A 45-attorney regional law firm specializing in commercial litigation faced a familiar challenge: document review consumed associate time at an unsustainable rate.

The Challenge

Discovery in complex litigation requires reviewing thousands of documents. Finding the relevant 500 documents among 50,000 requires human eyes on everything. Or it did.

The firm's associates spent 40-60% of their time on document review. This work was necessary but repetitive. It didn't develop their legal skills. It didn't serve clients efficiently. It was a tax on every litigation matter.

Partners knew there had to be a better approach. They'd heard about AI for document review but weren't sure how to evaluate options or implement safely.

The Approach

We worked with the firm's litigation partners to design an AI-assisted review workflow.

Phase one focused on document classification. Training the AI to distinguish relevant documents from irrelevant ones across the firm's common matter types: contract disputes, employment claims, and business torts.

Phase two added privilege flagging. The AI identified documents likely containing privileged communications, routing them to senior review rather than standard processing.

Phase three integrated with the firm's existing document management system. Associates could access AI recommendations within their normal workflow rather than switching between systems.

Throughout implementation, we maintained human oversight. The AI recommends; attorneys decide. No document was produced or withheld based solely on AI classification.

The Results

70% reduction in review time. What took 100 hours now takes 30. The AI surfaces the documents that need attention. Associates focus on evaluation rather than scanning.

Improved consistency. Human reviewers have good days and bad days. AI review is consistent. The accuracy of relevance determinations improved alongside the efficiency gains.

Associate satisfaction. The attorneys doing review work reported higher job satisfaction. They're doing legal analysis, not document scanning. The firm sees this in retention metrics.

Client value. Matters are staffed more efficiently. Review phases that used to take weeks now take days. Clients appreciate the faster turnaround and more predictable costs.

Implementation Timeline

  • Weeks 1-2: Workflow analysis and system design
  • Weeks 3-6: AI training on firm's matter types
  • Weeks 7-10: Pilot on selected matters with close monitoring
  • Weeks 11-12: Full rollout and team training

The 12-week timeline allowed careful implementation without disrupting ongoing matters. Associates were trained as the system rolled out, building confidence through experience.

What Made It Work

Senior partner sponsorship. The managing partner championed the project. This ensured resources and overcame initial skepticism from associates who worried about job security.

Realistic expectations. We positioned AI as an assistant, not a replacement. Associates still review documents. They just review fewer irrelevant ones.

Iterative training. The AI improved over time based on attorney feedback. When reviewers disagreed with AI recommendations, that feedback refined future recommendations.

Ethics-first approach. Every design decision prioritized professional responsibility. The AI helps find documents; attorneys make privilege and relevance determinations.

Looking Forward

The firm is now exploring phase two applications: contract analysis for their transactional practice and research assistance for brief preparation.

The document review success built confidence for broader AI adoption. Associates who were skeptical now ask what else AI can help with.

That's the trajectory we see repeatedly: successful first projects create appetite for more.