AI is now embedded across commercial legal practice. Research, drafting, matter management, and workflow automation are increasingly supported by AI-native tools, and firms are investing heavily in these platforms to improve efficiency, manage risk, and scale their operations.
But pro bono legal work has not followed the same trajectory.
Despite being a professional obligation and fundamental to access to justice, pro bono is still managed largely outside the core legal technology stack. For many firms and in-house teams, the intake and allocation of matters, case management, and impact reporting rely on spreadsheets, email chains, static webpages, or basic SaaS tools. These systems cannot scale to meet demand and do not reflect how legal teams actually deliver pro bono work.
As a result, pro bono is often met with a fragmented and underpowered infrastructure, even as participation continues to increase significantly. Lawyers are doing more pro bono work than ever before, yet the tools supporting that work remain secondary to those used for billable matters.
This distinction is becoming increasingly difficult to maintain and justify.
An outdated operating model for pro bono work
Pro bono work often operates across a complex, interconnected network of stakeholders, including external organisations, partners, lawyers, volunteers, and administrative staff. Matters frequently involve specific eligibility requirements, strict timelines, and ongoing coordination and reporting obligations.
Despite this complexity, pro bono is often supported by the least sophisticated technical infrastructure, with systems that cannot sustain growing demand over time. Pro bono coordinators must bridge gaps across multiple tools, including spreadsheets, long email chains, outdated portals, and static listing pages, while lawyers encounter friction when trying to participate. This creates a barrier to involvement in work that is meaningful, yet ultimately voluntary.
Firms also struggle to gain a clear and reliable view of their impact. When generalist legal platforms are repurposed for pro bono, critical details are often lost, increasing administrative burden and reducing time available for substantive legal work.
A blind spot in legal AI adoption
AI in the legal domain has largely been deployed where the return on investment is most visible. Improvements in research efficiency, drafting speed, and workflow optimisation for billable matters offer clear and immediate benefits.
Pro bono, by contrast, has often been treated as peripheral to core legal operations rather than as a domain with its own operational complexity and risk profile. In reality, the opposite is true. Pro bono work demands robust systems because it involves vulnerable clients, sensitive information, and complex coordination.
Managing each stage of the pro bono lifecycle on separate platforms creates a greater administrative burden, puts strain on already resource-constrained teams, and reduces the time available for meaningful, client-facing work.
Building the foundation for scalable pro bono efforts
If AI is to support pro bono effectively, it must be built on the same core principles that underpin modern legal platforms. Pro bono work benefits from structured intake, intelligent opportunity matching and allocation, automated workflows, robust reporting, and transparent, auditable processes.
When these foundations are in place, AI can reduce administrative friction that has historically slowed pro bono delivery. Tasks that consume time but add little value can be automated, allowing lawyers to focus on substantive legal work. Matching lawyers to pro bono matters can become more precise, and oversight and reporting can shift from reactive to real-time.
Crucially, this does not mean treating pro bono as identical to commercial work. It means recognising that pro bono is equally deserving of sophisticated infrastructure, while respecting its distinct requirements.
The future of legal AI supports access to justice
The real value of expanding legal AI into pro bono work lies not just in efficiency, but in impact. Every administrative task that can be streamlined or automated returns time to client service. Every improvement in coordination increases the number of matters that can be supported. Every insight generated through structured data strengthens the case for sustained investment in access to justice.
AI does not replace the human judgment, empathy, or expertise that pro bono work requires. Rather, it creates the conditions for that expertise to be applied more widely. These tools allow legal teams to focus on complex legal judgment instead of administrative overhead.
As legal AI becomes embedded in the fabric of legal work, what will matter is whether systems are designed to reflect the full scope of practice and streamlining pro bono work cannot remain an afterthought. It requires dedicated infrastructure and human-centred design, with systems that deliver the same level of seriousness afforded to other areas of legal operations.
By building pro bono systems with the same intention and design as commercial legal operations, AI can unlock greater impact, expand access to justice, and ensure that lawyers’ expertise is applied where it matters most.
