AI in Law and Legal Practices – Current AI application in Law

In the business world, every virtual thing you will do virtually, like sales, mergers, purchases, and many more, comes under the Law, and they will make legally enforceable contracts.
We recognize it or not, and day today, we are operating against the milieu of our legal regime and the implicit likelihood of litigation.
UK’s one of the most respected analyst at the intersection of legal and technology believes that this trend will continue to boom in the coming up years.
Artificial intelligence companies are continuously finding ways to develop advanced technologies that will manage tasks in various industries for better accuracy and speed. In this legal practice profession, AI has already found its into supporting clients and lawyers in the same manner.
The rising interest in applying AI in Law is slowly transforming the profession and shutting down the work done by the legal researchers, paralegals, and litigators.
Most of the professional service companies and law firms are planning to make the right decision in their business are planning to use USM’s AI advisory services and research to asses where AI can augment the workflow of its professionals.
In this article, you will obtain to know different ways in which AI is currently applied in the Law and how technology providers are trying to streamline work processes.
To ease the flow for the users, we are breaking down the AI’s current legal applications into the following categories:
Helping lawyers perform due research & diligence
Giving extra insights & shortcuts through analytics
Automating creating processes in legal work (Includes legal work)
AI and other technologies are allowing machines to take on many tasks that may be used to think required human lawyers, and that’s not plateauing. And the developments will warm up by 2020.

Current AI application in Law

We are segregating existing AI applications in Law into six categories based on our assessment of the companies and their offerings. They are;

  • Due diligence

It comes under one of the primary tasks of the lawyers to perform on behalf of the customers to confirm the facts & figures, and systematically assessing a legal condition. It required for intelligently advising customers on what their options and what actions they need to take.
The due diligence can positively affect long-term shareholder returns; the process can also be tedious and a lot of time-consuming. Lawyers need to conduct a detailed investigation for precise results, and in some cases, they too prone to mistakes & inaccuracy while doing spot checks.

  • Leverton

It is an offshoot of the German Institute for Artificial intelligence that uses AI to dig out relevant information/data, compile leases, and manage documents in real estate. The cloud-based tool has the capability of reading contracts at a very high speed in 20 various languages.
IT firm Atos sought the help of real estate firm ‘Colliers International’ in the year 2015, that used Leverton in performing due diligence of a company that the former was about to acquire.
With the help of Leverton’s AI, information like maintenance costs, payable rent, and expiration dates, were taken from thousands of documents and then structured on a spreadsheet.

  • JPMorgan

In 2016, JPMorgan developed its in-house legal technology tools, and they named the complete program as Short for Contract Intelligence (COIN).
The AI technology has the capability of extracting 150 attributes from 12,000 commercial credit agreements and contacts in a few seconds that is equivalent to 36,000 hours of legal work. This program was developed after the bank noticed an annual avg of 12k new wholesale contracts with blatant mistakes.

  • Kira Systems

The founder of the company thinks that due diligence errors by junior lawyers occur very often because of various reasons that lead to working late nights and some time on the eve of weekends too, forgetting to perform due diligence before the end of the workweek and failing to work on it.
Most of the associates are in a certain negative mindset about the efficacy of manual due diligence. Lawyers, being human, get cranky & tired, with unfortunate implications for voluminous due diligence.
The Kira company states that it is capable of performing a more accurate due diligence contact review by highlighting, probing, and extracting pertinent content for examination. The company is claiming that its software can finish the assigned task 40% faster when it is using for the first time and 90% for those with more experience.

  • Prediction technology

In the year 2004, a team of professors from Washington University tested their algorithms precision in predicting supreme court decisions on all 628 cases that argued in 2002.
The professors compared their algorithm results with a team of expert’s findings. In this analysis, the researcher’s statistical model proved to better predictor with 75% accuracy with experts 59% accuracy.
If you are looking out for additional uses in the real world, you can read our previous article on ‘ Top use cases of artificial intelligence in banking.’
Nikolaos Aletras of University College Lond and his crew used machine learning to analyze case text of the European court fo human rights and reported a 79% precision on their outcome prophecy.
Prof.Daniel Kantz, in his 2002 research paper, stated that “Quantitative right prediction already plays a great role in some practice areas and this role is likely growing as greater access to appropriate legal data becomes available.”

  • Ravel Law

Ravel Law is another tool that identifies outcomes based on relevant case law, referenced language, and judge rulings from 400+ courts.
The dashboard of the judge contains cases, circuits, decisions, and citations of a particular judge that is said to aid lawyers in understanding how a judge is likely to rule the case.
The firm’s claimed that Ravel Law could aid in litigation strategy by giving information on how judges making decisions.

  • Legal analytics

Case documents & docket entries provide additional insights during litigation by lawyers. Existing AI tools allege that today’s software products can extract key data points from these documents to support arguments.

  • Lex Machina

Hogan Lovells litigation attorney uses Lex Machina software to figure out ‘who is their counsel, who is the plaintiff, who else they have sued, and who have they represented.’
The software can generate data that can be used to examine an opposing counsel’s likelihood of losing or winning a case. The attorney claims to save time with the help of analytics results when creating a narrative.
Intellectual property lawyer used the software when she was representing a generic pharma company. While she is using the software, she found that the judge’s history of ruling cases tends to errand cases like her. Both sides are settled at the end, which was a better resolution, according to the lawyer Huong Nguyen.

  • Settlement analytics

Just keep in mind that legal analytic has some limitations. The CEO of settlement analytics said in his paper that there is uncertainty in producing results with a high level of precision with this type of technology.
It comes in petite sizes after cognitive biases, filtering, the tendency to interpret random trends as valid patterns that consist of a lot of noise that may affect the decision-making process.

  • Document automation

Work automation will most likely be one of the top disruption in the global economy.
Some law firms already started to adopt such technology by drafting documents via automated software. Many software companies claim that the final report will take days to months with human drafting, but it is a matter of a few minutes for software.
Most of the companies in the finance and banking industry are starting using this technology.

  • Neota logic system

The company claims that its software ‘PerfectNDA’ minimizes the NDA process by offering templates selected by AI based on the user’s scenario. It also enables feature document filling & integrated e-signatures to streamline the related manual process involved in NDA drafting.

  • Intellectual property

Securing copyrights, patents, and trademarks are the toughest things, and it is often the best thing left to law expertise. And we all know that the entire patent practice can be lengthy and laborious.
According to the US patent attorney, ‘you only have one year from the first time your invention publicly first issued to file a patent application.
If suppose you are a business owner launched product within the last year, then you need to talk to the patent attorney immediately to safeguard your patent.

  • Anaqua studio

This cloud-based application mainly designed for drafting prosecution and patents. The company datasheet told it is the first patent application tool for lawyers to save 20 hours on non-provisional patent application and 4 hours for provisional patent application.
This tool also used to detect bugs in a document, formatting detects, and circular claims apart from automatically generating literal claims support.

  • TrademarkNow

This company is taking some of the manual knowledge work of intellectual property application with Artificial intelligence. The company uses a sophisticated algorithm that is said to curtail week long searches for patents, trademark, registered products using the Trademark clearance platform that returns search results in less than 15 seconds.
It can analyze the results and rank them based on relevance to the user, as identified by the algorithm.

  • Final thoughts

The most accredited benefits of AI tools in legal practice is the enhancement of efficiency.  AI software employes algorithms that fasten document processing while finding for bugs and other concerns.
It looks like counter intuitive as the law practice most depends on billable hours, and it often does not behoove a lawyer to take less time in finishing a document or task. Because of this reason, tasks will likely not be strong enough to drive artificial intelligence espousal.
It is imprecise as to how the transition to legal AI will occur. On the other hand, some of the large firms will go for initial adoption because they can pay for AI tools and integrations. Besides it, small & new firms will begin with a lean, automated, and efficient driven approach, because they don’t have to pact with the enormous existing overhead of mighty firms.
Most of the top AI companies will believe that a wide range of adoption of AI in legal services may begin with a pool of small, medium, and nimble legal firms that will combine and emerge as a group of firms from the beginning they focus on efficiency and maximal automation.
These types of firms will show interest in applying AI and other tools to a particular domain, and they can leverage technology to garner large profit/employee numbers.
Some of the lawyers will debate that “smart people are not interested in this kind of technology, and they want to continue with the conventional methods.”
Undeniably for some legal matters, there may be little option to leverage human expertise. Still, other things will be impacted heavily by AI, and the field itself will eventually have to shift.
At USM Business Systems, we help legal and professional service enterprises to find out how AI technology will free up their professionals and lawyers to focus on high ROI work for more clients.
Artificial intelligence is very less discussed at the level of executives and partners in the law firms compared to other industries, making them susceptible to deceptive marketing by AI vendors.
Are you running a law firm?
Are you planning to develop or integrate AI tools to your law practice?
Contact us to know more in detail


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