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Legal Director’s Guide to AI-Driven Discovery and Analytics | Ipro Tech

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As Chief Legal Officer (CLO), you are responsible for managing your organization’s risk profile for legal and regulatory compliance, overseeing day-to-day business, and overseeing the legal department. On top of that, you need to devote a substantial amount of your time to strategic advice for the rest of the business. If you feel like you’re stretched out too much, you’re not alone.

But there is an assistant ready to help you whenever you ask for it. This helper will never complain about doing the same task over and over (and over again). This wizard also doesn’t mind huge amounts of data – in fact, this wizard needs that data to do its job.

We are, of course, talking about artificial intelligence (AI), which can streamline work processes, easily eliminate repetitive tasks, and sift through piles of data in a short time, highlighting the potentially interesting parts for the job. human examination.

As a CLO, the more you can streamline legal operations and save time on legal matters, the more time you have to think and work strategically. This is where artificial intelligence (AI) can be a boon.

Why CLOs Should Adopt AI

Generally speaking, AI is “the capacity of a computer or a machine to imitate the capacities of the human mind”, that is, to learn from information to recognize language. , understand concepts and differentiate objects. Voice assistants like Alexa or Siri use AI to understand signals, perform actions, or display results that match a request.

AI excels at sifting through massive amounts of data to identify specific terms or concepts, even when those concepts are expressed in different terms. Because an AI system can analyze data faster than any human and doesn’t get tired or distracted, it can assess datasets faster and easier than a human while maintaining accuracy. . A machine can also handle repetitive and laborious tasks quickly and efficiently without falling prey to boredom or wandering attention.

Legal departments can therefore use AI to streamline processes, reduce costs and increase productivity. Given that “almost two-thirds (63%) of [legal department] respondents say recurring tasks and data management constraints prevent their legal teams from creating value in their organization.

6 Ways CLOs Can Leverage AI in eDiscovery

eDiscovery provides an exceptional entry point for CLOs and legal departments who are simply learning to take advantage of AI, as it has many different applications and uses for the varied tasks of eDiscovery.

Here are some of the applications of AI in enterprise eDiscovery.

  1. Complete early case assessment

At the start of a case, the legal department needs a way to get a quick overview of the validity of a claim and its potential ramifications.

AI can analyze this mass of data to identify “hot documents” and other critical information, allowing the legal team to quickly assess the seriousness and value of the claim. Note that AI doesn’t replace lawyers – it just increases their efforts, leading them to the data most likely to be relevant so they can verify its importance.

  1. Structure data using concept clustering

In the course of running an eDiscovery case, you can identify many relevant facts and key areas of interest. For example, even in a relatively straightforward contract dispute, you may need to know more about the exact promised date for delivery, the actual delivery date, and the agreed consequences of any delays. To that end, the review would run more smoothly if you could assess the documents and electronically stored information (ESI) on the promised delivery date all at once before moving on to any of the other issues.

AI can enable this type of approach through what is known as the bundling of concepts. Essentially, an AI system can learn to recognize terms that occur together, creating “stacks” of information about each separate problem. By taking random or disorganized data and structuring it into groups, AI can help the legal team quickly make sense of the body of information. When the CSE is presented in concept groups, review teams can increase review speed by 15-20%, saving time and money..

  1. Use of technology-assisted review (ART)

Perhaps the best-known use of AI in eDiscovery is in the review stage, the most expensive and time-consuming part of the eDiscovery pipeline. With technology-assisted review (TAR), a human reviewer begins to assess documents in a corpus, marking them for relevance and privileges, as well as any other labels of interest. As the human examiner moves forward, an AI system effectively monitors their shoulder, learning what words, terms, and phrases may be of interest. The AI ​​then identifies documents that share that language and places them at the top of the stack for the human reviewer to assess. As the exam progresses, the ART software continues to learn and becomes more precise in its assessments, limiting the number of documents that the human examiner actually has to review.

Using ART in the exam can reduce exam time by up to 40%, with associated cost savings. And this has been well accepted by the courts since at least 2015, when US trial judge Andrew J. Peck noted in Rio Tinto PLC v. Vale SA, 306 FRD 125 (SDNY 2015), that “case law has developed to the point that it is now a black letter law according to which when the producing party wishes to use the TAR for the examination of documents, the courts l ‘will allow’.

  1. Drafting of personal information

One of the primary concerns during discovery is to accurately identify personal information so that it can be withheld as privileged, redacted or otherwise anonymized and protected from disclosure.

Fortunately, AI systems can be trained to identify all types of personal information with pinpoint accuracy, flagging these fields for redaction or anonymization. This is an advantage in protecting inside information for eDiscovery, and it allows for greater compliance with privacy laws, such as the EU General Data Protection Regulation (GDPR). or the California Consumer Privacy Act (CCPA).

  1. Generating eDiscovery Analyzes

This is yet another area where AI shines, easily compiling information on expenses, business performance, and case outcomes and presenting it in an easy-to-understand format. Using AI-powered analytics to uncover patterns in your cases or costs can help you resolve recurring issues at the source, assign cases to the most knowledgeable and profitable outside counsel, and better manage your data.

  1. Managing eDiscovery costs

AI can help CLOs save significantly on their eDiscovery expenses. AI helps reduce costs by enabling earlier and more accurate assessment of potential problems so that small problems can be fixed before considerable resources are invested. It speeds up document evaluation by grouping concepts together, which saves on revision. Technology-assisted review further reduces costs by limiting the number of documents human reviewers have to review, saving up to 40% of the cost of the review. AI quickly and accurately reports what to write, saving you time and money. Finally, AI-powered analytics assess spending patterns and case outcomes to identify areas for improvement.

AI offers a plethora of ways for legal teams to outsource repetitive, data-intensive legal tasks, saving them valuable time that they can then use to focus on strategic priorities and improve their own value. for the C suite and the board. In fact, in a survey of legal department operations managers, two-thirds of respondents (64.9%) said they expected legal departments to use AI for legal work in the past. next three years.

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