GenAI Beyond Review: Building Exhibits from Intelligence
Artificial intelligence—particularly generative AI and large language models (LLMs)—is rapidly transforming how we live, work, and analyze information. According to one survey, 52% of US adults reported having used GenAI chatbots. 72% of those surveyed have used ChatGPT, 50% have used Google’s Gemini, and 39% have used Microsoft’s Copilot. These chatbots are being used for a variety of tasks, including writing, summarizing content, generating new ideas and more.
That revolution extends to litigation and eDiscovery. GenAI is beginning to revolutionize how legal teams approach the end-to-end management of eDiscovery by automating complex, time-consuming tasks like document review. Traditional linear review workflows are finally starting to be replaced by intelligent systems that can classify documents, identify patterns, and extract relevant entities and concepts with high accuracy.
Sentiment regarding the promise of GenAI is strong. In the 2025 State of the Industry Report published by Elite Discovery’s partner, eDiscovery Today, 26% of 551 respondents said they expect GenAI to have a transformative effect on eDiscovery solution offerings and workflows this year. More than four in five respondents (81.7%) said they expect it to at least create new workflows this year.
How GenAI Is Transforming Document Review for eDiscovery
Without a doubt, the transformative effect of GenAI is most discussed in terms of how it can transform document review. GenAI is streamlining document review by enabling more intuitive and efficient workflows that adapt to the legal context of a case. Unlike traditional rule-based or supervised learning approaches that rely on predefined training sets, generative models can infer meaning, sentiment, and intent across documents with limited input.
This enables legal teams to engage with data more naturally—for example, asking an AI to “find documents showing the defendant’s knowledge of the issue.” Such contextual queries help uncover relevant content faster, improving both speed and accuracy in the review process.
As a technology partner with eDiscovery platforms like Relativity, Reveal, and Everlaw, we’ve seen what these platforms can do to leverage AI and GenAI to streamline document review. The ability to classify documents quickly at a high rate of accuracy based on natural language instructions promises to transform how document review is conducted. Given that review costs have been historically as much as 73% of the total eDiscovery spend, it’s logical that most of the discussion regarding the benefits of GenAI relates to document review.
However, the same discussion regarding GenAI and document review also inevitably invites comparisons to predictive coding and concerns about whether the adoption rate of GenAI in the legal community will be impacted by the same barriers to adoption we saw for predictive coding – such as complexity and concerns over transparency.
At Elite, we were early adopters of predictive coding technologies and methodologies, such as continuous active learning, and have been providing services related to the use of predictive coding for over a decade. What we’ve seen so far with the implementation of generative AI with our technology partners is that it is easier to use than predictive coding implementations have been. GenAI is also less of a “black box” in terms of how it classifies documents than predictive coding because it provides a description of why it classified each document the way it did, so it promises to be more transparent than predictive coding has been.
How GenAI Can Streamline the Process of Insights to Exhibits
Despite the considerable benefits of streamlining document review, GenAI’s greatest strength may be its versatility. Unlike predictive coding workflows and technologies (which are document review-centric), GenAI can be applied to many more use cases throughout the entire lifecycle of the discovery process or even the entire litigation.
In the State of the Industry report mentioned above, more than 30% of respondents said they apply LLMs and GenAI to seven different eDiscovery use cases! In addition to document review, those use cases were document summarization, privilege and PII identification, case strategy, and early case assessment (ECA), document translation, timelines of key events, and deposition prep and summaries.
Those last two use cases illustrate GenAI’s underdiscussed strength: GenAI can be used to generate insights as exhibits to streamline trial preparation.
GenAI can not only be used to gather insights from a document collection – it can deliver those insights in a manner that can streamline the process of creating exhibits for trial.
Here are two examples of insights to exhibits using AI:
Deposition Summaries
It’s no surprise to us that deposition prep and summaries was one of the top use cases for GenAI: summarizing depositions has always been a pain – it can be extremely time-consuming and labor intensive. By leveraging AI, you can now transform lengthy deposition transcripts into concise, comprehensible summaries in minutes – and you can do so in a variety of different formats:
- Narrative Summary: A clear and engaging format that transforms deposition testimony into a story-like account. It highlights the most significant points and statements in a way that enhances readability and comprehension.
- 10:1 and 5:1 Page-Line Summary: This highly detailed summary format condenses the transcript by capturing key points alongside their corresponding page and line references. It offers a streamlined overview while preserving precise citations, making it ideal for quickly locating specific testimony within the original transcript.
- Deposition Abstract: This concise overview provides a high-level summary of an entire deposition of any size, which can accompany the narrative and page-line summary formats.
AI’s ability to quickly create deposition summaries not only generates insights about the deposition testimony, but it also puts the evidence in a format that “jump-starts” the generation of exhibits.
Medical Chronologies
These structured timelines present a clear sequence of medical events, offering an effective way to understand a patient’s medical history. Particularly valuable in cases involving personal injury, medical malpractice, product liability, or insurance disputes, medical chronologies simplify complex medical information – making it easier for legal teams to analyze and for juries to comprehend.
Without leveraging AI, creating these chronologies is a time-consuming and laborious process. With AI, you can not only quickly scan through your collection of medical records to find the most relevant details (such as hospital admissions, surgeries, diagnoses, and treatment changes), but you can also output those details in organized timelines, creating step-by-step records of the patient’s medical journey in chronological order, tied directly to the documents.
Conclusion
We are just beginning to scratch the surface of use cases for generative AI in discovery and litigation. While GenAI’s impact on streamlining document review can’t be ignored, applying AI and GenAI to a variety of other use cases—like generating insights as exhibits to streamline the presentation of evidence in legal proceedings—enables legal teams to truly maximize the technology’s potential. The sky’s the limit!
For more information regarding Elite’s AI-powered deposition summaries and medical chronology services, click here.
Contact us today or schedule a demo to explore how we can support your cases with cutting-edge solutions!
