1. Artificial Intelligence (AI) will increasingly be used for eDiscovery, but results could be a double-edged sword. The consensus within the eDiscovery community is that AI is a useful tool that attorneys should not fear. In fact, AI-based tools, such as predictive coding, privilege reviews, early case analysis, and incoming production analysis, provide vital support to manage resourcing, time, and costs requirements. Predictive coding – an application of machine learning technology that uses algorithms to identify potentially relevant documents using keywords, phrases, and metadata – is more likely to be used in 2024 than in prior years in order to reduce the workload for collected documents. The concern, however, is that AI has the potential to actually create more documents for review to the extent client use of AI generates additional documents. In a world where client charges are based on data size, use of AI could become a double-edged sword.
  2. Changes to collaboration tools will make document collection more manageable. Emails containing attached files are straightforward enough for collection purposes, but what if the email contains links to documents housed within the collaboration tool? That could vastly increase the volume of documents required for collection because the email contains a pointer to a storage platform. Fortunately, some collaboration tools are improving their system capabilities to allow collection of only those linked documents rather than the entire storage platform, which will reduce collection costs. Changes made by collaborative platforms should continue to improve collection management.
  3. Use of collaborative platforms will create preservation issues. Even if collaborative platform changes help manage the volume of documents collected, the problem still exists that those documents are dynamic and able to be edited. And so, changes to the document could be made prior to a litigation hold but subsequent to transmitting the email. Further, when pairing a cover email with a linked document, the paired document may be different now than it was when the email was sent. This possibility creates challenges because a copy of the document as it existed when the email was sent may no longer exist. Thus, spoliation concerns are real, particularly where the content of a document as it existed when its corresponding email was sent is a critical fact in the underlying case.
  4. Proliferation of AI will result in AI errors, biases, glitches, and hallucinations. Using AI in eDiscovery may more readily identify helpful evidence, but AI used out in the real world may also result in more unreliable (or fake) evidence. AI technology continues to advance and improve but nothing is failsafe. And so, practitioners must validate and understand AI used not only in the eDiscovery space, but also how it is being used to generate content that may become evidence in a case, and be mindful to not unwittingly put forward misleading or false evidence or submissions.
  5. A growing emphasis on AI’s role in eDiscovery will cause practitioners to be more mindful of the agreements they reach with Electronically Stored Information (ESI) protocol. It will be increasingly common for parties to review and revise their ESI protocols in an effort to anticipate new challenges in the eDiscovery space. This may include provisions regarding use of AI and protocols concerning treatment of links to collaborative workspaces. An ESI protocol should lead to fewer eDiscovery disputes and early resolution of any eDiscovery disputes that do arise. The best ESI protocols will provide both predictability and flexibility to account for the realities that discovery is an evolutionary process and circumstances may change as discovery unfolds. Notably, some judges are more rigid than others when it comes to enforcing strict adherence to the ESI protocol and thus practitioners should be prepared to account for the terms agreed to in their ESI protocols.