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 the rate of adoption is pretty high at this point. Which is true to an 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 like deduplication and DeNISTing there is an 87% adoption rate, and when it comes to Data Processing and OCR, it drops to 74% (side note – who are the 13%-26% still not doing these things!).

For standard analytics available in most eDiscovery solutions, the highest adoption rates belong with entity search (77%), basic entity extraction (61%), and foreign language extraction (61%).

And with proactive intelligence tools common in eDiscovery, you see a high adoption rate of the machine learning driven Technology Assisted Review (TAR) at 81%, as well as the related techniques of topic modeling (63%) and concept clustering (68%). Even more advanced options like relationship analysis (61%) and pattern analysis (49%) are finding their way into the eDiscovery toolkit.

AI for the left side of the EDRM

So, while there is still some room for further adoption, it seems things are on a solid track when it comes to AI and eDiscovery. If, of course, you’re only considering the far right side of the eDiscovery Reference Model (EDRM), since all the above tools and techniques fall in the Processing and Review stages.

This means that legal teams and law firms are still having to work through a lot of data the old fashioned way before getting to utilize the benefits of AI-assisted technology, which is what we’ve highlighted with month’s eDiscovery Blues cartoon.

The fact that all the AI and technology adoption falls on the right side of the EDRM is noted in the report, saying “most of our respondents reported that they work primarily in the review and production stages of eDiscovery, rather than in the early phases such as collection and data processing.” And it’s long been understood that left side EDRM tasks typically fall to in-house corporate legal teams and the right side falls to law firms, with help from service providers throughout.

But there are plenty of opportunities for forward thinking law firms to utilize AI before the review process.

Law firms, pre-filing investigations, and the FRCP

When it comes to the legal process, one should always go back 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 more advanced (and under-utilized) tools available to them.

This rule simply states that before a law firm presents a pleading, written motion, or other paper to the court, “the factual contentions [must] have evidentiary support or, if specifically so identified, will likely have evidentiary support after a reasonable opportunity for further investigation or discovery.”

In other words, when a law firm decides to take on a case, they have to first make sure 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 all the above, as well as mobile devices, and social media.

This means if they are only utilizing technology to help search and classify through data during the review stage of discovery, they have to somehow sort through all of this electronically stored information (ESI) manually to know if they even have a case.

How Technology Can Help

Direct Cloud Collection

When it comes to taking a quick look at a large slice of the communication data most people both personally and professionally use (e.g. Outlook, Office 365, Microsoft Teams, Google Suite, Zoom, Slack, etc.,) the ability to connect to that data directly is key. With in-place search functions which allow keyword searching prior to collection or processing, not only can law firms gain that quick insight needed before filing a claim, they also can reduce processing, hosting, and review costs later in the discovery process.

Yet according to the State of AI adoption survey, only 17% of respondents stated they used direct cloud collection.

Image Classification

While image recognition tools have somewhat wide adoption (over 60%) automating the classification of those images by type or topic hasn’t caught on in the same way (24%). If you think about how many images are a part of our daily communications, going through them all manually can be time consuming and prone to error. And, the adoption of image recognition tools above happens during the processing and review stages of discovery, which doesn’t help a law firm doing an initial investigation into a claim. So, tools which can help search and classify images before collection could save a lot of time and costs.

Conclusion

While there continues to be wide adoption of technology in the legal industry, there are still many opportunities to use it to your advantage, not simply when it comes to document review. Don’t trudge through manual processes waiting for your chance to hit the AI button. Instead, start looking for ways to leverage technology upstream.

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