Evaluating and Choosing Your Firm’s Legal Tech Stack

Until extremely recently, the legal industry has not been on the forefront of a lot of the technological development we’ve seen over the past few decades. And there are a couple of reasons for that.

One is cultural: Lawyers are, by nature, somewhat conservative, which is a good thing. Lawyers need to be careful and thoughtful about managing risk. The “move fast and break things” attitude that’s so common in tech doesn’t really work in law. Lawyers are trained to uncover risks while preventing mistakes, so caution is built into the DNA of the profession.

But there’s also a structural reason. Lawyers work in words, while data processing works best with numbers. And until very recently, technology just hadn’t caught up to the ability to manage legal data in the form of words in a way that was nuanced enough to make real changes. Legal work happens in natural language, which is fluid and deeply contextual; the uneasy task of turning that language into data sufficiently structured to process was prohibitively expensive, overly limited in scope, or (typically) both.

This is the real shift: for the first time, AI can analyze and interpret legal text at scale, making the large volume of legal data more usable. Moreover, the outputs of this modern AI are non-deterministic, meaning that like humans, they can produce different output given the same input. This is because their underlying structure doesn’t require them to follow if/then logic, but rather generates outputs through probabilistic reasoning. As a result, it can produce results that look a lot like human judgment and help power legal work such as research and document automation.

The advent of this level of sophistication in computing has opened the doors of AI to attorneys. What used to be expensive and difficult to apply in law has become much more accessible. Suddenly, we can imagine solutions that were off the table just two or three years ago.

Still, as an industry, we’re behind others when it comes to adopting new technology. So, the question isn’t whether lawyers can use AI and automation, but it’s how to do it in a way that actually works for you and your firm.

Step One: Identify the Right Problem

Most people start with the solution: “Let’s look at the tech solutions out there and pick one for us.” But that’s putting the cart before the horse. The first step is figuring out what problem you’re trying to solve.

Take a look at your firm’s operations and identify any sources of friction. Ask yourself:

• What’s bogging down the firm?
• Where are we doing the most manual work, especially at scale?
• What could be automated that isn’t?

Maybe you’re spending too much time on document review. Maybe your legal research process is scattered and unstructured. Whatever it is, define any bottleneck clearly enough that you could explain it to an outsider. I call this the “explain it to your mom” test. If you can’t describe the problem in plain language that a layperson could understand, you haven’t defined it clearly enough.

Then, quantify it. How much time or money is this actually costing? You can’t prioritize what to fix until you translate it into value for your firm - so every potential investment in technology should come with an estimate as to how it will improve your firm’s P&L. That’s how you decide what’s worth tackling and what you can live with for now.

The final piece to consider is whether and how AI might be useful in solving this problem, vs more “traditional” technology. Agentic AI systems can act on your behalf, not just generate output. That means part of choosing your problem is deciding where and to what degree it makes sense to delegate judgment. Do you want AI to only generate recommendations, which humans validate, or will you allow it to take limited autonomous action within guardrails? Clarifying this early will guide what kind of technology you choose and how you implement controls.

Step Two: Find the Right Solution

Once you’ve defined the problem, then you can start looking for solutions. And as you do that, think about three things:

1. People: How open is your team to new technologies? How capable are they of adopting them? Do you have a team in place who can successfully implement new technology?
   
2. Processes: What workflows need to change so the new technology actually delivers value?
   
3. Technology Stack: How does this new tool fit with what you already use, from Microsoft Word to your case management software?
4. Vendors: Do your vendors truly understand your challenge and the outcomes you’re aiming for? What level of support do they offer, and is that support suited to your organization’s needs? Compatibility and partnership matter just as much as product features.
   
   

Tip: Throughout the tool selection process, make sure to give your coworkers or employees a say, as they are the end users. Consider firm-wide polls to gather information on which tools will actually benefit everyone.

Step Three: Implement New Tools

Every technology implementation I’ve seen goes through three phases:

1. Design. The early stages of matching a new tool or solution to what you currently use are critical to its eventual adoption and success. Every tool you buy is going to require some customization to match your firm’s work. You need to feel ownership over the solution. You’ll likely need to adjust how you work to accommodate the tool as much as the tool adjusts to you. It’s a push-pull process.
   
   
2. Configuration. This is where the vendor starts to build the system to your requirements. Things will break. Processes you thought you understood may behave differently in practice. Go in knowing this part will be rocky, and work with your vendor as a team to troubleshoot. Small tests and “service rehearsals” can go a long way toward uncovering problems before they become too big.
   
   
3. Launch. Once the tool is nearing ready to deploy, your challenge shifts from technical problem solving to managing and promoting adoption. Here, communication matters most. Make sure your staff know what’s expected of them, what’s changing, and how to get help. Whether it’s weekly meetings, office hours, or firmwide updates, communication needs to be a key workstream. You may also want to implement an AI policy to help guide implementation.

Listen to your team where things are going wrong, and work together to come up with solutions. Swarming problems in the early days of launch establishes confidence that they will get fixed, which serves as a virtuous cycle of communication and adoption.

A practical tip: Identify early who your firm champions will be: these are the tech-forward employees who are excited about the problem you’re solving and will help ensure the implementation process goes smoothly. Give them extra training so they can help their teammates and build internal leadership. This is a great way to upskill more junior team members and build expertise from within. Without designated champions, adoption becomes slower and less consistent, and the value of the new tool may never fully materialize.

It’s an exciting time to be exploring technology for legal applications, perhaps the most exciting so far in my 10+ years working in legal tech. While the scope of what can be accomplished through technology is expanding, the fundamentals of successful implementations haven’t changed:

1. Laser focus on understanding and driving quantifiable profit and loss improvement through technology investment
2. Thoughtful design of the target state and a practical plan of how to get there
3. Careful design for and managed adoption by the people who will actually be using the software

Getting these three aspects right is crucial to unlocking the substance of the modern AI revolution. Firms that approach AI adoption strategically will not just catch up to innovation, but help redefine how legal services are delivered.

This Might Interest You:

• 10 Best AI Tools for Lawyers in 2026
• 14 Legal Tech Conferences Happening in 2026
• What is Legal Intelligence?