Although artificial intelligence (AI) has been used in the e-discovery space for more than 10 years, AI is now capable of more complex litigation tasks, such as legal research, drafting pleadings, and predicting judicial decisions, in a fraction of the time it would take a human lawyer to do the same tasks. If AI can help lawyers and law firms more quickly process and analyze large amounts of data, and in turn, make the litigation process less expensive, faster and more efficient, why have litigators been so slow to adopt the newest technologies and capabilities? Understanding and demystifying what AI can and cannot do (i.e., it can help automate the more mundane, repetitive legal tasks and analyze large amounts of data, but it cannot negotiate, advocate, or provide sophisticated legal advice) might help litigators not fear, but rather, embrace AI as a way to access larger pools of data, make more informed strategic choices in their advocacy, and provide better and more efficient legal services to clients.

In simplified terms, AI is essentially highly advanced software that can simulate human thought processes to complete basic, time consuming tasks and produce relevant and accurate results in much less time. Machine learning is a form of AI that employs statistics, pattern matching, and inference to perform a task, as opposed to using explicit procedures. Perhaps that sounds threatening, but using AI tools as an aid to law practice is not just having a moment; it is here to stay and will soon become an indispensable part of practice for all lawyers. Yet lawyers, and litigators in particular, have been slower to embrace and adopt new technology than other professions. According to a survey conducted last year by the American Bar Association, only 10 percent of lawyers used AI-based tech tools for their legal work in 2018 (though those usage rates are higher for respondents working at larger law firms). (The ABA's "2018 Legal Technology Survey Report" included 900 respondents from across the nation and at firms of various sizes.) A 2019 Bloomberg Law survey indicates that only one in four people in law firms and legal departments use AI-based legal technology. (Bloomberg Law Legal Operations & Technology Survey included 500+ in house and law firm practitioners.)

Why Is Adoption Essential?

Litigators should be aware of some of the powerful AI and machine learning tools, which can quickly access and analyze large amounts of data and help us make better informed strategic decisions and improve the quality of our advocacy. The time spent slogging through data and documents and repetitive tasks can instead be allocated to providing sophisticated legal analyses and more effectively shaping the narrative we ultimately provide the judge or jury. This is not only good for clients, but also for job satisfaction and attorney development and training, especially at the junior level. As other factors are driving change in the legal industry, including growing pressure on in-house corporate law departments to increase effectiveness and efficiency, investing the time and effort to understand and adopt AI technology, especially as a litigator, is essential.

However, making sense of the myriad of AI tech products in the market can be overwhelming and confusing, especially to a profession that is naturally risk-averse. Indeed, much of the technology that claims to do more advanced legal work is still emerging. In recognition of these barriers, some of the larger law firms for instance have opted to collaborate with Reynen Court, which, much like an "app store," provides law firms with a single platform to access new legal tech products from a variety of vendors. The hope and idea is to remove the friction involved in exploring, comparing, and using various AI technologies available from many vendors—a small but significant step in the right direction.

How Can AI Be Helpful in Litigation?

Putting aside AI use in e-discovery and document review, which is probably the most prevalently used AI among litigators, there are at least three other major areas in which AI can best help litigators specifically to be more effective and efficient: (1) legal research; (2) data analytics and legal outcome prediction; and (3) automatic pleading and document discovery generation.

Perform better, faster legal research. AI-based tools, such as Casetext, Judicata, Ross, Points of Law (Bloomberg Law) and AI-enhanced Westlaw and Lexis, make legal research faster, easier, and more thorough and trustworthy than ever before. Years ago, associates using online research tools had to learn to formulate clunky, algorithmic search terms to find relevant cases, lest they miss a whole category of case law. Newer AI research tools help lawyers find all of the most relevant case law using plain English to describe the legal issue and some relevant facts. Bloomberg Law's Points of Law uses AI and machine learning to quickly isolate and analyze the relevant language in a court opinion and click through a generalized "point of law" in a timeline to gather all the cases in support of a statement of law to strengthen legal arguments. Several vendors have AI-based brief analyzers, which allow a user to upload a brief and identify relevant cases that the document missed or failed to cite.

Predict legal outcomes. Consider how often a client has asked you to predict the likelihood of success and costs associated with a case. With experience, we litigators get fairly good at this exercise, but it comes with the caveat that litigation can be unpredictable and expensive. No one lawyer or even law firm can make full and optimal use of the massive amounts of data stored in the court systems, including opinions, orders, and jury verdicts. But because AI has the capacity to hold and review such vast amounts of data spanning many years, it has the ability to provide some valuable insights about the likely outcome of a case. Companies such as Lex Machina, Ravel Law, Premonition Analytics, and others have used the data they have mined on every federal judge and state appellate judge to give insights into a judge's patterns, abnormalities, rulings, reversal rate, and numbers of citations to a judge's decisions—to in essence, predict judicial outcomes based on real data. Interestingly, AI can predict Supreme Court decisions better than human experts based on two centuries of Supreme Court data analytics. This kind of data-driven information helps litigators more effectively advise clients in their decision-making, better quantify litigation risk and expense, and generate better informed legal strategies that are more likely to succeed.

Generate "automatic" pleadings. AI is now being used to generate responsive pleadings, discovery responses, and related documents by a simple upload of a complaint or discovery requests and incorporating jurisdictional requirements. LegalMation, for example, is an AI vendor with a product that automatically generates some of the more routine responsive litigation documents, such as answers and responses and objections to requests for production and interrogatories, in just a few minutes.

What AI Cannot Do

As discussed above, AI can improve the practice of law and help lawyers deliver better services more efficiently by cutting through the time to complete the more repetitive and mundane tasks. This allows litigators of all levels to spend more time and mental energy on more complex, sophisticated analyses, and client interactions. But why the resistance? Understanding AI's limitations may help more litigators to embrace AI's benefits in their practice.

AI cannot counsel, negotiate, engage in creative thinking, or apply critical thinking to data. It can help you write a better brief, but it cannot write the brief. It lacks human common sense and judgment. It cannot think on its feet or tell your client's story in court. In short, it cannot strategize and advocate on your client's behalf. Moreover, most if not all of the AI technology available to aid litigators requires active human oversight. While AI is starting to displace some of the more routine types of legal work attendant with practice, the point of introducing AI in litigation is not to replace lawyers with computers, but rather to elevate their practice to a level otherwise unattainable.

Conclusion

We are in the midst of transformation in the legal industry and lawyers and law firms of all sizes must commit to delivering both excellence and efficiency. That means taking real steps to improve lawyers' access to and comprehension of technology designed to help litigators be better and faster at what they do—not replace them. Because the truth is, it is not the adoption of AI that will hurt or detract from lawyers; rather, it is the failure of lawyers and law firms to learn and embrace AI technology that will leave them behind.

Susan L. Shin is a partner in the complex commercial litigation practice group and a first-chair trial lawyer at Weil, Gotshal & Manges.