Sat. May 18th, 2024

Editor’s Note: The exponential growth in electronically stored information (ESI) has created immense eDiscovery challenges for organizations. Effective information governance and eDiscovery capabilities are crucial to managing legal risk and obligations. This content outlines key eDiscovery processes – from initial case assessment through defensible disposition of data – to inform discussions around developing comprehensive workflows aligned with organizational needs and resources. A thoughtful approach enables legal teams to control costs, avoid sanctions, leverage ESI for facts, and meet discovery duties. As data volumes and litigation continue rising, a sound eDiscovery framework is essential. This article has been republished with updates from earlier editions to reflect the latest eDiscovery technology and practice developments.


Content Assessment: The Workstream of eDiscovery - Considering Processes and Tasks

Information - 91%
Insight - 89%
Relevance - 94%
Objectivity - 95%
Authority - 90%

92%

Excellent

A short percentage-based assessment of the qualitative benefit of the post highlighting the workstream eDiscovery processes and tasks.


Industry News – eDiscovery Beat

The Workstream of eDiscovery

ComplexDiscovery Staff

From the trigger point for audits, investigations, and litigation to the conclusion of cases and matters with the defensible disposition of data, the myriad approaches data discovery and legal discovery professionals use to administer eDiscovery are as diverse as they are complex. Leveraging research aggregated from leading eDiscovery educators, developers, and providers, the eDiscovery Processes and Tasks listing provided herein serves as a strategic planning tool, guiding business and technology discussions and decisions concerning cybersecurity, information governance, and legal discovery-related eDiscovery projects. It’s important to note that the processes and tasks outlined in this document are not exhaustive but represent a singular perspective on the discipline of eDiscovery.

eDiscovery Processes and Tasks Checklist



eDiscovery Processes and Tasks Through The Lens of Generative Artificial Intelligence

This update also includes subjective assessments of Generative AI (GAI) productivity enhancements, aiming to provide a model for considering the holistic impact of GAI on eDiscovery tasks and processes over the next 12 months. These evaluations offer potential insights into productivity gains that can be achieved through the strategic application of GAI technologies.

GAI Enablement Model Background Notes:

  • Categories: All 102 tasks are categorized into collection, processing, or review workstreams.
  • Task Numbers: Each task in the workflow is assigned a specific tracking number.
  • Process: Eleven processes are identified as subcategory organization areas for all tasks.
  • Tasks: Detailed descriptions of specific workflow tasks for each process.
  • GAI Enablement Rating: A subjective rating assessing the potential near-term (<12 months) productivity impact of GAI on specific tasks, ranging from 0 (No AI Enhancement) to 3 (AI LLM and Prompt Engineer Overview Enhancement).
  • GAI Productivity Multiplier: Estimates of the short-term (<12 months) productivity impact of GAI on specific tasks, measured as Level 0 (0% increase in productivity), Level 1 (15% increase in productivity), and Level 2 (30% increase in productivity).
  • Industry % of eDiscovery Spend: Estimated industry spend on specified categories. Provided as context to potential GAI impact.
  • Industry eDiscovery Spend in 2024: Estimated industry spend on specified categories. Provided as context to potential GAI impact.

By integrating these GAI productivity assessments, this revised listing underscores the transformative potential of AI technologies within the eDiscovery field. It serves as a foundational guide for legal and IT professionals to explore and evaluate how AI can be effectively integrated to enhance operational efficiencies and meet strategic goals in a rapidly evolving digital landscape.

eDiscovery Processes and Tasks Checklist – AI Enablement Model


It’s important to emphasize that while this framework serves only as a model, it might help structure thought about the economics and efficiency of GAI-enabled eDiscovery.

News Sources


Assisted by GAI and LLM Technologies

Additional Reading

Source: ComplexDiscovery OÜ

 

 

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ComplexDiscovery OÜ is a highly recognized digital publication focused on providing detailed insights into the fields of cybersecurity, information governance, and eDiscovery. Based in Estonia, a hub for digital innovation, ComplexDiscovery OÜ upholds rigorous standards in journalistic integrity, delivering nuanced analyses of global trends, technology advancements, and the eDiscovery sector. The publication expertly connects intricate legal technology issues with the broader narrative of international business and current events, offering its readership invaluable insights for informed decision-making.

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Generative Artificial Intelligence and Large Language Model Use

ComplexDiscovery OÜ recognizes the value of GAI and LLM tools in streamlining content creation processes and enhancing the overall quality of its research, writing, and editing efforts. To this end, ComplexDiscovery OÜ regularly employs GAI tools, including ChatGPT, Claude, Midjourney, and DALL-E, to assist, augment, and accelerate the development and publication of both new and revised content in posts and pages published (initiated in late 2022).

ComplexDiscovery also provides a ChatGPT-powered AI article assistant for its users. This feature leverages LLM capabilities to generate relevant and valuable insights related to specific page and post content published on ComplexDiscovery.com. By offering this AI-driven service, ComplexDiscovery OÜ aims to create a more interactive and engaging experience for its users, while highlighting the importance of responsible and ethical use of GAI and LLM technologies.