Most firms talk about AI adoption like it’s a purchase. Buy the tool, turn it on, done. I push back on that idea every chance I get. Becoming an AI-native law firm isn’t a single event. It’s a longer journey, and most firms are only at the start of it.
Actionstep’s Chief Product Officer, Triona Buckley covered the shift from the practice of law to the business of law in an earlier piece, “AI for Law Firms: Myths and Realities Explained.” Something law firms need to keep in mind over the next few years, is why the difference between bolted on AI and native AI matters so much, and why mid-market firms may be better positioned for this shift than people assume.
Becoming AI native is a journey, not a purchase
The legal industry heading toward two things happening at once. On one side, lawyers will keep using AI tools personally, the same way people across every industry now lean on tools like ChatGPT and Claude for their own work. On the other side, firms will be retooling at the platform level, building the standardized data foundation that AI needs to be useful.
Right now, almost everyone is focused on only one of those two dimensions, either the personal productivity side or the platform side, rarely both. The firms that focus on both will have the real AI advantage. As individual AI use becomes more common in law firms, and firms rebuild their platforms around AI at the same time, those two threads start to come together, and the day-to-day work of a lawyer begins to shift. Routine typing and research get handled by the tools, which frees lawyers to spend more of their time advising clients, exercising judgment, and building relationships. That shift undercuts the doom and gloom predictions about law firms disappearing. Five years from now, those predictions will look less like a real outcome and more like a trivia question nobody thought to ask twice.
The difference between bolted on AI and native AI
One of the points we keep coming back to is that AI needs context to be useful, and context requires access to the firm’s full data, not just one part of it. A bolted-on tool typically connects to a single system and does one narrow thing well. A native AI layer sits on top of the complete practice management system, so AI has visibility into a matter, a client’s history, and firm policy no matter where someone is working.
That difference has a direct financial effect. When AI operates with complete context, it can recommend or even execute work based on what’s worked for the firm in the past, or how the firm set up work to get done, then explain its reasoning for review. My honest expectation is that, done at scale, native AI pushes the unbillable hour toward zero and increases the value of each billable hour. Firms get more done per hour of work. If that plays out the way I think it will, it’s a rare case where both sides win: firms get more profitable, and legal services get less expensive for clients.
Native also matters for a reason that has nothing to do with productivity: safety. One of the advantages of a native AI layer is that you can use AI against it from outside the system too. Someone can go use a tool like ChatGPT, and if it’s working through an AI-native layer, it inherits the same governance and guardrails Triona talked about, so your people can use these tools safely rather than operating in the wild west. That’s a big part of why AI needs to be built in at the base level of the platform, not added on the side. A bolt-on might let you do one thing well, but it also leaves you exposed everywhere it doesn’t reach, and stuck in your old ways everywhere else.
Why mid-market firms need a partner, not a hire
Large firms can often brute force their way into AI adoption by investing heavily in tools and specialized talent. Mid-market firms usually can’t. Hiring one person to lead an AI strategy is fragile. If that person leaves, the firm is back to square one.
The path forward for mid-market firms is to run through platform partners rather than internal hires. A modern, AI-capable platform can carry more of that weight than a solo internal expert ever could, and a growing network of consultants is already emerging to help mid-market firms put these tools to work.This shouldn’t be thought of as a disadvantage. It’s simply a different, and often easier, path than the one larger law firms are on.
There’s also an upside here that doesn’t get enough attention and that’s talent. A mid-market firm that invests in AI-native tools now and can offer new associates a genuinely better day-to-day with less of the mundane work, access to modern tools, and a real quality-of-life difference. It is going to look progressive to the next generation of graduates. That gives mid-market firms a real shot at attracting talent away from big firms, where the tooling and the competition for attention can be a lot less favorable.
Start with one problem, not everything at once
Firms need their data consolidated, cloud-based, and structured well enough for AI to come in and use it properly, and no matter which AI tool firms adopt, a patchwork of disconnected, on-premises tools will hold them back from becoming AI-native.
So first, get your data house in order first because there’s no way around it.
But don’t try to fix all of it at once. Pick one problem that would make the biggest difference to the people doing the work and solve that first. The early win builds momentum, and the next opportunity tends to become obvious.
None of this happens without leadership driving it from the top, with real commitment, not as a side project for whoever happens to be curious.
That same thinking shapes how we build AI into the Actionstep platform. We’re not interested in sprinkling in isolated features. We’re building one layer that connects the work a firm has already done to the work still ahead of it, all within Actionstep so firms don’t have to choose between moving fast and moving carefully.
See what’s possible when AI works with your firm’s expert judgment, not in place of it. Talk to our team to learn how Actionstep can help you prepare for the future of law.
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