The Role of AI in Modern Document Review

Last updated: 01 Aug, 2024By
AI in Document Review

You’ve probably observed the surging interest in artificial intelligence and its transformative potential across various sectors. Even new regulations have been introduced. But what does the future hold for AI in document review? 

In today’s legal landscape, AI is revolutionizing the document review process by automating repetitive tasks and enhancing workflow efficiency. By minimizing the time spent on manual reviews and initial content creation, legal professionals can allocate more time to in-depth analysis and client engagement. 

What Is AI Document Review? 

AI document review leverages artificial intelligence and machine learning algorithms to efficiently analyze and categorize vast quantities of electronic documents based on their relevance to legal matters. This technology is precious during the discovery phase, where electronically stored information (ESI) is examined and selected for potential use as evidence in legal proceedings. 

As AI technology continues to evolve, its applications in document review have expanded, leading more legal teams to adopt these innovative solutions. Today’s AI tools can summarize documents, search through diverse file types, and highlight pertinent documents with remarkable accuracy. Additionally, many e-discovery platforms now incorporate generative AI into their workflows, further enhancing their capabilities. 

For example, the Everlaw AI Assistant is currently being utilized by several organizations in a closed beta. This advanced tool provides features such as document review and writing assistance, helping attorneys rapidly pinpoint the most critical information in their cases. 

The Challenges of Traditional Document Review 

Legal professionals today are under immense pressure to “do more with less.” Document review projects, essential for civil litigation, data breach responses, and investigations, involve scrutinizing increasing volumes of data within tight deadlines. Traditional document review methods, which rely heavily on manual processes, face several significant challenges: 

  • Volume and Complexity of Documents:

    The sheer volume of documents that need to be reviewed can be overwhelming. Additionally, the complexity of these documents, which may include various formats and technical jargon, adds another layer of difficulty to the review process. 

  • Time Constraints and Human Error:

    Tight deadlines exacerbate the pressure on legal teams. The manual review process is not only time-consuming but also prone to human error, which can lead to oversight of critical information and potentially impact case outcomes. 

  • Cost Implications:

    The traditional approach to document review is resource-intensive, requiring significant investment in human labor and time. This leads to high costs, which can strain budgets and limit the ability to allocate resources to other critical areas. 

Types of AI Document Review 

AI document review services primarily employs two methodologies: Technology Assisted Review (TAR) and Generative AI. While TAR has been the dominant technology, generative AI is emerging as the future of document review. 

1. Technology Assisted Review (TAR) 

TAR is the most established form of document review technology available today. It offers attorneys a fast and reliable way to review documents, and its use is widely accepted by courts during the eDiscovery process. Despite its utility, TAR has certain limitations. 

For instance, TAR is optimized for text-heavy documents such as Word files and emails. However, in the digital age, with diverse data types like text messages and videos increasingly becoming part of eDiscovery, TAR falls short in handling these formats effectively. 

2. Generative AI 

Generative AI is an emerging technology that is rapidly being integrated into legal workflows to assist with document review. Utilizing machine learning algorithms, generative AI can adapt and learn, quickly surfacing the most relevant information and providing comprehensive document summaries. It has the capability to review a wide array of data types, from video calls to Slack messages, and can perform various tasks beyond document review. 

Although generative AI is still in the developmental stage and not yet as widely accepted in courts as TAR, its legitimacy and adoption are growing. As the technology advances, its integration into legal practices is expected to become more commonplace. 

Supporting Technologies 

  • Machine Learning Algorithms: These algorithms enable generative AI to learn and improve over time, enhancing the accuracy and speed of document review. 
  • Natural Language Processing (NLP): NLP allows AI to understand and interpret human language, making it possible to analyze and summarize complex legal documents. 
  • Optical Character Recognition (OCR): OCR technology enables AI to convert different types of documents, such as scanned paper documents, PDFs, or images, into editable and searchable data. 

By leveraging these advanced technologies, AI-driven document review is set to transform the legal landscape, offering enhanced efficiency, accuracy, and adaptability. 

Benefits of AI in Document Review 

1. Speed and Efficiency 

AI automates repetitive and time-consuming tasks in document review, such as data extraction (names, addresses, dates, and numbers), keyword tagging, redaction (privacy, other projects, and trade secret protections), and classification (organizing documents into distinct categories for quick access). This significantly reduces the time and effort required, leading to faster completion of document reviews and more efficient workflows. 

2. Accuracy and Consistency 

AI improves the accuracy of document reviews by identifying relevant documents that might be missed by human reviewers. Machine learning algorithms, such as those used for Predictive Coding and Active Learning, can detect patterns in data, helping reviewers find relevant documents more reliably.  

Natural Language Processing (NLP) can extract key terms and concepts, identify relationships between entities, and present documents in a more intuitive, topic-related manner. AI’s ability to reuse past coding decisions ensures consistent handling of sensitive information, reducing the risk of errors. 

3. Cost Reduction 

By automating labor-intensive tasks and increasing the speed and accuracy of document review, AI helps reduce the overall cost of the process. Firms can save on labor costs and avoid the expenses associated with human error. The ability to reuse coding decisions also cuts down on the need for repeated reviews, further lowering costs. 

Applications of AI in Legal Document Review 

1. E-Discovery:

AI streamlines the e-discovery process by quickly identifying and categorizing relevant documents from vast data sets. It can handle various data types, including emails, text messages, and multimedia files, making the e-discovery process more comprehensive and efficient. 

2. Contract Analysis:

AI assists in contract analysis by automatically extracting and summarizing key terms and clauses, identifying potential risks, and ensuring compliance with regulatory requirements. This allows legal teams to manage contracts more effectively and reduce the time spent on manual reviews. 

3. Compliance and Risk Management:

AI helps legal teams stay compliant with evolving laws and regulations by continuously monitoring and analyzing regulatory changes. It identifies potential risks and provides recommendations for mitigating them, enabling proactive risk management. AI’s ability to learn and adapt ensures that it can handle new compliance challenges as they arise. 

Additional Insights 

As AI continues to learn and improve with each use, it becomes more adept at handling complex legal tasks. This ongoing improvement mirrors the institutional knowledge that human attorneys develop, but with the added benefit of AI’s ability to process and analyze vast amounts of data rapidly. 

When evaluating AI platforms, it’s crucial to consider their capabilities. Look for tools that can reuse coding, track historical coding, refine their models over time, and do so without retaining data. These features ensure that the AI platform can provide consistent, accurate, and efficient document review, ultimately transforming the legal landscape. 

Future Trends in AI and Document Review 

The future of document management is on the cusp of a remarkable transformation powered by the capabilities of AI. By harnessing these technological advancements, organizations can unlock unprecedented levels of efficiency, security, and collaboration. As we stand at the threshold of this exciting new era, integrating AI into document management systems emerges as a choice and a necessity for those looking to lead in a rapidly evolving digital landscape.

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