Document Review Crisis: Cost, Speed, and Consistency
Traditional document review has long been associated with high costs, slow turnarounds, and inconsistent results. But as legal matters grow increasingly complex, data volumes are exploding, formats are evolving, and deadlines are tightening. The rise of chats, multimedia, and multilingual content is straining even the most seasoned review teams.
Fortunately, technology is not just supporting the process; it’s transforming it. Artificial intelligence, particularly Generative AI (GenAI), is redefining how review is done. From predictive coding to privilege detection, GenAI is introducing efficiencies that weren’t possible even a few years ago. Let’s explore the current pain points of legal review and the emerging solutions that may change everything.
Why Review Is Getting Harder
As communication platforms continue to develop, the number of documents requiring review continues to rise. These large volumes often come with tight deadlines and constrained budgets. High document counts with limited timeframes demand more reviewers, which in turn increases the risk of inconsistent coding. And since consistency and accuracy are critical to defensibility, this requires extra layers of quality control, adding cost, not efficiency.
New Document Types, New Challenges
Modern review is no longer just about emails and PDFs. A new generation of document types is introducing significant complexity. Text messages and chats are often fragmented, informal, and embedded with images or media, making them difficult to search and interpret. Images, handwritten notes, and whiteboard photos present another challenge since they are typically unsearchable and hard to redact accurately. Audio and video files are lengthy, unclear, and frequently lack adequate indexing, which means reviewers must spend extra time just to determine relevance. Finally, multilingual content and cultural nuances often require repeated review cycles by specialized language reviewers to ensure accurate understanding and consistent coding.
Workflow Complications Beyond the Files Themselves
In addition to document complexity, the review process is hindered by intricate workflows. Privilege reviews require a deep understanding of roles and the ability to track complicated communication chains. Hot documents and key issues are especially hard to identify early in the review, particularly when documents are delivered in staggered batches. PII protection varies significantly across projects, increasing the need for tailored identification and redaction processes. Other redactions (such as those involving third-party confidentiality or product-specific content) often introduce new obligations mid-review, making consistent redaction a challenge. Inconsistency remediation is one of the most demanding tasks, especially when changes in review strategy or early decisions lead to discrepancies across phases or productions.
How AI Is Already Making a Difference
Generative AI and machine learning are already delivering significant efficiencies in both task execution and process refinement.
AI is being used to:
- Generate document-level summaries, allowing reviewers to quickly grasp the key issues within a set.
- Predict whether documents are Responsive or Privileged, reducing the manual effort required during first-level review.
- Detect PII and perform autonomous redactions with human quality control as a safeguard.
GenAI tools now offer fast and accurate language translation and transcription too, cutting down the time spent on multilingual review. Timeline creation is another area GenAI is saving time by identifying key people and events, linking each point to its source.
Predictive coding workflows benefit from early training and validation with human feedback to ensure reliable results at scale, and incorporating GenAI analysis can help make Predictive Coding attain better results, faster. AI can also support case strategy by helping prioritize review based on people, concepts, or timeframes. And real-time reporting dashboards visualize trends, track progress, and flag anomalies, helping ensure that reviews stay on time and within budget.
Enhancing the impact of GenAI is TCDI’s SMART Data platform, a suite of AI-powered tools designed to make document review faster, smarter, and more accurate. SMART Data combines advanced OCR, translation, summarization, and transcription capabilities to extract insights from even the most difficult file types, including images, handwriting, and foreign-language content. We built these tools to streamline the review process and help our MSMR team work more efficiently. The result is better-informed decisions, faster review timelines, and more consistent outcomes.
What Comes Next: AI We Still Need
While today’s applications of Generative AI are already improving the document review process, we’re only scratching the surface of what’s possible. To fully realize the future of intelligent, scalable, and cost-effective review, we need more. The next generation of AI tools should not only assist reviewers; it should actively learn from patterns, enforce consistency, and anticipate risks before they emerge. Here are some tasks we expect AI to help with in the very near future:
- Cross-Matter Intelligence Memory to suggest consistent coding and enforce ethical walls.
- Auto-Adaptive Review Workflows to provide dynamic batching and prioritization with built-in QC triggers.
- Self-Auditing Privilege & Confidentiality Checkers for advanced pattern recognition and pre-production auditing.
- Litigation Risk Dashboards for real-time budget, volume, and anomaly monitoring.
- Automated Production Quality Checks that validate redactions, Bates numbers, and load files.
- Living Data Maps & Custodian Intel that creates dynamic visualizations of document and custodian relationships.
Conclusion: The Future Is People + Process + AI
AI isn’t here to replace anyone; it’s here to make us better. The future of document review lies in amplifying human intelligence with thoughtfully implemented AI tools, built on strong processes and decades of expertise.
At TCDI, we believe in Process-Driven AI, and we’re leveraging our 37 years of legal and technological experience and our foundation in Lean Six Sigma principles to achieve more than ever before. Review solutions need to be faster, smarter, and more defensible to keep pace with today’s eDiscovery challenges. Thankfully, we see so many ways that GenAI will help us resolve these challenges and create a future for eDiscovery that is managed by people, fueled by AI, and built on process.
Caragh Landry
Author
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Caragh brings over 20 years of eDiscovery and Document Review experience to TCDI. In her role as Chief Legal Process Officer, she oversees workflow creation, service delivery, and development strategy for our processing, hosting, review, production and litigation management applications. Caragh’s expertise in building new platforms aligns closely with TCDI’s strategy to increase innovation and improve workflow. Her diverse operational experience and hands on approach with clients is key to continually improving the TCDI user experience. Learn more about Caragh.
Jennifer Andres
Author
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As the Military Spouse Managed Review Director, Jennifer brings over 6 years of Document Review experience to TCDI. Her understanding of document review processes and military spouse lifestyle allowed her to create and implement TCDI’s Managed Spouse Military Review program, providing for remote review possibilities for military spouse attorneys in search of remote opportunities. She oversees the successful management of projects and train teams for review, coding and tasks related to document review. Learn more about Jennifer.
