Why Legal Technology Leaders Are Rediscovering eDiscovery in the Age of AI

eDiscovery began as new legal technology in the early 2000s and developed into a specialized, service-oriented industry that operates separately from broader legal tech teams. Legal technology leaders are now placing renewed interest in eDiscovery solutions. The renewed interest stems from a realization that eDiscovery databases contain the essential documentary evidence for AI-powered litigation workflows.  Innovation teams within law firms are starting to understand that access to eDiscovery repositories is necessary for any Generative AI strategy in litigation.

Tech Teams Show Growing Interest in eDiscovery Discussions Involving AI

The separation between eDiscovery and general legal technology teams developed naturally over the past two decades. eDiscovery became a specialized industry unto itself due to its complexity and significant financial investment requirements. Large service organizations dominated the market, focusing primarily on document review and consulting services. This specialization created distinct teams within law firms, with eDiscovery professionals operating independently from colleagues managing practice automation, billing systems, and document management platforms.

This division made practical sense when eDiscovery served a single purpose: processing documents for production in litigation. The industry developed its own conferences, educational events, and specialized expertise. When legal tech teams encountered eDiscovery questions, they typically responded that a different team handles those matters. The two domains functioned as separate industries with minimal overlap.

The emergence of Generative AI has begun shifting this dynamic in meaningful ways. Legal tech teams are showing growing interest when eDiscovery discussions include AI applications. They are increasingly exploring eDiscovery solutions rather than automatically deferring to specialized teams. This shift reflects a developing understanding that eDiscovery databases house the documentary evidence essential for AI-powered legal work beyond traditional discovery tasks.

eDiscovery Databases are Key Repositories for AI-Powered Legal Work

When lawyers want to prepare for depositions, analyze case issues, or prepare written discovery using AI tools, they need access to the underlying documentary evidence. This evidence resides in eDiscovery databases, which contain both client-collected data and materials produced by opposing parties. Without this foundational information, AI systems lack the source material necessary for meaningful legal analysis.

Scale presents both an opportunity and a challenge in this convergence. Even small eDiscovery matters involve hundreds of thousands of documents, while larger cases can include millions of documents. Employment disputes, which might seem straightforward, routinely generate hundreds of thousands of documents. This scale distinguishes true eDiscovery solutions from general AI systems that claim to handle discovery work but lack the infrastructure and expertise to manage such volumes effectively.

Any experienced litigator understands that distilling a data collection of hundreds of thousands of documents into a timeline is an entirely different task than making a  timeline from a handful of documents. Litigation operates at scale.

Many AI companies without eDiscovery backgrounds now offer what they describe as discovery solutions. However, eDiscovery professionals recognize these offerings as inadequate because they fail to address the scale, data diversity, defensible processing and regulatory supervision requirements inherent in discovery work. Courts oversee the process, regulators maintain detailed knowledge of requirements, and the adversarial nature of litigation demands precision that general AI systems cannot provide.

Combining eDiscovery Expertise With AI Capabilities

The financial implications of this convergence are substantial. The eDiscovery industry currently represents a ten billion dollar market, with a vast majority of the spending dedicated to manual consulting and document review. Generative AI, particularly through agentic workflows, will eliminate much of this manual work. The technology now exists to automate first-pass review processes that have historically required extensive human involvement.

This automation potential creates urgency for both sides of the convergence. Legal tech teams recognize they need eDiscovery expertise to handle the scale and complexity of litigation data for AI applications. Meanwhile, eDiscovery professionals understand that their traditional service model faces significant disruption as AI capabilities advance. 

The solution lies in viewing eDiscovery systems not merely as tools for creating production sets, but as curated repositories of case evidence. When eDiscovery platforms incorporate generative AI capabilities for data curation, they become foundational infrastructure for all litigation workflows that utilize AI. This approach enables organized access to important information while maintaining the scalability and analytical features that distinguish true eDiscovery systems from hyped Generative AI platforms.

This convergence represents more than technological advancement. It reflects a maturation of understanding about how AI can enhance legal practice. The recognition that eDiscovery databases serve as essential repositories for AI-powered legal work bridges the gap between specialized discovery teams and broader legal technology initiatives.

Law firms that embrace this convergence position themselves to leverage AI more effectively across their litigation practices. They gain access to curated, scalable data repositories that support diverse AI applications while maintaining the precision and oversight requirements of legal work. The firms that continue to treat eDiscovery as a separate function may find themselves at a disadvantage as AI becomes more central to legal practice.

The renewed interest in eDiscovery reflects this broader understanding. eDiscovery has become relevant again because legal professionals recognize its central role in AI-enabled litigation. This convergence creates opportunities for more efficient legal practice while maintaining the rigor and precision that effective legal representation requires.