Strategies for Integrating AI Into Legal Operations

AI tools are everywhere right now, and legal teams are understandably curious. But for legal ops professionals, this isn’t about trend-chasing. It’s about identifying real, measurable opportunities to ease the pressure on legal and improve operations.

We’ve all seen teams get excited about a tool without doing the groundwork, only to end up with something expensive that no one uses. The most effective legal ops leaders resist the urge to jump in without a plan. They assess their environment first, get alignment across stakeholders, and focus on use cases that are high value and low risk. That’s how we should be thinking about AI.

Here’s how to get started:

Prioritize Use Cases Based on Pain Points 

No tool, AI or otherwise, will be effective if you haven’t done the readiness work to identify where your team’s time is actually going. We recommend categorizing day-to-day work into four quadrants using a modified version of the Eisenhower Matrix, or what we call the Value Exercise. This helps identify where automation can drive the most meaningful impact.

Here's how to think about it:

1. High Urgency, High Impact 

These are mission-critical tasks with deadlines and risk attached. EOQ deal support is a classic example. These often involve cross-functional collaboration and can’t afford mistakes. While AI may support these tasks in the future, we don’t recommend starting here.

2. Low Urgency, High Impact 

These tasks are often the tasks that could be hugely beneficial to the organization, but because there’s no immediate deadline, they often get deprioritized. Good candidates include:

• Drafting playbooks for standard contracts like NDAs or DPAs

• Creating internal FAQs or decision trees to support intake

• Automating repeatable first-pass work, like summarizing contract terms

These types of tasks build infrastructure that frees up time without creating new exposure. And even if AI isn’t used to solve for these tasks, solving tasks in the other categories will free up time for the team to tackle these important initiatives.

3. High Urgency, Low Impact 

These tasks come with deadlines but are not especially strategic. They tend to soak up time because someone else is waiting on them. Think of things like:

• Fielding intake questions manually

• Following up on missing information

• Responding to repetitive status check-ins

This is another area where AI can be valuable, especially when paired with a strong routing or intake solution. Just because something is urgent doesn’t mean it requires a lawyer.

4. Low Urgency, Low Impact

This is the noise. These are legacy tasks that may have served a purpose at one point but are now low value and often go unquestioned. You might be manually maintaining a spreadsheet no one looks at or sending emails that no longer need to happen. These are good candidates to eliminate entirely—or at the very least, automate and deprioritize.

Pilot in the Low-Risk, High-Gain Zone

Start with work that’s clearly worth automating—something your team is stuck doing it over and over again. Look for places where your team feels like they’ve become the bot. If they’re answering the same policy questions ten times a week or manually routing every intake request, you’ve found a candidate.

A few high-value pilot areas:

• An internal bot to handle FAQs and policy questions. Whether it’s “Am I allowed to sign this?” or “What’s our T&E policy?”, a simple tool that pulls answers from your existing documentation can save hours of legal time and reduce frustration across the business.
  
  

• A personalized legal writing assistant. Instead of generating emails, slide content, newsletters, or memos from scratch, give your team a tool that pulls from your own knowledge library with your own style to accelerate drafting. This isn’t generic automation. It’s a way to help the team start faster and stay consistent.
  
  

• Intake triage and routing. A lightweight AI layer can direct requests to the right person, flag missing information, and cut down on back-and-forth.
  
  

• Status updates. If your team spends half the day fielding “Where’s my contract?” pings, that’s a sign something should be automated.

You don’t need to start big. Just pick something repetitive that’s draining time, automate it, and measure what changes.

Measure the Impact and Iterate

If you're not tracking the impact of your AI experiment, you’re guessing. And you won’t get continued support without data. Start with a baseline. For example, how many NDAs does your team process per month, and how long does it take?

Then track again after implementation. Ask:

• Is turnaround time improving?

• Are fewer requests being escalated?

• Has legal had more capacity for higher value work?

We’ve seen teams save hundreds of hours and millions of dollars per year by running pilots to automate tasks like document generation or intake and triage. But you need numbers to prove it. Metrics give you credibility and help build the case for future investment.

Bring in Stakeholders Early

Legal ops sits in a unique spot. You work closely with legal, but also partner with IT, procurement, compliance, and the business. That’s an advantage.

Bring people in early. You’ll need IT to assess tools, legal to weigh risk, and business users to make sure the solution is usable. Start with their pain points, not just your own. If you can show how this helps their team, you’ll get much better support and adoption.

You’ll hear concerns like “We’ve always done it this way,” or “Legal already handles this.” You can overcome that if you’re clear about the value and involve the right people upfront.

Invest in Skills, Not Just Tools

AI isn’t going to replace lawyers. But lawyers who don’t evolve will absolutely be replaced by the ones who do.

That doesn’t mean your legal team needs to spend their days learning prompt engineering. Think of it like building a website. Sure, anyone can do it, but should they? That’s where you come in.

Legal ops should be taking the lead on AI strategy. This is our lane. The tech is still evolving, and now is the time to learn it, experiment with it, and shape how it fits into your team’s workflow.

Where you invest will depend on your resourcing and your appetite for risk. In our experience, most legal departments don’t need custom AI tools to get started. A well-built custom GPT or Gemini bot (Gem) can go a long way toward solving your team’s current pain points. Start there. When you’ve hit the ceiling of what those tools can do, and you’ve built the muscle internally, that’s when it makes sense to move to a more advanced solution.

AI and the Future of Legal Ops

Legal ops teams are in the best position to lead AI adoption. Not to follow someone else’s roadmap, but to define it.

You already operate at the intersection of legal, business, and technology. You understand the workflows. You see where time is wasted. That puts you in the right seat to identify what’s worth automating and what isn’t.

Start by solving real pain points. Focus on low-risk, high-impact areas where the team feels stuck. Use tools that are already available to you, like custom GPTs or Gemini bots. Most teams can solve a lot without major investment if they know where to look.

This isn’t about trend-chasing or big spending. It’s about being deliberate and strategic. You don’t need to wait for legal leadership to ask. You can show them what’s possible.

AI is not a threat to legal ops. It’s a tool to amplify your impact. Use it wisely, and take the lead.