AI Lawyers: How AI Is Transforming Law Practice

Case documents and docket entries provide supplementary insights during litigation by lawyers. Current AI tools claim that today’s software products are able to extract key data points from these documents to support arguments. The company also claims that with their tool, law firms can cut costs by 90 percent and reduce contract review and approval time by 80 percent (though these numbers don’t seem to be coupled with any case studies). We already know that major disruptions are approaching the legal industry due to AI and automation. Instead of being victim to the changes, law firms and legal teams must prepare for the future of the legal profession by perfecting their current legal processes and incorporating tech to reach their goals. The impact has already been felt in the industry, as law firms and large corporations alike are leaning on legal tech.

Imagine a legal research task that used to take days now being completed within minutes. AI-powered tools can automate time-consuming tasks like document review, legal research, and contract analysis. This frees up valuable time for lawyers to focus on more complex and strategic work, ultimately enhancing their efficiency. Perhaps surprisingly, AI has been found to be equally efficient at flagging ESI for relevance and privilege as human review, particularly in large ESI sets. Because the technology is expensive to implement, it is not often used in smaller cases.

The Legal Tech Startup Ecosystem

In 2016, Stanford University student Josh Browder was facing thousands of dollars in parking tickets in New York City. DoNotPay might not have really been the first, but it was one of the most visible introductions into how AI and machine learning might impact the future of the legal industry. But similar to any analytics platform, AI tools that deal with predictive technology need a lot of data in the form of case documents to fully work according to Kantz.

According to the company, users can  which documents put them at risk for litigation when they use the software. Expanding the coverage from 1816 to 2015, Prof. Daniel Katz of Michigan State University and his two colleagues achieved a 70.2 percent accuracy on case outcomes of the Supreme Court in their 2017 study. Similarly, Nikolaos Aletras of University College London and his team used machine learning to analyze case text of the European Court of Human Rights and reported a 79 percent accuracy on their outcome prediction. While there has been a growth in the use of e-Discovery tools, its application has become a public issue in states such as California. The State Bar also suggests that if a lawyer is incompetent on the facility, he should learn the skill, hire someone who’s knowledgeable, or just simply decline representation.

Commnication as a key skill for in-house Legal Counsels:

Jeannie observes that the ‘need for caution remains, as the technology is still only predictive’. Jeannie continued, “Managing the risk of inaccuracies occurring in the use of AI technology relates back to the importance of robust risk management strategies and careful design about how the human and AI interact. “A real risk is also presented in legal professionals becoming overly reliant on AI solutions, which is a problem because AI lacks human reasoning. Legal professionals are bound by ethical obligations and the irresponsible use of AI may result in civil liability as well as reputational damage. Also in 2018, Harvard Law School published an article stating that “Within a few years, AI will be taking over (or at least affecting) a significant amount of work now done by lawyers.

Read more about How AI Is Improving the Legal Profession here.