Four Questions to Evaluate Your Firm’s Agent Governance
As legal AI agents become part of everyday practice, four questions can help firms evaluate whether their governance framework is ready.
AI agents are moving from pilots to production in legal organizations. According to new research from RSGI, 68% of law firms and in-house legal teams are already deploying AI agents, with more than one in five law firms running 50 or more agents in production.
As firms expand from AI assistants to agents that can execute multi-step work, governance becomes less about individual prompts and more about defining the boundaries within which agents operate. The good news is that firms don't need an entirely new governance framework. The controls they've already built for AI assistants provide a strong foundation — but they need to be extended to govern agentic work.
A useful way to evaluate whether your governance framework is ready for agents is to ask four questions.
1. Does every agent have clearly defined access boundaries?
An agent's capabilities are defined not only by its underlying model, but by the information and systems it can reach. Governance begins by defining the scope of that access. Which document repositories should an agent search? Which knowledge bases, research platforms, or matter files can it use? Beyond information, what tools or downstream systems can it interact with?
Equally important is determining what the agent is permitted to do with that access. Some workflows may allow an agent to retrieve and analyze information freely, while others may require human confirmation before accessing certain systems or moving work forward.
The goal isn't limiting access, but to ensure agents operate within the same permissions and boundaries that already govern legal work.
2. Have you defined where agent autonomy ends and human judgment begins?
Unlike traditional AI assistants, agents don't simply generate information, they perform work. That raises an important governance question: Where should autonomy end and human judgment begin?
Many firms may be comfortable allowing agents to perform research, summarize documents, extract terms, or prepare first drafts without interruption. Other actions naturally call for lawyer review before proceeding. Examples might include:
- Sending communications outside the firm
- Updating systems of record
- Finalizing documents
- Taking actions that create legal, ethical, or business consequences
Every firm will draw these boundaries differently. The important step is explicitly defining which actions agents may perform independently and where human approval remains mandatory.
Extending Governance to Legal AI Agents
How governance evolves as legal AI agents take on more autonomous work.
3. Can lawyers meaningfully review and supervise agent execution?
Governance doesn't stop once an agent begins executing a workflow. Because agents operate across multiple steps, firms should think about how lawyers remain engaged throughout the process, not just at the end.
Effective supervision may include reviewing an agent's proposed approach before execution, validating the sources it relies on, providing feedback during the workflow, and carefully reviewing outputs before they are relied upon or shared.
Comprehensive logging also becomes increasingly valuable. Visibility into an agent's plans, actions, sources, and outputs strengthens auditability while giving lawyers greater confidence in how work was completed. Rather than overseeing every intermediate action, the objective is to ensure meaningful human judgment remains in the workflow wherever it matters most.
4. Who governs the agents themselves?
As organizations adopt more agents — and eventually create their own — the governance conversation expands beyond who can run an agent. It also becomes important to ask who can configure one.
Publishing an agent effectively defines a workflow that others will rely on. That makes deployment itself a governance decision.
Many firms will find that existing principles around role-based permissions, administrative approval, and change management provide a useful starting point. The same governance disciplines used to approve new software or knowledge assets can also help determine who is authorized to create, modify, or publish agents across the organization.
Preparing Your Governance Framework for Agents
Across all four of these questions, the common thread is that governance becomes more proactive.
Instead of supervising every prompt individually, firms increasingly define the boundaries before an agent begins its work: what it can access, what actions it may take, where human review occurs, and who can deploy it.
That doesn't reduce the importance of lawyer oversight. It changes where that oversight is designed into the workflow.
As legal AI continues to evolve, firms that have already invested in strong governance foundations are well positioned for what's next. Agents don't change what governance is for. They simply shift governance from individual interactions toward the work itself — helping firms scale AI adoption while preserving the oversight, accountability, and professional judgment that legal practice requires.
Want to dive deeper? Read Extending Governance to Legal AI Agents for a practical framework for evolving your firm's AI governance as agents become a larger part of legal work.
