Authored by Bobby Balachandran

This article originally appeared on Law.com on June 23, 2026.

One of the most common questions surrounding AI today is whether it will replace lawyers and legal professionals. I think that's the wrong question to be asking. A more useful question is this: Where can AI eliminate the coordination burden that prevents legal professionals from spending time on the work that actually requires their expertise?

Much of the conversation around legal AI has focused on content generation, can AI draft a memo, summarize a document, review a contract, or analyze case law? These capabilities are important, and they continue to improve rapidly. But when I speak with General Counsel, Chief Legal Officers, and legal operations leaders, the challenge they describe is rarely a lack of information or expertise. The challenge is that legal work often moves too slowly.

Consider what happens when a subpoena arrives, an internal investigation begins, or a privacy request lands with a legal team. The legal analysis itself is often only one part of the process. Before that analysis can even begin, information must be gathered from multiple systems and stakeholders. Legal needs input from IT; IT coordinates with security; privacy teams become involved; outside counsel requests updates; and deadlines are tracked across spreadsheets, emails, and meetings. Ultimately, a lot of valuable time is spent moving work between people rather than moving the matter itself toward resolution. That is not an expertise problem. It is a coordination problem.

For years, organizations have invested in tools that help individuals perform tasks more efficiently. What they have not always addressed is the workflow that connects those tasks together. As a result, highly trained professionals frequently spend their days managing handoffs, chasing updates, and coordinating activities across functions. This is where autonomous and agentic AI create an entirely different opportunity.

Most discussions about AI focus on helping a person complete a specific task faster. The bigger opportunity lies in helping the entire workflow move faster. Instead of accelerating a single step in a process, autonomous systems can coordinate the process itself: routing work, gathering information, tracking progress, maintaining documentation, escalating issues when needed, and creating a defensible record along the way.

We are beginning to see this in real-world legal use cases. Take a subpoena response as an example. In many organizations, a subpoena still triggers a chain of manual coordination across legal, IT, HR, records, privacy, and outside counsel. Deadlines must be tracked, stakeholders identified, information gathered, approvals documented, and responses managed. The legal judgment involved may be relatively straightforward; what consumes time is the orchestration required to move the request from intake to completion.

The same pattern exists across privacy requests, regulatory inquiries, internal investigations, and other high-volume legal workflows. These processes are not suffering from a lack of expertise; they are burdened by fragmented coordination. That is why they represent some of the most compelling opportunities for autonomous and agentic AI.

While the initial wave of legal AI focused on helping professionals complete individual tasks faster - such as reviewing documents or conducting research, this next wave handles the gaps between those tasks. It is focused on accelerating the movement of work by autonomously managing the handoffs between people, systems, and decisions that traditionally create delays.

Importantly, this is not about removing lawyers from the process. Legal judgment, strategy, privilege decisions, and risk assessments remain fundamentally human responsibilities. The goal is to remove the administrative friction surrounding those decisions so legal professionals can focus their attention where it creates the most value.

For legal leaders evaluating AI today, the most important question may not be which tool can generate the fastest answer. A more valuable question is to ask where expertise is currently being consumed by coordination. Where are legal teams spending time chasing information, managing handoffs, tracking deadlines, or routing work between stakeholders? Those high-friction, high-volume processes represent the greatest opportunity for autonomous AI to create measurable value.

The first wave of legal AI helped professionals work faster. The next wave will help the work itself move faster. That's where I believe the most meaningful transformation lies, not in replacing expertise, but in enabling it.

Bobby Balachandran is the Founder and CEO of Exterro.