Case Study: How Harvey AI Redefines Legal Workflows


Harvey AI is an artificial intelligence platform tailored for legal professionals, launched by a startup founded in 2017. Funded by prominent Silicon Valley investors, including Sequoia Capital and OpenAI, its primary goal is to employ machine learning and natural language processing to analyze and extract insights from legal documents, thereby streamlining various routine legal tasks.

Key Takeaways

  • Harvey AI significantly enhances efficiency by automating repetitive legal tasks, allowing lawyers to focus on higher-value work.
  • The introduction of Harvey AI leads to a reduction in costs, as it decreases the billable hours required for routine legal tasks.
  • Through its advanced contract analysis capabilities, Harvey AI helps in early spotting of errors and legal risks, contributing to risk mitigation.
  • The capacity to handle more clients and cases is greatly increased with the assistance of Harvey AI.
  • Harvey AI is instrumental in uncovering valuable insights buried within contracts and legal documents.


Harvey AI integrates features like contract analysis, plain language insights, legal research automation, and custom document drafting. This not only accelerates the contract review process but also simplifies legal jargon for easier comprehension by non-lawyers. Its legal research automation feature significantly reduces the time-consuming aspect of legal research.


The implementation of Harvey AI across various law firms has demonstrated its transformative potential in the legal sector. Notably, Littler Mendelson, a law firm specializing in employment law, utilized Harvey AI for contract reviews during employee onboarding processes. This integration resulted in a remarkable 70% faster turnaround time, significantly freeing up the workload of their lawyers.

Similarly, the multinational firm Baker McKenzie employed Harvey AI to scrutinize and compare key clauses in hundreds of commercial real estate leases, leading to over $1 million in cost savings. These instances showcase Harvey AI’s capability in streamlining complex and time-consuming legal tasks.

In another notable application, Kor Group implemented Harvey AI for due diligence document reviews in several mergers and acquisitions deals. This adoption led to a 25% faster completion rate of deals, with over 2,500 documents reviewed more efficiently.

Furthermore, at Wolters Kluwer, a global provider of professional information, Harvey AI’s legal research automation significantly reduced average memo drafting time from 4.5 hours to just 1.5 hours, marking a 67% decrease in time spent.

These real-world applications of Harvey AI across diverse legal firms underline the platform’s versatility and effectiveness in enhancing the efficiency and accuracy of legal workflows


The implementation of Harvey AI has led to 20-50% time reductions in tasks such as contract review and legal research. This efficiency gain translates directly into cost savings, providing a competitive edge in the legal market.

Challenges and Barriers

While promising, Harvey AI faces limitations like the need for careful implementation, training, and the necessity of lawyer oversight. Challenges also include the potential for job disruption and the requirement to reskill the legal workforce for AI integration.

Future Outlook

Legal AI, including Harvey AI, is forecasted to become a significant industry, potentially reaching $1.9 billion by 2030. Experts predict these technologies will profoundly change how legal services are delivered, urging legal teams to adopt AI proactively for a competitive advantage.

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