priority steps, offers recommendations, and includes direct links to relevant resources, giving each court a clear and practical starting point.
Level 1: Building the Foundations
The guide places its strongest focus on Level 1. These early steps are not meant to be red tape. They are investments in long-term success, ensuring that any AI project is built on solid ground. Skipping them risks confusion, wasted resources, or even harm to public trust.
At this stage, courts are encouraged to focus on six essential pillars:
- AI Governance: creating a committee to oversee AI adoption and ensure accountability.
- Guiding Principles: setting clear values and boundaries to guide decisions.
- Internal AI Use Policy: offering staff clarity and guardrails on what is acceptable.
- Data Governance: improving data quality, since weak data can derail any project.
- AI Literacy: giving each role in the court the knowledge and skills needed to use AI responsibly.
- First Project Selection: choosing a starting project based on real workflow needs, not trends.
Together, these six pillars form the foundations of readiness, helping courts build a culture of responsible, sustainable innovation.
Establishing AI Governance: The Leadership Backbone
AI governance is described in the guide as the backbone of readiness. It isn’t a piece of software, it’s a human leadership structure. A governance committee sets policies, oversees projects, and manages both internal and external communication.
The guide recommends a diverse membership, so decisions reflect a wide range of perspectives. Alongside court leaders, this means including staff from different roles, such as interpreters, clerks, and technologists.
To turn this concept into action, the guide introduces the AI Governance Tool. It provides a detailed 12-month roadmap with a suggested five-team structure, month-by-month activities, and meeting agendas. Following this plan allows a court to complete all six Level 1 steps within a year. More importantly, it gives leaders a concrete starting point, helping them move past organizational resistance and ensuring that governance becomes a working part of the court’s culture rather than an abstract idea.
Articulating Guiding Principles: The North Star for Decision-Making
One of the governance committee’s first tasks is to draft a statement of guiding principles for AI. This statement is not a one-time exercise but a durable reference point to which courts can return when difficult or uncertain questions arise. To facilitate this process, the guide provides sample principles, formatting suggestions, and examples from other jurisdictions. Courts are therefore not required to begin from a blank page.
The importance of such documentation is illustrated by the 1999 NASA Mars Climate Orbiter failure, where a $125 million mission was lost due to a misalignment between teams using different measurement systems. Similar risks apply to AI projects: unclear expectations and poor alignment remain among the most common causes of failure in software development. Establishing guiding principles from the outset helps courts reduce these risks.
In this sense, guiding principles represent more than a philosophical exercise. They constitute a discipline of risk management that aligns stakeholders, sets boundaries, and prevents costly missteps. Like a North Star, they provide courts with a stable reference point as they advance in their use of AI.
Drafting an Internal AI Use Policy: Providing Guardrails and Clarity
While the governance committee sets long-term strategy, staff need guidance right away. An internal AI use policy fills this gap by offering clear rules for daily work with AI tools.
It serves two key functions:
- Guardrails : spelling out what employees can and cannot do with AI, reducing immediate risks.
- Clarity : helping staff understand what counts as appropriate use of different tools in their workflows.
The guide makes this task easier by providing examples from other jurisdictions, summaries of common provisions, and sample policy language. Courts don’t need to reinvent the wheel; they can adapt what’s already working elsewhere.
Assessing Data Governance: Fueling the AI Engine
The quality of a court’s data is the foundation of every AI project. It determines not only which innovations are possible, but also whether they succeed. The principle is unforgiving: garbage in, garbage out. If a clerk records the same outcome in five different ways, the result will be five different flavors of confusion for AI. For this reason, the guide identifies data governance as one of the most prudent investments a court can make. Strengthening data quality and standardizing practices must come before any new AI tool. The NCSC already provides extensive resources on data governance, and the AI Readiness Guide builds on this work by showing how better data directly fuels AI readiness.
Developing a Role-Based AI Literacy Strategy
AI literacy means having the knowledge, skills, and mindset to use AI effectively and responsibly. But it isn’t a one-size-fits-all concept.
What a court clerk needs to know to work with an AI tool can be very different from what a bailiff needs. The guide stresses that the first step is to define AI literacy by role, based on each court’s workflows and context.
By tailoring training this way, courts can build confidence and competence across all staff, without overwhelming them with irrelevant information.
Choosing the First Project Wisely: Need Before Novelty
The guide warns courts against chasing the latest “shiny AI tool” simply because it looks impressive. Instead, it emphasizes a need-first approach. The starting point is a workflow analysis, mapping out where staff encounter the biggest pain points, tasks that are highly manual, time-consuming, or prone to error. These areas are the most likely to benefit from AI, and in some cases, a simpler automation may be sufficient. To help courts make disciplined choices, the guide includes a Project Scoring Matrix. This tool allows courts to evaluate potential projects against seven criteria, such as time savings, feasibility, and measurable impact, ensuring that the first project selected is both practical and worthwhile.
Level 2: From Plan to Practice: Implementing the First AI Project
With these foundations established, courts can move to Level 2, where the focus shifts from planning to the practical and human challenges of implementation. At this stage, the real challenges often have less to do with technology and more to do with people.
The guide emphasizes that change management, communication, and strategy are usually the hardest parts of any AI project. Success depends on helping staff adapt to new ways of working, coordinating across roles, and keeping stakeholders engaged, long before and long after the technology is deployed.
Leading Change with Human-Centered Design
Effective change management starts well before an AI tool is deployed and continues long after. It’s about helping people adapt smoothly and ensuring the system fits their needs.
The guide stresses a human-centered design approach, instead of forcing people to adapt to technology, the question becomes, “How can the system meet people’s needs?” When staff are engaged early as co-creators, they gain ownership, a key predictor of successful adoption. This also uncovers barriers and insights that top-down plans often miss, since frontline staff know court workflows best.
A case study brings this to life. At Northeastern University, researchers built an AI tool to summarize lengthy education plans for families of students with disabilities. Families weren’t just test users; they were collaborators from the start, shaping features and refining prompts. The result was a tool that truly worked for the community it was designed to serve.
Strategic Vendor Engagement and Procurement
Courts have public duties that most private vendors don’t share, which makes vendor selection and contracts especially critical.
The AI Readiness Guide recommends careful vetting and provides a checklist of contract terms, covering data security, confidentiality, transparency, and accountability, to ensure partnerships uphold the court’s values and protect the public.
Level 3: Closing the Loop: Learning and Preparing for What’s Next
AI readiness is not a one-time milestone but a continuous cycle of implementation, learning, and adaptation. After a project goes live, courts must integrate lessons learned and workflow changes back into their governance and everyday practices. To support this process, the AI Readiness Guide provides a post-project checklist that prompts courts to revisit their core foundations, adjusting governance structures, updating guiding principles, and refining internal use policies as needed. This structured feedback loop ensures that each project leaves the court better prepared for the next, making AI adoption an ongoing program of continuous improvement. This cycle of learning and adaptation lies at the heart of the guide’s vision.
A Proactive Path Toward a Smarter Justice System
The AI Readiness Guide for State Courts delivers a clear message: responsible AI adoption is not about chasing technology but about building the human-centered structures that allow it to serve justice. Governance, principles, data quality, and literacy are as essential as the tools themselves. By treating AI as a structured journey, the guide shows courts how to innovate while safeguarding fairness and public trust.
More than a technical roadmap, it is a call to action for courts to prepare deliberately, act responsibly, and learn continuously. Courts that take this path will not only improve efficiency but also help shape a justice system that remains both effective and trusted in the age of AI.
Learn More
For those interested in learning more, the full webinar recording and additional resources are available here:
📌 Webinar Recording: Building AI Readiness in State Courts
📌 Presentation Resources:
For more details on AI applications in legal assistance, visit:
🌍 NCSC AI Initiative
This content has been updated on 01/09/2026 at 9 h 51 min.