Artificial Intelligence (AI) is no longer just a fictional topic pitched around sci-fi fanatics. Our world is becoming more and more cohesive with AI.
When you call customer service for your mobile related issues and interact with the automated voice, you’re being served by AI.
When you tell your Google Home, Amazon Echo, or even Siri to play your favorite playlist, you’re interacting with AI.
This smart technology is more concrete today than it ever was in the past, and the future of AI seems as bright as ever. Moreover, even the client-facing businesses need to learn, the winners of the future are those who can adapt to the changing needs of clients. This fact is now digging the legal sector, which has been a turtle in embracing changing technologies up until now.
In the report of 2017, cited by PwC claim, that clients that have long been unsatisfied with the mounting cost and speed of legal service delivery. Many believe that the time has come and “2020s will be the decade of disruption” as law firms are increasingly investing in technology to automate tasks and improve decision making.
Impact of AI in the legal industry
Lawyers of this decade are under tremendous pressure to deliver legal services efficiently at a cheaper price to attract new clients. So to be smarter and efficient, adopting technological solutions have become obligatory for the legal sector.
AI can assist lawyers in various aspects from managing a wide range of document-intensive tasks that are crucial to negotiate a transaction, conduct an internal probe, or determine the evidence significant to the litigate or protection of a claim.
AI uses various set of rules to classify and process structures in data, increasing accuracy and value of the credentials as more probes are processed; which is machine-based learning, it also understands and respond to human language structures; which is natural language processing, and make prediction based on structures found in sample data; which is predictive analysis.
There are AI tools that assist many areas of law practice:
Contract review and analysis–
Reviewing contracts is one of the most tedious tasks for law firms yet significant. As there is excessive content in a contract and finding that one particular clause can be tough. So here comes AI into play. There are two AI software namely Kira and eBrevia that helps to extract relevant information from the contract to reduce the workload of law firms.
Kira can highlight particular contract provisions for example cooperation clauses that too in a large collection of agreements and generate a “roadmap” to alter the form. Whereas, eBrevia is a “contract investigator” software that alters collections of contracts into searchable text, abstracts information based on user terms, reveal changes from “playbook”, and organizes documents by language and category.
Consent and threat forecast–
There are many AI application available that help law firms to monitor consents and standard potential intimidations. For instance, NexLP, Inc. offers “Story Instrument” that can review email and other connections in the probe to regulate the schedule of key events, recognize the contributors and the associations among these key players to construct the framework for connections.
Moreover, there is one more tool namely RAVN, from iManage that reads the large volume of documents and identify, classify, and extract information swiftly and competently.
Legal Research–
Earlier, legal research was one of the most time-consuming processes as lawyers to need to do various searches about the case from law books and analyze all the aspects to conclude the case in a simple manner. This was not the favorite jobs of the lawyers. Now with digital transformation, law firms can research collect millions of facts and figures, review thoroughly within minutes.
How? Thanks to AI! ROSS Intelligence is a software that allows lawyers to ask a legal research question in usual language, review more than a million page of case law per second, and creates an answer. ROSS also introduces EVA software that analyzes briefs, checks references, and finds similar cases.
Writing briefs and memo drafting–
Recently, Casetext has come up with its new legal research assistant in October 2016 CARA. It has the capability of both artificial intelligence and natural language search technologies to assist attorneys in finding additional case law. CARA also allow lawyers to upload a brief or memo and then retrieves additional relevant case law not cited in the original document.
Moreover, it has been awarded the New Product of the Year Award for 2017 by the American Association of Law Libraries.
One more flagship product IBM Watson Debater scans a database for relevant content identifies the strongest arguments and builds arguments on both sides of the issue in natural language.
Decision analysts–
AI also helps judges in the decision making process. As judges are usually overwhelmed with the list of cases, so AI tool that has natural language processing namely Lex Machine; line up the documents to forecast decision significances. It helps with positive arbitrations in which to bring proceedings, effective motions, and arguments before particular juries.
E-discovery–
Image Source: Edrm.net
Lawyers across the world are very much familiar with Technology Assisted Review (TAR), which is meant to categorize all the legal documents to attain a more efficient document review process. As compared to manual document review process and relying on a team of attorney or paralegal to find the various search terms, TAR count on one attorney to guide the review process through interactive testing. Brainspace software is also TAR that review documents at rates up to one million per hour and recognizes key phrases and gatherings in related documents.
The Final Word
AI can improve the efficiency and accuracy of the most outdated legal industry by automating their tiresome, repetitive jobs such as research work, document review, or litigation support. It can also mug up through the various legal process and make valuable forecasts across an immense amount of data that would be impossible for humans alone to manage.
