Outside Counsel’s Guide to Mastering ESI Protocols in the Age of Modern Data

Summary: Navigating eDiscovery in the era of modern data presents new complexities that can make or break a case. We explore five critical considerations outside counsel must address, including the implications of generative AI, to ensure they stay ahead in a rapidly evolving legal landscape.

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The already complicated landscape of eDiscovery has dramatically shifted with the advent of modern data (i.e., cloud-based, collaboration, and generative AI data). These data types present challenges due to differences in the way data is created, stored, and managed.

While recent court decisions have provided guidance for handling certain aspects of cloud data, like cloud attachments, the fast-paced evolution of modern data types often leaves a void of applicable case law in its wake.

All this makes representing corporate clients in eDiscovery more technically complex than ever before. As outside counsel, you must have a strong handle on your client’s data to effectively prepare for Rule 26(f) meet and confers and ESI protocol negotiations. To help, I’ve outlined five critical considerations to help you better handle modern data in eDiscovery.

1. Redefine your client’s data and data relationships

When negotiating an ESI protocol, you’ll need to understand and define your client’s relevant data sources—and unpack the relationships between the data to determine how it is collected and produced. Critical factors to consider are:

• Modern attachments in cloud-based systems function like hyperlinks, blurring the lines of what constitutes a distinct document and attachment.
• Enterprise cloud systems can save hundreds of versions, leading to greater replication and proliferation of versions—in turn, creating proportionality burdens.
• Enterprise tools can now also retain audit logs (records of when and how a document is accessed and engaged with), necessitating decisions on whether that data is in scope for eDiscovery.
• Generative AI tools are creating new data at exponential rates. You’ll need to understand what data is being created and how it is being stored to advocate for what is reasonable and proportional to retain and collect.

2. Understand how your client’s data is stored

Understanding how your client's data is stored is no longer optional—it's imperative. Failure to grasp the technical details could lead you to unknowingly agree to unreasonable or impossible production demands on behalf of your client. Before entering negotiations, be sure to consider:

• The specific cloud platforms and applications being used by the client organization
• What license is currently in use and how the options and features under that license might impact data accessibility
• How the client’s system configurations will impact planned eDiscovery workflows

3. Develop collection and search strategies for the cloud era

The days of simple custodian-based collections are gone. You need to understand how your client’s data can be collected and what limitations exist as early as possible in the litigation. Once again, a client’s system licensing, configuration, and capabilities are key areas to consider when evaluating data collection requirements in ESI protocols.

You’ll also need to consider proposed search methodologies. Some traditional search methods limit your ability to find information in nuanced datasets. Providing more effective search options can help you stand out to clients, while saving you from agreeing to ineffective search workflows in ESI protocols.

Key considerations regarding collection and search include:

• The impact of licensing and configuration on collection capabilities
• Advanced search methodologies beyond basic keywords

4. Understand key processing and production considerations

To negotiate data processing and production specifications, you’ll need to have a firm handle on your client’s upstream data capabilities and limitations. If chat data needs to be converted or parsed, you’ll want to know upfront what this will look like and how it’s accomplished.

With custom platforms or workflows, data may be in a non-standard format and associations between data can be forced. Other considerations at this phase include how, and if, metadata is preserved, as well as how data has been tagged.

• The format you’ll need to produce data in
• Preserving and producing relevant metadata
• Converting and parsing chat and cloud-based data

5. Limit scope in the age of gen AI

Generative AI is changing the conversation around scope because of the nature of the data it creates, and the novelty of the technology. Should the scope include all the data created by generative AI, including prompts and responses? If so, that would create a challenge because often those are artifacts, not records, meaning they may not always be in a format that is easily stored and collected. You’ll need to be aware of these issues so that you don’t agree to produce generative AI data that is extremely burdensome (or impossible) to produce.

Be prepared to:

• Address the discoverability of AI-generated content, including prompts and responses
• Determine what generative AI prompt tools are available within your client’s organization
• Find out if there are blanket policies in place for employee use of non-enterprise gen AI

Conclusion

While modern data makes eDiscovery more challenging, it also presents an opportunity for you to differentiate yourself to clients through technical expertise and a thorough understanding of your client’s data.

For more guidance on how you can help your corporate clients solve their modern data challenges, check out our information governance page.