5 Practical Ways to Use AI in eDiscovery—and Save Time and Money

Summary: Discover five practical ways to use AI in eDiscovery, including early case assessment and automating data collection, to streamline workflows, cut costs, and improve accuracy—transforming legal review and investigations.
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Recent industry analysis from Complex eDiscovery suggests that document review costs will decrease from 64% to 52% of total eDiscovery expenses by 2029, driven by advances in generative AI, TAR, and predictive coding. AI continues to make eDiscovery more scalable, accurate, and affordable—hallmarks of technology with staying power. As organizations navigate the AI-driven evolution of data intelligence, here are five practical applications that can make eDiscovery more efficient and cost-effective.

Trend 1: Performing early case assessment

What is it? AI-bolstered early case assessment (ECA) tools analyze large document collections during initial discovery phases, quickly identifying potentially relevant materials and key themes. These tools leverage predictive algorithms to provide rapid insights into case materials.

What makes it cost-efficient? By reducing manual document review, which typically accounts for 70-80% of eDiscovery costs, ECA tools deliver substantial savings while providing early strategic insights into case strengths and weaknesses.
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Trend 2: Redacting sensitive information

What is it? AI can automatically identify and redact sensitive information like personal identifiers, financial data, and privileged content. Using an AI classifier that’s trained to recognize specific sensitive information types like PII and PHI, the technology locates the information for responsiveness (such as for a regulatory request) and can also redact it prior to production.

What makes it cost-efficient? Automated redaction dramatically reduces the manual effort required, potentially saving hundreds of attorney hours per case while maintaining consistency and accuracy.
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Trend 3: Automating data collection

What is it? AI-powered data collection automatically identifies relevant data sources across an organization's digital landscape, from email servers to cloud storage platforms, while simultaneously initiating and tracking legal holds, monitoring for potential spoliation risks, and maintaining chain of custody documentation.

What makes it cost-efficient? This automated approach not only reduces human error and manual effort but also ensures more comprehensive and defensible data collection processes. It’s an investment up front that pays long-term dividends with decreased time to review and minimized burdens of attorney rework.
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Trend 4: Drafting ESI protocols

What is it? Attorneys can pop into ChatGPT or Copilot for Word and prompt the AI to write ESI protocols based on historical agreements, court orders, and case law. The AI can suggest optimized terms and conditions tailored to specific case requirements, also identifying potential data sources, search methodologies, and time frames.

What makes it cost-efficient? AI assistance streamlines the initial drafting process, reducing attorney time spent creating the bones of an agreement or protocol and giving practitioners a framework to build on—shaving time off front-end setup while only requiring (as with any written negotiation) attention to accuracy and detail.
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Trend 5: Fact finding

What is it? AI-powered document analysis tools are revolutionizing how legal teams identify and extract critical information from large document collections by using tailored AI classifiers to tackle specific review tasks like identifying confidentiality, privilege, and key documents related to specific case issues. Instead of traditional linear review, these intelligent systems can rapidly remove large volumes of irrelevant documents from the review queue, speed up the review process for remaining documents, and deliver critical insights to the case team faster and more efficiently.

What makes it cost-efficient? By dramatically reducing the time lawyers spend reading through voluminous document sets, AI document analysis can cut document review costs significantly— one recent project saw a savings of $1M when moving to AI classifier-driven review and away from linear. The technology not only accelerates the review process but also improves accuracy by consistently applying intelligent categorization and highlighting potentially critical documents that might be overlooked in traditional manual reviews.
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AI + HI ensures trends in the right direction

As legal, compliance, and IT teams find more ways to incorporate AI into everyday work, the need for HI (human intelligence) has never been greater or more applicable. These five trends represent ways organizations can begin incorporating AI into their legal, investigative, and regulatory work, and their uniting factor is human sensibility, creativity, and judgment to elicit the best results. The key to success with AI lies not in removing people from the work to make it go faster and cost less, but to use this incredible technology to scale and transform our knowledge, vision, and experience in ways that provide exponential and immediate value.

To learn more about how Lighthouse is using AI, check out our AI for eDiscovery page.