October 14, 2024

Consulting discovery document review data artificial intelligence

Leveraging your eDiscovery software’s suite of AI and analytics features can significantly enhance your data analysis and decision-making processes.

Over the past 12 months or so, the legal industry has been abuzz about AI. eDiscovery is no exception. But beyond the hype and promise of Gen AI, what are the particulars of how it and AI-powered analytics aid eDiscovery? The answer is that leveraging your eDiscovery software’s suite of AI and analytics features delivers several distinct benefits, including enhancing your decision-making processes, improving the accuracy of responsive and privilege reviews, prioritising and sequencing materials for review and deposition or trial preparation, and streamlining workflows for identifying key documents.

These benefits begin with the ability of advanced AI and analytics tools like machine learning algorithms and data visualisations to help law departments and law firms uncover hidden patterns and insights within their data. These insights enable the benefits previously mentioned:

Proactive Data Management. One of the most compelling aspects of AI and analytics is that they allow case teams to identify trends and help make informed decisions that may drive strategic objectives.

Contrast this with ‘pre-AI’ eDiscovery, whereby it was virtually impossible to differentiate the signal from the noise to understand which documents were most likely relevant and deserved the most attention. Using AI and analytics to inform eDiscovery decisions not only boosts productivity but also sharpens an organisation’s competitive edge in a data-driven landscape.

Prioritising Data. When applied to predefined data types and organised datasets, analytics can guide users in concentrating on specific patterns, trends, and relationships through clearly defined criteria. This approach is particularly effective for tasks like identifying unique email threads, categorising documents, or identifying duplicates (or textually similar documents) based on structured data fields. The last task is especially important when the differences between different versions and drafts of the same document may prove key to your case.

Obtaining Insights. Advanced machine learning algorithms can enable users to identify themes, concepts, and contextual relationships within your data set that traditional approaches may not. Unaided by the power of AI, many of these insights will not be immediately apparent, if at all. AI and advanced machine learning are especially impactful in analysing complex documents and extracting meaningful information from a broader context. To give two examples of when AI tools can make an impact: in cases in which opposing counsel produces hundreds of thousands of documents leveraging AI and cluster analytics can provide high-level analysis of the material and group documents according to conceptual similarities, and in instances when a client over-collected material, AI and predictive coding enable you to target relevant documents faster than otherwise possible.

Organising and Streamlining Reviews. There are also benefits to be had using your eDiscovery software’s built-in suite of AI and analytics tools before transitioning to GenAI. One is that built-in tools enable users to better understand their data, including identifying patterns, trends, and key insights. That knowledge forms a solid foundation for integrating GenAI workflows and fosters confidence and familiarity with data structures, both of which are crucial when applying more complex, AI-driven capabilities. Another benefit comes from the ability of built-in AI analytics to streamline data preparation. This ensures that the data is clean and organised, thereby enhancing the effectiveness of GenAI in generating actionable insights that align with an organisation’s strategic goals. This incremental approach – ‘preparing the field’ with built-in AI and analytics tools – boosts confidence in GenAI’s accuracy and also allows you to achieve the maximum potential to automate tasks and enhance overall efficiency in data management while maintaining cost efficiencies.

As with many emerging technologies, some of the claims about AI’s capabilities have far exceeded the facts on the ground. However, in the realm of eDiscovery, the technology is already having a substantial impact – for those who understand the benefits it can provide.