The eDiscovery landscape is undergoing a profound transformation, driven by the rapid evolution of artificial intelligence (AI). What was once a labor-intensive, manual process is now being revolutionized by technologies capable of analyzing vast volumes of data with speed, precision and insight. AI is not just a buzzword; it’s a catalyst for smarter, faster and more defensible legal workflows. This article outlines how AI is advancing the pace, efficacy and impact of the eDiscovery process while sharing some real-life examples.
The Rise of AI in eDiscovery
The ability to harness AI is no longer optional—it’s essential. Legal teams are expected to deliver results faster, with greater transparency and defensibility. AI empowers them to do just that, while also unlocking new possibilities for collaboration, risk management and innovation.
AI has steadily gained traction in the legal and compliance sectors, particularly in eDiscovery, where the need to sift through massive datasets is constant. From predictive coding and sentiment analysis to automated document classification and generative AI, these tools help legal teams uncover key insights, reduce costs and improve accuracy.
As data volumes grow and cases become more complex, AI enables professionals to focus on strategy and decision-making rather than manual review. It’s changing how we think about relevance, privilege and responsiveness.
For example, the use of AI data visualization enables investigators to detect anomalous email activity in an employee’s account and help determine the root cause of a cyber incident. Professionals can now visually identify gaps in communications over a period of time, indicating potential mass deletion activity and areas for additional analysis. Alternatively, they can instead focus on spikes in off hours and weekend activity indicating potential suspicious behavior. AI also now enables visualizing email communications among individuals, allowing professionals to quickly identify data exfiltration points or other custodians involved. AI can be leveraged to identify risk factors or signals that, when considered individually, may seem insignificant, but when analyzed collectively, can be highly indicative of suspicious behavior. Given the increasing sophistication of bad actors, traditional AI models that do not adapt or learn over time become significantly less effective.
How AI Advances eDiscovery Processes and Insights
With its critical role in uncovering data to inform legal cases, investigations and other scenarios, eDiscovery draws on many sophisticated technologies and approaches. The way we use, manage and retain data continues to change, as does the way that cybercriminals attempt to access and leverage that same data. eDiscovery has adapted in response. However, the recent surge in the availability of AI tools and techniques—and the responding shifts in cybercrime—has accelerated this evolution. Today, AI is redefining eDiscovery for several important reasons, including:
Volume of Data
- Legal cases often involve massive amounts of digital data, such as emails, documents, chat content and social media. AI enables better management and analysis of this data.
Speed and Efficiency
- Traditional manual review is slow and expensive. AI can quickly sift through millions of documents to identify relevant ones.
Cost Reduction
- By automating parts of the review process, AI reduces the need for large teams of attorneys and paralegals, cutting costs significantly.
Improved Accuracy
- AI can reduce human error and bias, especially in tasks like identifying privileged or confidential information.
Predictive Insights
- AI can identify patterns and trends in data that might not be obvious to human reviewers, helping to build stronger legal strategies.
AI and eDiscovery: Changing the Investigative Landscape
Major leaps forward in AI mean that it is advancing eDiscovery in critical ways, such as:
Clustering and Categorization
AI enables the grouping together of similar documents to streamline and accelerate the review process. It also helps to identify duplicates, or near-duplicates, and organize data thematically.
Technology-Assisted Review
Through machine learning, AI enables technology-assisted review, or the prioritization and classification of documents based on relevance. Common methods include predictive coding, where the system learns from human reviewers and applies that knowledge to unseen documents.
Natural Language Processing
Natural language processing helps to provide greater insight into context, sentiment and meaning in unstructured text. This is valuable for the identification of key topics, entities (people, places, organizations) and relationships.
Generative AI
Generative AI uses deep learning models to quickly understand datasets and communicate to reviewers what may be relevant to the matter. It achieves this by providing a method of querying and interrogating datasets
At its core, AI in eDiscovery is about enhancing human expertise. However, it is important to emphasize that this is not about replacing professionals but amplifying their capabilities. While AI can dramatically accelerate workflows and uncover insights at scale, it is the knowledge, experience, and investigative mindset of skilled professionals that ultimately drive quality outcomes. The most effective use of AI occurs when experts thoughtfully identify the problem, select the appropriate tools and guide the technology to deliver meaningful results.
AI models have advanced significantly, but they still require human oversight. Keeping the human in the loop is essential, not only to mitigate risks like hallucinations or misclassification, but also to ensure ethical and defensible practices. Blindly deploying AI without supervision can lead to errors, inefficiencies and even reputational harm.
What we’re seeing now is a shift in how professionals approach their work. They’re learning to pair their analytical skills with cutting-edge AI capabilities to solve problems in new, more strategic ways. This human-AI collaboration enables teams to streamline processes, improve accuracy and focus their time on complex, high-value tasks rather than routine review.
Ultimately, the highest quality eDiscovery results come from this partnership, where technology amplifies human judgment and professionals elevate the impact of AI through thoughtful application and continuous learning.
Leverage AI-Powered eDiscovery with Kroll
Kroll’s scalable eDiscovery solutions are trial-tested for unrivaled speed, accuracy and insight. Harnessing Kroll’s global expertise in cyber risk, investigations, compliance, disputes and risk management, our experts have deep experience in supporting privacy, litigation and investigations at scale to optimize the eDiscovery process.
At Kroll, we’re proud to be at the forefront of leveraging the transformative impact of AI on eDiscovery. As a Relativity Gold Partner, we have long embraced cutting-edge solutions to help our clients navigate complex data challenges. This ongoing commitment means that our entire team is undergoing certification in Relativity Generative AI, ensuring that every member of our organization is equipped to deliver the most advanced, AI-powered solutions available. We’re not just adopting AI; we’re investing in it, understanding its limitations and positioning ourselves as a trusted partner in this evolving space. This investment reflects our belief that AI is not just a tool; it’s a strategic imperative.
Meet With Kroll at Relativity Fest Chicago
We will be at Relativity Fest Chicago this year from October 7-9 and we’d love to connect with you. Whether you’re just beginning your AI journey or looking to deepen your capabilities, our team is ready to share insights, answer questions and explore how we can help you harness the power of AI in your eDiscovery workflows.
Reach out or schedule a one-on-one; we’re here to talk about the next chapter of eDiscovery. Let’s build smarter, faster, and more resilient legal solutions—powered by AI.
