How Generative AI Is Revolutionizing Legal Tech with AWS
Legal professionals often spend a significant portion of their time sifting through and analyzing vast amounts of documentation. This process, crucial for tasks such as building arguments, preparing drafts, and comparing documents, can be incredibly time-consuming. However, the rise of generative artificial intelligence (AI) has introduced a new era of foundation models (FMs). These models, using simple prompts, can perform diverse actions, including drafting emails, extracting key terms from legal documents, summarizing lengthy briefs, and facilitating searches across multiple files. Given these capabilities, generative AI is becoming exceptionally well-suited to legal technology.
Goldman Sachs estimates that generative AI could automate up to 44% of legal tasks in the US. Furthermore, a recent special report published by Thomson Reuters indicated that awareness of generative AI is significantly higher among legal professionals, with 91% of respondents having heard of or read about these tools. However, these models alone are not a complete answer, especially considering legal and ethical concerns around data security and privacy. Security and confidentiality are paramount within the legal field, and professionals require robust practices to protect sensitive client information. While advancements in AI and natural language processing (NLP) hold great promise for the legal industry, accuracy and costs are also valid concerns. AWS AI and machine learning (ML) services aim to address these industry concerns.
This post explores how legal tech professionals can build solutions for various use cases using generative AI on AWS.
AI/ML on AWS
Amazon has long invested in AI and ML, with these technologies driving many of the experiences customers enjoy. Examples range from e-commerce recommendation engines to Alexa devices. These capabilities are built using the AWS Cloud. AWS has played a key role in making ML accessible to a wide range of users, including more than 100,000 customers across all industries and sizes. Companies such as Thomson Reuters, Booking.com, and Merck are already utilizing the power of AWS services to deliver novel generative AI solutions. AWS simplifies the process of building and scaling generative AI that’s customized to your data, use cases, and clients. It offers flexibility in choosing the optimal FMs to suit specific needs, enabling organizations to apply generative AI to different applications such as chatbots, intelligent document processing, media creation, and even product development.
When building generative AI applications, FMs are only one piece of the overall architecture that includes knowledge bases, data stores, and document repositories. Organizations need to understand how their data is integrated with various components and implement proper controls.
Security and Your Data on AWS
Robust security and confidentiality are fundamental in the legal tech domain. At AWS, security is the top priority. The AWS architecture is designed to be the most secure global cloud infrastructure for building, migrating, and managing applications and workloads. This is achieved with over 300 cloud security tools and trusted by millions of customers including those in the government, healthcare, and financial sectors, which have stringent security needs. AWS follows a shared responsibility model for security. Core security disciplines like identity and access management, data protection, privacy, and compliance are important for generative AI workloads as they are for any other. For example, if a generative AI application accesses a database, the data classification, protective measures, and threat monitoring must be understood and implemented. Beyond focusing on established security practices, it’s critical to recognize the unique risks and additional security considerations that generative AI workloads bring.
Sovereignty has remained a priority for AWS from the start. AWS was the only major cloud provider to allow control of your customer data’s location and movement while addressing data residency requirements. The AWS Digital Sovereignty Pledge is an ongoing commitment to offering AWS customers the most advanced set of sovereignty controls and features available in the cloud, further expanding the necessary capabilities without compromising performance, innovation, security, or the scale of the AWS Cloud.
AWS Generative AI Approach for Legal Tech
AWS solutions allow legal professionals to focus on the highest-value tasks. On AWS, generative AI solutions are accessible to legal teams of all sizes. With scalable cloud computing capacity, the ability to fine-tune models for specific legal tasks, and services tailored for sensitive client data, AWS provides the ideal environment for applying generative AI in legal tech.
The following sections highlight how AWS is collaborating with legal customers on diverse use cases, all centered around boosting the productivity of various tasks within legal firms.
Search Based on Context and Conversational Q&A
Legal professionals store information in various ways, including on-premises, in the cloud, or a hybrid approach. Consolidating documents can take hours or days, especially when information is stored in different locations. Current industry tools often limit searching within a specific domain, which may not fully allow users to quickly and efficiently locate information. To address this issue, AWS uses AI/ML and search engines to deliver a managed service. Users can ask human-like, open-ended questions to a generative AI-powered assistant to get answers based on data and specific information. The users can then prompt the assistant to find key metadata attributes, locate relevant documents, and answer legal questions and terminologies. What used to take hours can now be done in minutes, and through customer collaborations, AWS generative AI has improved productivity of resources by up to a 15% increase, compared to manual processes during its initial stages.
Legal Document Summarization
Legal tech workers can now generate first drafts with generative AI capabilities. Several use cases are being implemented in this category:
- Contract summarization for tax approvals
- Approval attachment summarization
- Case summarization
Document summarization can use existing documents and videos from a firm’s document management system, or a new document can be uploaded and questions can be asked in real time. Generative AI creates the summary instead of writing it, allowing a lawyer to conduct the final review of the produced document. This approach reduces workload to 5–10 minutes, which previously would take from 20–60 minutes.
Drafting and Reviewing Legal Documents Using Generative AI
Generative AI can significantly boost attorney productivity by automating legal document creation. Tasks such as drafting contracts, briefs, and memos can be very time-consuming for attorneys. By using generative AI, attorneys can simply describe the key aspects of a document in plain language, and instantly generate an initial draft. This new approach utilizes templates and chatbot interactions to add allowed text to its initial validation before moving it on to legal review. Another use case focuses on improving contracts by using generative AI. This can streamline the contract negotiation process for lawyers by reviewing and redlining contracts, and also help to identify any potential discrepancies or conflicting provisions.
Given a set of documents, this functionality also enables attorneys to ask open-ended questions based on documentation, along with follow-up questions, allowing for human-like conversational experiences.
Start Your AWS Generative AI Journey Today
We’re at the beginning of a new era in generative AI, and we’re just scratching the surface of the potential applications within the legal field. From text summarization to drafting legal documents or even conducting context-based searches, the AWS generative AI stack allows users to build and train independent FMs while delivering services with existing FMs and also applications that use other FMs. You can start with the following services:
- Amazon Q Business: This is a new, transformative generative AI-powered assistant tailored to your business. Amazon Q Business allows users to have conversations, solve problems, generate content, and take actions using data and expertise found in your company’s information repositories, code bases, and enterprise systems.
- Amazon Bedrock: This service is fully managed and offers a choice of high-performing FMs from leading AI companies like AI21 Labs, Anthropic, Cohere, Meta, Mistral AI, Stability AI, and Amazon through a single API. Amazon Bedrock offers a broad set of capabilities for individuals to build generative AI applications with security, privacy, and responsible AI. With Amazon Bedrock, you can experiment with top FMs for your use case, privately customize them with your data using techniques such as fine-tuning and Retrieval Augmented Generation (RAG), as well as creating agents that perform tasks using enterprise systems and data sources.
In upcoming posts, we will explore how to use AWS generative AI services to focus on the different architectural patterns that help to solve different cases.
Conclusion
Generative AI solutions are helping empower legal professionals to reduce the difficulty in finding documents and performing summarization, and also allow legal businesses to modernize and standardize their contract generation and revisions. These solutions are not intended to replace practicing law experts but to increase their productivity and use of time. We are excited about how legal professionals can build with generative AI on AWS. Explore our services and find out where generative AI can benefit your organization. Our mission is to enable developers of all skill levels, along with organizations of all sizes, to innovate using generative AI in a secure and scalable manner. This is just the beginning of what we believe will be the next wave of generative AI, powering new possibilities in the growing field of legal tech.
Victor Fiss is a Sr. Solution Architect Leader at AWS, helping customers in their cloud journey from infrastructure to generative AI solutions at scale.
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.
Pallavi Nargund is a Principal Solutions Architect at AWS, leading the generative AI efforts for East – Greenfield. She also leads the AWS for Legal Tech team.
