Five Ways That Artificial Intelligence and Machine Learning Are Transforming Legal Practice

Artificial intelligence can be extremely confusing and a little threatening too, at least for those of us who are not computer scientists.  It introduces us to a strange new vocabulary of terms and concepts, such as natural language processing and neural networks, and we have only the vaguest idea of how these technologies work and what they actually do.

Nonetheless, as AI/ML technologies are beginning to play a significant role in the legal market, it’s important for legal professionals to have a basic grasp on what these technologies are capable of doing and how they are likely to transform legal practice.  Here are five critical ways in which AI/ML technology has already been successfully introduced into the legal market, all of which are very likely to continue expanding in the years ahead.

  1. Better Management of Voluminous Data.   We are inundated by data, which is currently estimated to be growing at the rate 1.7 megabytes every second for every human on the planet.  This poses a very practical problem in the legal market where the amount of information that needs to be processed and managed, for both litigation and transactional matters, keeps growing at a similarly explosive rate.  The 2019 State of -Discovery Report produced by FTI Consulting and Exterro estimates that the amount of data managed by law firm and law department IT staff has increased five-fold in just the last 5 years.
    Quite simply, AI/ML technology is the best tool we have in our toolbox in order to stay afloat in the sea of data. That’s why e-discovery, contract management and due diligence platforms have all been building AI/ML capability into their products, so that key data can be extracted from voluminous documentation, on a first pass without human review.  This greatly streamlines the process of due diligence and e-discovery, and provides lawyers with a means to find the meaningful signals amidst all the noise.
  1. Automation of Highly Repetitive Tasks. A second key function of AI/ML technology is to achieve cost savings and efficiencies through the automation of highly repetitive tasks. This is often referred to as robotic process automation, which gives rise to the notion that there are robot-lawyers poised to take over.  In fact, when you look around the law firm or corporate law department today, there are any number of tasks being handled by junior associates, paralegals or billing specialists that could be far more efficiently and accurately handled through robotic process automation.
  2. For example, AI/ML companies, such as LawGeex and ThoughtRiver, have developed AI tools that have proved helpful for streamlining the process for contract negotiation and review, particularly when dealing with high-volume standardized contracts, such as  NDAs, 
    derivative contracts and sales agreements.  These tools can be customized to follow a company’s contract playbook, prepare first  drafts in automated fashion and then generate redlined markups that highlight where terms and provisions need to be escalated for attorney review.  The end result is a more efficient and  consistent process for contract negotiation, which can enable an in-house team to achieve substantial savings of time and money.

  1. Leveraging Human Expertise. One of the primary functions of the next generation of AI tools is to enable lawyers to capture their expertise and build automated systems, such as virtual legal assistants or legal chatbots, that can interact with end users. These automated systems are capable of both collecting information from end-users and then dispensing advice based on pre-established rules-based logic.  In effect, this enables legal professionals to leverage their expertise and deliver it in the form of a digital product or service.
  2. AI/ML companies, such as Neota Logic and Bryter, have developed no-code platforms which allow legal experts, with little or no background in computer programing, to build these expert systems on their own.  This has made it much easier to build and deploy these expert chatbots in large corporate environments where they can help provide compliance and regulatory advice to employees across the enterprise, consistently and to scale. And as with other applications of AI technology, the legal chatbots allow a law department to achieve significant cost-savings, by resolving routine matters in a fully automated fashion and routing more complicated issues to an attorney for human review.

  1. Outcome Prediction. Software capable of outcome prediction is already becoming a reality in the legal market, primarily focused on AI/ML systems used to help analyze litigation claims.  When trained to analyze discrete types of claims in particular jurisdictions, these AI/ML prediction engines have been shown to perform more accurately and far faster than expert attorneys conducting a similar review.
  2. These AI-powered prediction tools are beginning to find a place in the market. For instance, Blue J Legal has developed AI/ML engine for analyzing tax disputes which it claims can predict outcomes with 90% accuracy. Litigation funding companies are also using prediction engines to analyze which pending lawsuits are potentially good fits for their investment portfolios, although their final investment decisions still depend on human review. While the current generation of AI/ML prediction tools are still far from perfect, and perform best in these niche contexts, AI/ML prediction systems will no doubt achieve far wider acceptance as their algorithms continuously improve through further training.

  1. Information Filtering – Your Interface to the Digital World. In the old days, lawyers read advance sheets and update services and sent junior associates off to the library to research and write memos in order to stay abreast of the latest regulatory developments.  Now, as online information sources have proliferated, AI/ML tools are replacing manual processes and providing a new heavily automated solution for lawyers and compliance professionals to keep on top of the latest developments that affect their business and practice.
  2. Compliance.ai is a prime example of a company that has successfully harnessed AI/ML technology to serve the needs of its corporate clients.   They have built an AI/ML engine that monitors available online information sources and then generates personalized alerts that automatically summarize how corporate processes need to be adapted based on the latest regulatory changes.  These AI/ML tools have proven particularly useful in heavily regulated industries, such as financial services, where rapid regulatory change is an essential part of business life.

These, then, are the five basic inroads that AI/ML technology has established in the legal market in just the last few years.  Overall, the impact on legal practice thus far may be relatively modest in scale, but it’s important to keep in mind that we are still in the early stages of the development of the technology.  By their very nature, artificial intelligence and machine learning systems improve in their power and capability through the continuous fine-tuning of the algorithms they use, which makes it inevitable that we will see AI/ML tools handle increasingly sophisticated challenges and tasks in the coming years.  That’s also why it seems inevitable that the technology is destined to play a major role in driving transformation of legal practice.

 

Andrew Jardine

Andrew Jardine

Andrew provides advice to Cenza and their clients on how best to utilise legal services in conjunction with different legal technologies, achieving high quality and cost effective solutions. Andrew does this by leveraging his legal technology and strategy consulting experience gained during his time as an early stage employee at Kira Systems and while as a Consultant at Deloitte earlier in his career. In hisspare time Andrew publishes a legal technology podcast, “Legaltech Tapas”, helping people to stay informed about different legal softwares.

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