There's a common assumption that guardrails and innovation sit on opposite ends of a seesaw, and it may often seem that every policy or training requirement is a drag on progress. The data tells a different story, however. The organizations struggling most aren't the ones with too many rules around AI; rather, they're the ones without enough of the right rules.

Using AI in government and legal settings must be done responsibly. It carries real upside, including productivity, efficiency, and better public access to services, as well as real risk, including unsanctioned shadow AI, data leaks, and the consequences of poor training. Responsible AI use lives at the intersection of that risk and reward, and recent research shows how far most organizations still have to go to get there.

Adoption is moving faster than readiness

A new report from the TRI/NCSC AI Policy Consortium for Law & Courts, Staffing, Operations and Technology — A 2026 Survey of State Courts, found that about one-quarter of respondents say their court has implemented an AI project, or plans to implement one within the next 12 months. That's real momentum, but the infrastructure hasn't kept pace: only 13% of respondents say their court has assessed the quality of the data feeding their AI tools, and only 13% have built a formal AI-literacy strategy. Just 11% respondents say AI training is both provided and required for their role.

Meanwhile, the report estimates responsible AI use in courts could save an estimated 9.2 hours per person over the coming five years — representing an extra full day of work — without expending additional resources. However, this gain is available only to courts that build the guardrails to reach it safely.

Policy gaps, not policy itself, are the real barrier

This pattern extends well beyond the courts. TRI's recent 2026 Government Legal Department Report found that almost 1-in-5 respondents (19%) say a lack of an AI policy has become a barrier to adopting new technology. In fact, it isn't the presence of a policy that slows teams down, it's the absence of one, because without clear rules, teams hesitate and promising tools go unused.

And Thomson Reuters' 2026 Future of Professionals Report adds another dimension: 57% of professionals say they lack access to tools that meet professional accountability standards, the kind where errors carry real consequences. In courts and government agencies, a mistake can affect a filing deadline, a benefits determination, or someone's due-process rights.

Clearly, professionals aren't asking for less oversight of AI, they're asking for enough of it to trust the tools in front of them, and to know those tools will let them fulfill their responsibilities to the public rather hindering that mission.

Building guardrails for responsible AI use

Effective guardrails don't need to be complicated. They need to be clear, consistently applied, and built before adoption accelerates further — and not after something goes wrong. A few foundational guardrails can make an outsized difference, each answering a specific gap the survey data has already identified:

• Training for all employees — Everyone touching an AI tool, not just technical staff, needs a baseline understanding of what it can and can't do, and where its limits are. The State of the Courts Report notes that only 11% of respondents say training is both provided and required for their role, the largest gap in the data. A short, mandatory course covering the tool's purpose, its failure modes, and when to escalate a concern closes most of that gap on its own.

• Role- and application-specific training — A clerk, a caseworker, and an IT administrator each use AI differently and face different risks. Generic training misses the details that matter to each job. For example, a clerk needs to verify a citation; and a caseworker needs to know what data should never touch a public-facing tool.
• Data security and privacy training — Employees should know what data can and can't be entered into an AI tool, and why. This answers the data-quality gap in the State of the Courts Report, that showed only 13% have assessed the data feeding their AI systems.

• IT supervision and oversight — A clear reporting line between IT, legal, and program staff ensures someone owns the decision when a new AI tool is proposed, and gives leadership a documented trail if something goes wrong. It's also the most immediate relief for the 19% of the respondents to the Government Legal Department Report that cited a lack of AI policy as a barrier. A governance structure that already knows who signs off on new tools doesn't have to build one from scratch under pressure.

Each guardrail is deliberately simple, and that's the point. Complexity is what causes policies to stall in draft form for months while AI adoption moves ahead without them.

The path forward

None of this requires government agencies or courts to slow down. It requires them to be deliberate, and to treat guardrails as an accelerant rather than a checkpoint. An agency that trains its people, secures its data, and keeps a clear line of sight into how AI is being used isn't falling behind in the adoption race — it's building the kind of program that can scale without incident.

However, those agencies still waiting for a perfect AI policy before acting are missing the more urgent lesson: The risk isn't in moving forward with guardrails in place, it's in moving forward without them. Courts and agencies that put these four guardrails in place, even in basic form, will be better positioned to capture the work hours that AI can save, close the accountability gap professionals have flagged, and give the public confidence that the tools serving them are used with the same care they expect from any government process.

Clearly, the technology isn't waiting, and neither is the public's expectation of accountability.