Artificial intelligence has quickly become part of the legal profession’s vocabulary, but its place in the day-to-day operation of a law firm remains less certain.
For many lawyers, adopting AI still means using a standalone tool for a discrete task—summarizing a document, conducting research or refining a draft—while the underlying workflow remains largely unchanged. As more firms describe themselves as “AI-native,” the distinction between adding AI and reorganizing a practice around it is becoming increasingly important.
Justin McCallon, CEO of StrongSuit, argues that a genuinely AI-native firm does more than give lawyers access to a collection of new tools. It connects those tools across the life of a matter, allowing the information produced during intake, discovery and research to carry forward into strategy and drafting. The objective, he says, is to automate repetitive work and large-scale information synthesis while leaving legal judgment, strategic direction and final review firmly with the lawyer.
That vision carries both promise and risk. Greater automation could allow smaller firms to handle more sophisticated work and compete with larger practices, but embedding AI throughout litigation also raises questions about confidentiality, accuracy, professional responsibility and oversight. The technology alone is not enough: firms must choose appropriate safeguards, integrate their systems and reconsider the incentives and processes that shape how lawyers work.
McCallon approaches the issue with experience extending beyond legal technology. In this interview with LegalTech.ca, he discusses what distinguishes an AI-native law firm, where human judgment must remain decisive, why smaller firms may have an early advantage and how the combination of capable lawyers and connected AI platforms could reshape competition in litigation.
“AI-native” is becoming a popular label in the legal sector. What does an AI-native law firm actually do differently from a conventional firm that has simply added a few AI tools?
JM: Most firms that say they use legal AI mean a lawyer has a chatbot open in another browser tab. They draft a paragraph, paste it in, get a suggestion, paste it back. That helps at the margins, but it adds a step instead of removing one. It’s why 85% of lawyers report using AI while 77% still say most of their work is manual.
An AI-native firm runs on one connected platform. AI touches every stage of the matter, from intake through the final filing, and each stage builds on what the last one produced instead of starting from a blank page. The StrongSuit platform is able to take a big chunk of that, but AI-native isn’t about just picking one legal platform. It’s about building a full, connected system.
If we followed a litigation matter from intake through research, strategy, discovery and drafting, where should AI participate — and which decisions must remain firmly with the lawyer?
JM: The goal is for AI to support every step of the matter, from intake through a full draft, so that your time is focused on judgment. At intake, it can turn a call transcript into an open matter and a populated case file. In discovery, it can review the record and surface the evidence that matters. In research, AI can pull from a full case database of precedential U.S. cases with good-law and anti-hallucination safeguards. In drafting, it can produce a first-pass brief in your voice and structure. Generally, AI should do the work that is repetitive and the work that involves synthesizing large amounts of information.
What stays with the lawyer is judgment, strategy, and the ability to shape everything around your key decisions. You can redirect the routing at any point, apply your judgment where the matter calls for it, tailor any individual step to the case, and fix the rough edges the first pass leaves behind. StrongSuit supercharges your judgment. It doesn’t ask you to accept whatever comes out the other end.
StrongSuit argues that AI-native firms can increase attorney output without sacrificing quality. What evidence supports that claim, and which metrics should firms use to determine whether AI is genuinely improving their work?
JM: Some of the clearest evidence is the gap in the industry data itself. 85% of lawyers use AI, but only 24% say a meaningful share of their daily work is actually automated, and only about a third of solo and small firms report any revenue lift from it. The tools are in the building. Most firms haven’t connected them yet, and they’re not effectively using the platforms they are paying.
Beyond the industry numbers, we hear directly from attorneys on the platform, close to every day, about where StrongSuit has tripled or more their speed to complete a big portion of work on a matter.
But again, StrongSuit is one part of becoming an AI-native firm, not the whole transformation. The platform can carry a matter from evidence to a polished draft. Getting the full benefit still depends on the firm building the workflows and habits around it.
Litigation involves confidential information, professional obligations and potentially serious consequences for inaccurate work. What safeguards and review processes are necessary before a firm can responsibly embed AI throughout a matter?
JM: Start with the platform itself. Look for SOC 2 Type II certification, anti-hallucination and good-law safeguards on every citation, and a commitment that client files are never used to train the models. Then look at how the firm uses it: review of the full tech stack before anything touches a live matter, and attorneys actually using the tools as designed, with every finding reviewed and approved before it goes anywhere.
But be careful not to be too risk-averse, too. It’s easy to treat “this could go wrong” as a reason to sit on the sidelines, but that misses what’s actually at stake. Proper use of AI platforms can triple your output, or more. The answer isn’t caution instead of adoption. It’s building the safeguards so you can adopt responsibly and still move.
Many firms are experimenting with separate AI products that do not necessarily work together. Is the greater challenge choosing the right tools, integrating them into a coherent system, or changing the firm’s underlying processes?
JM: All three matter, and firms that treat any one of them as optional end up stalled. But if I had to name the one that unlocks the other two, it’s building a coherent system. When the tools are well-connected, changing the firm’s process gets a lot easier, because the system drives efficiency and adoption becomes easy. A disconnected stack makes process change a much harder sell.
That’s also the case for platforms over point solutions. StrongSuit carries documents, facts, and findings forward across evidence review, research, and drafting, so the firm isn’t rebuilding context or retraining people at every step.
You previously led transformation initiatives at AT&T that reportedly produced more than $100 million in annual savings. Which lessons from that experience translate to law firms — and what is fundamentally different about transforming a legal practice?
JM: At AT&T, the highly qualified legal team wanted to spend more of its time on actual legal work (rather than managing outside counsel), and the organization was incentivized to run efficiently. Those both pointed the same direction, and it undoubtedly helped the transformation.
Law firms don’t always have that same alignment. Efficiency matters, but the connection between efficiency and what gets rewarded is looser, especially under hourly billing, and partners at larger firms tend to be focused on the current quarter rather than a multi-year shift. That makes the change management heavier lifting in a firm than it was at AT&T. But the underlying principles carry over directly: change what gets measured and rewarded, not just what tool sits on someone’s desktop, and get the incentives pointed at the same outcome you’re trying to reach.
Why might small and mid-size firms be better positioned to become AI-native than larger firms, and what disadvantages could prevent them from making that transition successfully?
JM: Every firm, regardless of size, is starting from a present state that needs a real transformation to get to AI-native. Nobody skips that work. But smaller firms have less to rip out to get there. A 12-lawyer firm doesn’t have decades of legacy systems and layers of bureaucracy standing between a decision and a change taking effect. A larger firm does, and that’s what slows it down.
The disadvantage for smaller firms is resources: no innovation team to evaluate vendors or run a formal change program on top of a full docket. Without a deliberate plan for training and adoption, that speed advantage can go unused. But the starting line is closer for a small firm, and that matters.
If legal-tech investment continues flowing toward AI-native platforms and service providers, how could that reshape competition in litigation — and what role do you expect StrongSuit to play in that changing market?
JM: I think this wave benefits nearly everyone in the chain: lawyers, platforms like StrongSuit, the model companies, the infrastructure underneath all of it, clients, and society more broadly. That said, there’s real volatility in how it plays out, and steering it well is a shared responsibility across the industry, not something any one company gets to decide alone.
The comparison I keep coming back to is advanced chess in the early 2000s, when teams pairing strong players with AI consistently beat both grandmasters working alone and AI working alone. I think litigation is heading toward the same result. The firms that come out ahead won’t be the ones betting on AI replacing lawyers, or the ones ignoring AI altogether. They’ll be the ones that pair strong legal judgment with a strong platform. That’s the market StrongSuit is building for.