Generative AI Transforms Legal Tech with AWS
Legal professionals manage tremendous amounts of information. Extracting essential details, constructing arguments, and drafting documents consumes significant time. The rise of generative artificial intelligence (AI) offers new solutions through foundation models (FMs). These models can perform many tasks in legal tech based on simple prompts, like drafting emails, extracting key terms from contracts, summarizing documents, and searching across multiple documents.
Goldman Sachs estimated that generative AI could automate 44% of legal tasks in the US. A report by Thomson Reuters also highlighted the growing awareness of generative AI among legal professionals, with 91% having heard of or read about generative AI tools. However, data security and privacy are important. AWS AI and ML services help address these concerns.
This post describes how legal tech professionals can build solutions for different use cases with generative AI using AWS.
AWS AI/ML: A Foundation for Innovation
AI and ML have been a core focus for Amazon for over 25 years. Many of the capabilities customers use with Amazon, such as e-commerce recommendation engines, Just Walk Out technology, Alexa devices, and route optimizations, are driven by ML built using the AWS Cloud. AWS has played an important role in making ML accessible to a wide audience, supporting over 100,000 customers across various sizes and industries.
Customers like Thomson Reuters, Booking.com, and Merck are using the generative AI capabilities of AWS services to deliver innovative solutions. AWS makes it simple to customize and scale generative AI for your data, use cases, and customers. AWS additionally offers flexibility in choosing suitable FMs. Organizations can use generative AI for purposes like chatbots, intelligent document processing, media creation, and product development and design, and now apply the same technology to the legal field.
When developing generative AI applications, FMs are only part of architecture design. Other components, such as knowledge bases, data stores, and document repositories, are also involved. It is essential to understand how your enterprise data integrates different components and the controls that can be put in place.
Security and Your Data on AWS
Robust security and confidentiality are crucial in legal tech. At AWS, security is the top priority. AWS is created to be the most secure global cloud infrastructure for building, migrating, and managing applications and workloads. This commitment is backed by over 300 cloud security tools and the trust of millions of customers, including government, healthcare, and financial services.
Security is a shared responsibility model. Key security disciplines, such as identity and access management, data protection, privacy and compliance, application security, and threat modeling, are essential for generative AI workloads and all other workloads. For example, if your generative AI applications are accessing a database, you’ll need to know the data classification of the database is and how to protect the data, how to monitor for threats, and how to manage access.
Understanding the unique risks and additional security considerations that generative AI workloads bring is critical as well. To learn more, see Securing generative AI: An introduction to the Generative AI Security Scoping Matrix.
AWS has prioritized sovereignty. AWS allows you to control the location and movement of your customer data and address stricter data residency requirements. The AWS Digital Sovereignty Pledge is our commitment to providing AWS customers with the most advanced set of sovereignty controls and features currently available in the cloud. AWS is committed to expanding capabilities to meet your digital sovereignty needs, without compromising on the performance, innovation, security, or scale of the AWS Cloud.
AWS Generative AI Approach for Legal Tech
AWS solutions enable legal professionals to refocus their expertise on higher-value tasks. Generative AI solutions are now within reach for legal teams of all sizes on AWS. AWS, which offers virtually unlimited cloud computing capacity, the ability to fine-tune models for specific legal tasks, and services tailored for confidential client data, provides the ideal environment for applying generative AI in legal tech.
The following sections share how we’re working with several legal customers on different use cases to improve the productivity of various tasks in legal firms.
Boost Productivity: Context-Based Search and Conversational Q&A
Legal professionals store information in various ways, such as on-premises, in the cloud, or through combinations. Consolidating documents scattered across different locations can take hours or days before reviewing them. The industry often relies on tools where searching is limited to each domain and might not be flexible enough to search for information.
To address this issue, AWS used AI/ML and search engines to deliver a managed service where users can ask a human-like, open-ended generative AI-powered assistant questions based on data and information. Users can prompt the assistant to extract key attributes that serve as metadata, find relevant documents, and answer legal questions and terms inquiries. Tasks that once took hours can now be completed in minutes. Based on what we have learned with our customers, AWS generative AI has been able to improve resource productivity by up to a 15% increase compared to manual processes during initial phases.
Boost Productivity: Legal Document Summarization
Legal tech workers can benefit from automatically generating first drafts. Several cases are being implemented under this category, including:
- Contract summarization for tax approval
- Approval attachment summarization
- Case summarization
The summarization of documents can use existing documents and videos from your document management system or allow users to upload a document and ask questions in real-time. Instead of writing the summary, generative AI uses FMs to create the content so that the lawyer can review the final content. This approach reduces time spent on these tasks to 5–10 minutes instead of 20–60 minutes.
Boost Attorney Productivity: Drafting and Reviewing Legal Documents
Generative AI can boost attorney productivity by automating the creation of legal documents. Tasks such as drafting contracts, briefs, and memos can take attorneys significant time. With generative AI, attorneys can describe the key aspects of a document using plain language and immediately generate an initial draft. This approach uses generative AI to use templates and chatbot interactions to add permitted text to an initial validation before legal review. Another use case is to improve reviewing contracts using generative AI. Attorneys spend valuable time negotiating contracts. Generative AI can streamline this process by reviewing and redlining contracts and identifying potential discrepancies and conflicting provisions.
Given a set of documents, this functionality allows attorneys to ask open-ended questions based on the documents along with follow-up questions, enabling human-like conversational experiences using enterprise data.
Start Your AWS Generative AI Journey
Opportunities in generative AI are only beginning. AWS offers you the infrastructure to build and train your own FMs, services to build with existing FMs, and applications that use other FMs to perform tasks like text summarization, drafting legal documents, and searching based on context. You can begin with the following services:
- Amazon Q Business: Offers a new type of generative AI-powered assistant that can be tailored to your business to have conversations, solve problems, generate content, and take actions using data and expertise to streamline tasks, speed up decision-making and problem-solving, and help spark creativity and innovation.
- Amazon Bedrock: Offers a choice of high-performing FMs from leading AI companies through a single API, along with a broad set of capabilities to build generative AI applications. With Amazon Bedrock, you can experiment with and evaluate top FMs, customize them with your data, and build agents that perform tasks using your enterprise systems and data sources.
In upcoming posts, we will dive deeper into different architectural patterns that describe how to use AWS generative AI services to solve for these different use cases.
Conclusion
Generative AI solutions are allowing legal professionals to find documents and summarize them easier, while also allowing your business to standardize and modernize contract generation and revisions. These solutions are designed to increase productivity rather than replace the legal experts. We are excited about how legal professionals can build with generative AI on AWS. Explore AWS services and discover how generative AI can benefit your organization.
Our mission is to make it possible for developers of all skill levels and organizations of all sizes to innovate using generative AI in a secure and scalable manner. This is the beginning of the next wave of generative AI, powering new possibilities in legal tech.
Resources
- Securing generative AI: An introduction to the Generative AI Security Scoping Matrix
- AWS Security Reference Architecture (AWS SRA)
- AWS Responsible AI
About the Authors
Victor Fiss is a Sr. Solution Architect Leader at AWS, helping customers in their cloud journey from infrastructure to generative AI solutions at scale. In his free time, he enjoys hiking and playing with his family.
Vineet Kachhawaha is a Sr. Solutions Architect at AWS focusing on AI/ML and generative AI. He co-leads the AWS for Legal Tech team within AWS. He is passionate about working with enterprise customers and partners to design, deploy, and scale AI/ML applications to derive business value.
Pallavi Nargund is a Principal Solutions Architect at AWS and is the generative AI lead for East – Greenfield. She leads the AWS for Legal Tech team and is passionate about women in technology and is a core member of Women in AI/ML at Amazon. Pallavi holds a Bachelor’s of Engineering from the University of Pune, India. She lives in Edison, New Jersey, with her husband, two girls, and a Labrador pup.
