How modern technology is changing eDiscovery – for the better

It took less than six months between ChatGPT first bursting on the scene to becoming a standard tool in many South African businesses. Local futurists are sharing their tips and advice on how to make the most of large language models (LLM) such as ChatGPT and artificial intelligence (AI) in all spheres of business. The future is here, and within the legal landscape it’s teaching us two key things. First, as digital transformation continues to accelerate, cloud-based and software-as-a-service (SaaS) models are growing at lightning speed. They are expected to outpace traditional IT approaches within the next few years. Artificial intelligence (AI) and other legal technologies are, unsurprisingly, also proving their worth as critical tools for all types of eDiscovery projects.

Unsurprisingly, both in-house and external legal professionals are adapting to these changes, finding ways to cut down on time, energy and costs, not only during and after the electronic document review (EDR) process, but also before it, through early case assessments, diligent information governance, and other proactive solutions.

Let’s take a look at what those solutions are, and how they can keep your organisation ahead of the technology curve.

SaaS and cloud-based models

A major transformation in the legal arena is the shift from traditional on-premise setups to SaaS and cloud solutions. With extremely high data security safeguards that are compliant with local and international standards, legal firms and large enterprises alike are able to leverage the scalability of cloud with the flexible pay-as-you-go structures that eliminate significant upfront costs and provide predictable monthly fees. This move to the cloud may have begun slowly, but Gartner predicts that cloud-based spend will surpass traditional IT expenditure by 2025.

The rise of structured data

Most data is unstructured. From Word documents to digital photos, emails to Zoom call transcripts and WhatsApp messages, unstructured data lacks an identifiable structure or predefined data model. This results in a large amount of duplication and makes it difficult for computer programs to efficiently store and manage it. It’s one of the reasons why most businesses have so much data stored, even though it comes at a heavy cost. Reviewing thousands of gigabytes of unstructured data for relevancy and privilege is also the most time-consuming and expensive parts of the entire eDiscovery process.

The shift to the cloud isn’t just solving cost and storage problems, however. It’s also addressing the issue with unstructured data. As more businesses shift to cloud-systems that are often based on structured data models, they are reaping the benefits of structured data, which can save organisations precious time and money given how much easier it is to store, find and analyse.

Complex eDiscovery architectures

Whether you remember the days of digging through boxes or not, document review today is electronic, since most – if not all – of the data being reviewed is digital. However, it’s important to realise that just like with all technology, eDiscovery architectures are constantly evolving, becoming far more complex with the introduction of assorted file types generated by collaboration tools, chat platforms, and other apps. Consider how recorded Zoom meetings and other video conference calls have become discoverable evidence over just a few short years. The good news is that technology has kept pace, and solutions like automated transcription are helping legal professionals find useful and relevant information with minimal time and effort.

Workflow automation streamlines eDiscovery

According to Gartner research, 2023 is the year that will see a third of corporate legal departments employing a legal technology expert specifically to support in-house counsel with workflow automation initiatives.

One reason for this is because workflow automation is particularly helpful in eDiscovery, allowing teams quickly and automatically identify and reject irrelevant data, eliminating the need for manual processes.

Your teams can make the most of workflow automation by creating workflow templates that support different projects and create a clear map of who is responsible for each piece of the process.

Remote and hybrid work models are here to stay

The shift to remote work had a profound impact on Discovery. First, it triggered an explosion in the types and amount of digital data created through collaboration apps. Between March and December 2020, Microsoft Teams, Zoom, and Slack experienced staggering growth rates of 3891%, 1788%, and 1073%, respectively. A shift to hybrid work has most likely not lessoned this new way of working either, since collaboration apps have become the de facto way of working, which means the amount of new potentially discoverable evidence has grown for the foreseeable future.

And then, of course, it changed where and how eDiscovery and EDR professionals perform their jobs. We’ve spoken extensively about SaaS and cloud solutions in this article, but it’s a point worth reiterating – secure eDiscovery tools and servers are important because teams need to be able to access data from multiple different devices and locations.

AI will shape the eDiscovery process

AI is not limited to chatbots. It is fast becoming an expected and integral part of the eDiscovery process. From predictive coding to data analytics, AI will have as much of an impact on eDiscovery solutions in the future as it does on every other industry, allowing EDR and eDiscovery professionals to work more efficiently and effectively than ever before.

According to Law Technology Today, AI will be able to act as both an orchestrator “learning from past actions and results and coordinating tasks across multiple channels,” and a curator that “can recommend documents for deeper review (much like Netflix recommends a new movie or TV show).” This will change the way legal professionals manage all levels of the discovery process, adding layers of quality while simultaneously reducing costs, complexity and time. Organisations that do not leverage these tools will be at a large disadvantage to those that do.

Automated ECA will spearhead successful in-house eDiscovery

Early case assessment (ECA) is a preliminary step in the discovery process that helps legal teams prepare for litigation by more accurately predicting the cost of a case ad helping eDiscovery teams to create realistic legal budgets for the full discovery process and any ongoing litigation. For corporate law departments that are increasingly expected to forecast and adhere to their budgets in unpredictable operating environments, automated ECA is particularly important.


Let modern technology solve your eDiscovery challenges

eDiscovery is more complex than ever before, but rapidly evolving technologies can help organisations overcome these new challenges.