The use of automation, analytics, and artificial intelligence (AI) in the legal process is something the eDiscovery industry has been talking about for many years now, and one might be inclined to think that the adoption rate is quite high at this point. Which is true to some extent.
The 2021 State of AI and Technology Adoption in eDiscovery report, published by IPRO, ZyLAB and ACEDS, shows that when it comes to non-AI automation tools such as deduplication and DeNISTing, there is a 87% adoption rate, and regarding data processing and OCR, it drop to 74% (side note – that’s the 13%-26% who still don’t do these things!).
For the standard analyzes available in most eDiscovery solutions, the highest adoption rates belong to entity search (77%), basic entity extraction (61%), and foreign languages (61%).
And with the proactive intelligence tools common to eDiscovery, you see a high adoption rate of machine learning. 81% technology-assisted examination (TAR), as well as the related techniques of topic modeling (63%) and concept clustering (68%). Even more advanced options such as relationship analysis (61%) and pattern analysis (49%) are found in the eDiscovery toolkit.
AI for left side of EDRM
So, while there is still room for further adoption, it looks like things are on the right track when it comes to AI and eDiscovery. If, of course, you’re only considering the far right of the eDiscovery Reference Model (EDRM), since all of the above tools and techniques fall under the processing and review stages.
This means that legal teams and law firms still have to process a lot of data the old fashioned way before they can use the benefits of AI-assisted technology, which we highlighted with the eDiscovery Blues cartoon. of the month.
The fact that all AI and technology adoption falls on the right side of EDRM is noted in the report, stating that “most of our respondents said they were working primarily in the review stages and production of eDiscovery, rather than in the earlier stages such as data collection and processing. the right side rests with the law firms, with the help of service providers throughout.
But there are plenty of opportunities for forward-thinking law firms to use AI ahead of the review process.
Law firms, pre-filing investigations and FRCP
When it comes to the court process, always refer to the Federal Rules of Civil Procedure (FRCP) for guidance. And with FRCP Rule 11(b)(3), we find a perfect opportunity for law firms to adopt some of the most advanced (and underutilized) tools available to them.
This rule simply states that before a law firm presents any pleading, written request or other document to the court, “the factual assertions [must] dispose of evidence or, if specifically identified, will likely dispose of evidence after a reasonable possibility of full investigation or discovery. »
In other words, when a law firm decides to take on a case, they must first ensure that the client has the evidence to back up their claims. And that means doing a preliminary investigation of electronic data, including: email communications, collaboration data like MS Teams and Slack, video data from Zoom and other sources, images stored on anything precedes, as well as mobile devices and social media.
This means that if they are only using technology to help find and classify data during the discovery review stage, they must somehow manually sort through all of this electronically stored information (ESI ) to find out if they even have a case.
How technology can help
Direct collection in the cloud
When it comes to taking a quick look at much of the communications data that most people use personally and professionally (e.g. Outlook, Office 365, Microsoft Teams, Google Suite, Zoom, Slack, etc.), the ability to connect to that data directly is essential. With on-site search functions that enable keyword research prior to collection or processing, not only can law firms obtain the necessary information quickly before filing a claim, but they can also reduce processing costs. , hosting and review later in the discovery process.
Yet, according to the State of AI Adoption Survey, only 17% of respondents said they use direct cloud collection.
Classification of images
While image recognition tools have a fairly wide adoption (more than 60%), the automation of the classification of these images by type or subject has not taken the same path (24%). If you think about the number of images that are part of our daily communications, going through them all manually can be time consuming and error prone. And, the adoption of the above image recognition tools occurs during the processing and review stages of discovery, which does not help a law firm conduct an initial investigation of a claim. So tools that can help search and classify images before collection could save a lot of time and money.
Conclusion
While technology continues to be widely adopted in the legal industry, there are still plenty of opportunities to use it to your advantage, and not just when it comes to reviewing documents. Don’t wade through manual processes waiting for your chance to hit the AI button. Instead, start looking for ways to leverage upstream technology.
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