Five Questions Every GC Should Ask Before Deploying AI in the Legal Department

As a client once told us, “Litigation is a business problem stuck in the courtroom.”

It’s expensive, unpredictable, often irrational, and always disruptive to the people and operations that actually generate revenue. Yet the way most organizations manage litigation has not fundamentally changed in decades. We’ve added technology, sure, but often in service of the same outdated workflows. The process got faster, but the thinking has not.

Now the pressure is intensifying from a new direction. Boards and C-suites want to know what legal is doing with AI. If you haven’t deployed it yet, the assumption is you’re behind. Budget conversations increasingly come with an implied condition: Show us how you’re leveraging AI, or lose budget.

But here’s the problem with responding to pressure instead of a plan. Efficiency is a valid goal, but it cannot be the ultimate one. Getting to the wrong answer faster doesn’t help anyone. Automating a broken process just makes it break at scale. Before deploying artificial intelligence (AI) in the legal department, leaders need to pause long enough to ask better questions.

1. Do you understand the real problem?

This sounds obvious, and that’s exactly why it gets skipped, particularly when timelines are short and budgets are tight. Someone identifies a pain point, and the instinct is to solve it. But surface-level symptoms rarely tell the whole story.

A legal department might look at rising outside counsel costs and conclude the problem is rates and therefore the solution is discounts. But the real issue could be something entirely different: a lack of early case assessment, misalignment with business priorities, or a culture where disputes escalate because there is no internal triage process. AI can help solve each of those, but only if you have diagnosed the correct problem. Otherwise, you risk implementing a tool that efficiently manages the wrong issue. That is not progress. It is simply a more organized version of the same mess.

2. Are the right people at the table (and being heard)?

Technology decisions in legal departments often happen in a small room, with the general counsel (GC), perhaps a legal operations leader, and a vendor. That is rarely enough. The people closest to the work—paralegals, litigation support teams, contract managers, and outside counsel—often understand friction points that leadership never sees. But being in the room and being heard are two very different things. If the most junior person has the clearest insight but does not feel safe sharing it, the organization has the right people at the wrong table. Collaborative decision making is not about slowing progress. It is about avoiding expensive mistakes.

3. Can you envision what a real solution looks like?

Too many AI deployments begin with the technology and work backward toward a problem. That’s the equivalent of buying a tool and then walking around the house looking for something to fix. Instead, start with the outcome you actually want. What would it look like if early case assessment took hours instead of weeks? What if patterns from hundreds of matters surfaced risks before disputes ever formed?

Consider how Waymo’s autonomous driving works. Every mile driven feeds data back into a central intelligence layer. Every unusual situation, a pedestrian crossing unpredictably, a sudden braking event, becomes part of the system’s collective learning. One car learns something, and every car gets smarter. Engineers call it fleet intelligence.

That same shift is beginning inside legal departments. AI can connect data across contracts, disputes, compliance systems, regulatory filings, and historical litigation records. Every negotiation becomes a data signal. Every dispute becomes a learning event. Over time, the legal department stops operating as a collection of isolated matters and begins functioning as a continuous intelligence network for the business.

4. Have you defined the elements of success?

If you cannot define success before deploying AI, you will not recognize it afterward, and you certainly will not be able to defend the investment.

Success metrics should go beyond cost savings. Consider measuring time-to-resolution accuracy, speed of early-case assessment, reduction in outside counsel revisions, consistency in matter management, internal client satisfaction, and early detection of legal and compliance risks. The goal is measurable operational improvement, not an impressive demo.

5. Where are the risks?

Every GC is trained to spot risk, so apply that instinct here. What happens when the AI gets it wrong? Who reviews the output before it influences a decision? What’s the data security posture of the platform? How does the tool handle privileged information?  These questions are not reasons to avoid AI.

The organizations that will struggle aren’t the ones who move slowly; they’re the ones who move fast without asking what could go wrong. Build in checkpoints and assign accountability, while remembering that AI outputs are only as good as the judgment applied to them.

Bonus question: How will AI impact your role?

This is the question many general counsel (GC) consider privately but rarely discuss openly. AI will not eliminate the role, but it will reshape it.

As AI systems generate more insight, someone must still decide what those insights mean for the business. Algorithms can surface patterns, flag risk, and model scenarios, but they cannot decide how much risk an organization should take. That remains a leadership decision. In many ways, AI elevates the GC role rather than diminishing it, positioning the GC as the executive who translates legal intelligence into business strategy.

The future of legal operations is not about choosing between human judgment and artificial intelligence. It is about designing systems where both work together. AI is a force multiplier, but only when there is something worth multiplying.

Start with the questions. The answers will follow.