Are your litigation strategies still relying on slow, manual review? Early case assessment has evolved into a faster, more precise process with the help of AI and automation. These advances help legal teams uncover risks sooner, preserve evidence more effectively, and focus on the facts that matter most.
Today, we're taking a closer look into how GenAI-powered e-discovery and modern legal hold practices are transforming litigation technology, along with the tools and strategies shaping this shift.
Early case assessment is one of the most important stages in preparing for litigation. It helps legal teams make informed decisions early in the process.
The goal is to save time, control costs, and reduce risk. Modern tools and strategies now make it easier to review and act on large sets of information before a case moves forward.
There are three main points to understand about early case assessment:
Early case assessment is the practice of reviewing available evidence, facts, and risks before committing significant resources to a case. It allows legal teams to determine the strength of a matter, the likely costs, and whether settlement or further litigation is the best path.
Traditional early case assessment often relied on manual document review and basic keyword searches. This method can be slow and expensive. Modern case assessment tools can quickly analyze vast amounts of information, highlight key facts, and support faster decisions.
Early case assessment happens before full-scale eDiscovery review. It connects initial data collection to later review and production stages. By placing it at the start of the process, legal teams can narrow the scope of data, focus on relevant issues, and build a stronger litigation strategy from the beginning.
GenAI is changing how legal teams work with large volumes of data in eDiscovery. It brings new ways to review, analyze, and prioritize documents that would take far longer with traditional methods.
There are three main points to understand about the rise of GenAI in eDiscovery:
GenAI in eDiscovery refers to systems that can read, interpret, and summarize documents in ways that feel more natural than older search and review tools. It can group related documents, identify possible relevance, and flag sensitive information much earlier in the process.
Manual review of large data sets can be slow and costly. GenAI can process thousands of documents quickly while highlighting patterns and important details. This means less time spent on low-value files and more focus on materials that matter most to the case.
Assisted legal review benefits from GenAI because it can guide attorneys toward the most relevant content faster. It does this by ranking documents, detecting topics, and suggesting connections between pieces of evidence. It helps teams create stronger strategies without losing valuable time on broad, unfocused review work.
Legal hold is a critical step in protecting evidence during litigation. It involves notifying custodians about their duty to preserve specific data and monitoring compliance. This process can be time-consuming and prone to errors when handled manually.
GenAI in legal hold offers a way to manage these responsibilities with greater speed and clarity.
There are three main points to understand about GenAI in legal hold and preservation:
GenAI can create clear, consistent notifications that are customized to each custodian's role. It can track acknowledgments in real time and flag individuals who haven't confirmed receipt. This reduces the chance of missed communications and creates a stronger record for compliance.
GenAI can review case details and anticipate which custodians or data sources will likely need preservation. This allows legal teams to act before requests come from opposing counsel. It also helps limit the scope to what is most relevant, which can reduce unnecessary storage and review.
Missed deadlines or overlooked custodians can lead to spoliation claims. By monitoring compliance and providing alerts for at-risk data, GenAI can help protect evidence integrity. This supports both the legal strategy and the organization's credibility during litigation.
Technology-assisted review, often called TAR, has become a central part of modern eDiscovery. It uses software to help legal teams decide which documents are most likely to be relevant.
TAR uses algorithms to predict the relevance of documents based on examples reviewed by attorneys. Once the system learns from a set of reviewed documents, it can sort through large data collections and group the most likely relevant ones for further review.
GenAI can improve TAR by recognizing context and intent in ways that older systems could not. It can connect related information, spot unusual patterns, and adapt as new information is found. This helps legal teams focus on evidence that may otherwise be overlooked in traditional review methods.
By ranking documents by their likelihood of relevance, TAR and assisted legal review can save hundreds of hours in manual review.
Early case assessment is no longer limited to manual review and guesswork. Get in touch today to find out how we can help with your ECA.