As we’ve been wrapping up 2021 and looking forward to 2022—again hopeful that at some point this year we’ll see more of a return to “normal” life, whatever that means—I wanted to pause to reflect on our evolving data landscape. We’ve had two years of constant, chaotic change, with no clear end yet in sight. The legal industry has primarily risen to the challenge of managing increased caseloads and maintaining regulatory compliance amidst tremendous disruption. Still, we likely have not felt all of the repercussions of 2020 and 2021.

Here are my five takeaways about what I expect to see in the world of ediscovery in 2022 and beyond. 

1) Continued Growth in the Use of Collaboration Apps—Even When Offices Reopen

I don’t have a crystal ball, so I won’t try to predict when or whether offices will reopen in full force. But I am confident that businesses will continue to rely heavily on collaboration and chat-based messaging applications like Slack, Microsoft Teams, Zoom, Asana, and more, whether we’re working remotely or back in our shared office spaces. The reliance on these tools was rising before the pandemic and has become crucial for many organizations. 

We’re past the point of “peak email” and are entering a time where collaboration apps and chat messages will become the dominant form of business communications. That means that organizations need to think about how they’re preserving and governing the data generated by those applications, which brings us to our next point.

2) Greater Acceptance of Collaboration Data’s Relevance to Litigation and Compliance 

Initially, many businesses simply ignored or deemed collaboration data as being outside the scope of discovery.  As collaboration data has grown into its new status as a replacement for email, organizations have come to terms with the reality that it represents a discoverable data source. Yet this reluctance by organizations to change with the pace of technology follows a familiar trend; in the early days of ediscovery, companies often agreed to leave email off the table in favor of hard-copy forms of information. That attitude is about to become untenable.

Forward-thinking organizations have already acknowledged the importance of collaboration data and folded it into their ediscovery and information governance pipelines. Indeed, recent court decisions have affirmed the discoverability and proportionality of collaboration content. They recognize that collaboration applications are becoming the main form of business communication. Organizations that haven’t laid that foundation yet will soon find that they’re behind the times. 

Regulatory agencies are also likely to start asking for collaboration data in their inquiries. Many companies let down their guard in a rush to enable remote work in the early stages of the pandemic. Now is the time to finish repairing any gaps that were inadvertently created during that transition and fully incorporate collaboration data into the compliance management framework. 

Privacy regulations, in particular, are building momentum. I expect that trend to continue—and as it does, regulators will demand that businesses pay attention to where they store and use sensitive data. Organizations should assess their exposure, determine their risk tolerance, and devise an actionable plan to combat the risk. 

3) An Explosive Increase in Data Complexity

While I’ve been referring to “collaboration data” as a single broad category, it comprises a tremendous range of new applications and data types. 

For example, organizations on average use around 110 different software-as-a-system or SaaS applications. That represents 110 sources of potentially discoverable business communication. Furthermore, each collaboration app grows in complexity and function, resulting in a greater variety of data types within each app or platform. 

Slack is a great example; it now boasts integrations with over 2,400 apps, from Salesforce and Google Drive to Zoom and Microsoft Teams. Simple-to-implement workflows and new ways to communicate (such as huddles and clips) through Slack increase the complexity of preserving and collecting the relevant information for investigations and discovery. As ever, the context of that data is critical.

As a result, organizations will have to work harder than ever to understand and capture all of the types of discoverable data that they generate as they go about their work. 

4) Changing Levels of Confidence in the Ability to Manage Collaboration Data for Ediscovery

We’ve seen an interesting trend in user confidence as collaboration data has come to the forefront of business communication. As collaboration data grows more complex—and as courts affirm its discoverability—user confidence in the ability to manage that data can decline. It is not unexpected that when legal teams haven’t yet been required to deal with collaboration data in discovery, they don’t anticipate all of the difficulties they will encounter. Their confidence starts to wane as they gain experience working with that data and face novel challenges.  Not surprisingly, I am optimistic that confidence will rise as teams incorporate tools and technologies to help them better manage their collaboration data. 

5) Widespread Use of AI and Machine Learning to Distill and Understand Collaboration Data

Artificial intelligence is one of the tools that legal teams will need to use to keep up with the deluge of business data. Searching manually through loads of collaboration data to find specific conversations is not a viable approach. AI and machine learning offer a way to localize important data and understand its context quickly. The ability to search for similar terms or related language and drill down into specific conversations and relationships will be critical to identifying essential information. With the aid of AI, it will become easier to discover private user data, and detecting unwanted behavior will be vital as organizations try to deal with the glut of collaboration data they generate every day. More off-the-shelf software capabilities will also make integration with data platforms more manageable and more accessible than ever while delivering data intelligence at an unprecedented level and scale.

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