Orrick Uses Predictive Analytics to Cut Costs by 96.7%

2 min readSources: LegalTech News

Orrick's predictive analytics cuts attorney review volume by 96.7%.

Why it matters:

This substantial cost reduction demonstrates how AI can optimize legal workflows, benefiting both firms and clients with significant financial savings and operational efficiency.

Key points:

  • Orrick cuts attorney review volume by 96.7%, saving $58,000 per matter.
  • Deployment of AI tools leads to over 50% cost savings in document review.
  • The Observatory platform evaluates 600 legal-tech products for in-house counsel.
  • Orrick ranks in the Top 10 by Financial Times for innovation.

Orrick has effectively utilized predictive analytics to significantly reduce the volume of documents that require manual attorney review by up to 96.7%. This impressive reduction translates into a substantial average savings of $58,000 per matter, marking a pivotal shift in leveraging AI for cost efficiencies in legal processes.

The firm's practical application of Everlaw’s AI Assistant Coding Suggestions in intellectual property litigation has further illustrated potential savings, with document review costs being cut by more than 50%. This not only highlights AI's current impact but also its promise for future application in diverse legal scenarios.

Moreover, the introduction of The Observatory platform facilitates comprehensive comparisons among over 600 legal-tech products. This initiative empowers in-house legal teams with unparalleled insight into tools like project management and AI platforms, crucial for strategic operational decisions.

Orrick's consistent ranking in the Top 10 most innovative law firms by the Financial Times underlines its commitment to integrating cutting-edge technologies to enhance legal service delivery. As AI continues to evolve, its role in crafting effective and economical solutions becomes undeniable.

By the numbers:

  • 96.7% — Reduction in attorney review volume, cutting $58,000 per matter.
  • 50% — Cost savings in document review through AI tools.