Why Ungoverned AI Is a Legal Department's Biggest Risk and What to Do About It

There is no shortage of anxiety about AI in legal. Some of it is overblown, and some of it is entirely legitimate. The challenge for legal ops professionals right now is figuring out which is which — because the answer determines whether you approach AI as an opportunity or spend the next three years watching from the sidelines while the pressure to modernize keeps building.

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This comes with an important caveat — making AI work for you requires knowing exactly what you're asking it to do, and building the guardrails to make sure it does only that.

Understanding the Risks of AI in Legal

The anxiety around AI in legal contexts tends to cluster around a few specific fears. Hallucination — the tendency of AI models to generate confident, plausible, and entirely fabricated responses — is a real and documented risk, particularly in a profession where a false case reference can have serious consequences. 

Data security is another. When you feed a model information about your matters, clients, and strategies, where does that data go? Who can use it? Can it be used to train the model that your competitors are also using? These are reasonable questions that deserve clear answers before any AI tool goes anywhere near sensitive legal work.

How to Build Governance, Not Barriers

In our recent webinar, Ridhima Mohla (VP of Customer Success at Checkbox) and Joy Thorpe (Director of Strategy for the Legal Centre of Excellence at Altria) explored exactly this challenge. At Altria, the response to these concerns wasn't to avoid AI. It was to build governance around it. This included:

• An AI governance board,
• AI policies across the organization,
• Contract clauses with vendors explicitly prohibiting the use of Altria's data to train external models, and
• Significant investment in staff education (e.g. AI training per person that covers prompting, ethics, risk awareness, and the basics of how these systems actually work).

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What Does Controlled AI Look Like In Practice?

A well-governed AI deployment in legal isn't a general-purpose tool pointed at sensitive work and left to run. It's a system built with specific parameters — scoped to defined tasks, trained on curated and maintained content, and designed to recognize the boundaries of its own competence. When it encounters something outside those boundaries, it should say so, and route the user accordingly.

The hallucination risk that makes legal professionals nervous about AI is often a consequence of deploying it without sufficient constraints. An AI agent that knows what it doesn't know, and is built to escalate rather than fabricate, is a fundamentally different proposition from one given broad access and minimal guardrails.

For legal departments that are understandably cautious, this is the path in. Controlled AI doesn't require abandoning the professional standards that make caution necessary. It requires applying those same standards to the design of the system itself.

The 80/20 Opportunity

If a well-designed AI agent can handle 80% of routine queries and requests (i.e. FAQs, document retrievals, intake collection, standard responses), then your lawyers and paralegals are freed to focus on the 20% that genuinely requires their expertise. 

That's basically AI doing what technology has always done at its best: taking the repetitive, low-value work off the plate of the people whose time is too valuable to spend on it.

The main goal for legal departments is to be able to truly focus on providing legal advice. AI, used well and governed carefully, is one of the most powerful tools available for getting there. Used carelessly, it's a liability. The difference lies almost entirely in the quality of the thinking that goes into the implementation and in asking, before anything else, what problem you are actually trying to solve.

Key Takeaways

The legal teams getting AI adoption right are the ones investing as much in how they implement AI as in what they implement. 

• The risks around hallucination and data security are real, but manageable with proper governance. 
• Policies, training, vendor safeguards, and clear parameters are what make it possible to move forward with confidence. 
• Before deploying anything, it pays to scope your AI carefully. 

The corporate legal teams seeing genuine results are the ones who asked what they were trying to solve before they chose a tool. Do that well, and the 80/20 opportunity becomes very achievable. 

If you're ready to explore what this could look like for your team, book a demo to see how leading in-house legal teams are implementing legal AI tools with the right guardrails in place.