Legal professionals often spend a significant portion of their work searching and analyzing large documents to derive insights, prepare arguments, draft documents, and compare documents. The rise of generative artificial intelligence (AI) has led to a shift in foundational models (FMs). With simple prompts, these FMs can perform a variety of tasks, such as drafting emails, extracting key terms from contracts and briefs, summarizing documents, and searching across multiple documents. As a result, these models are well-suited for legal technology. Goldman Sachs estimated that generative AI could automate 44% of legal tasks in the United States. According to a special report published by Thompson Reuters, awareness of generative AI is significantly higher among legal professionals, with 91% of respondents saying they have heard or read about these tools.
However, with legal and ethical concerns about data privacy, such models alone are not enough. Security and confidentiality are paramount in the legal field. Legaltech professionals, like any business that handles sensitive client information, require robust security and confidentiality practices. While advances in AI and natural language processing (NLP) promise to aid lawyers in their work, the legal industry also has legitimate questions about the accuracy and cost of these new technologies, and how to maintain the privacy and security of client data. AWS AI and machine learning (ML) services can help address these concerns within the industry.
In this article, we discuss how legal tech professionals can use generative AI on AWS to build solutions for a variety of use cases.
AI/ML on AWS
Amazon has been focused on AI and ML for over 25 years, and many of the features customers use on Amazon are powered by ML – e-commerce recommendation engines, Just Walk Out technology, Alexa devices, route optimization, and more. These features are built using the AWS Cloud. AWS has played a key role in making ML available to anyone who wants to, including over 100,000 customers of all sizes and industries. Thomson Reuters, Booking.com, and Merck are some of the customers using the generative AI capabilities of AWS services to deliver innovative solutions.
AWS makes it easy to build and scale generative AI that is customized for your data, use cases, and customers. AWS gives you the flexibility to choose a variety of FMs that best fit your needs. Organizations can use generative AI for a variety of purposes, including chatbots, intelligent document processing, media creation, and product development and design. The same technology can now be applied to the legal sector.
When building generative AI applications, FM is part of the architecture, not the entire solution. Other components are involved: knowledge bases, data stores, document repositories, etc. It is important to understand how your enterprise data is integrated with the various components and what controls can be put in place.
Security and Data on AWS
Robust security and confidentiality are foundational to the legal technology sector. At AWS, security is our top priority. AWS is designed to be the most secure global cloud infrastructure for building, migrate, and managing applications and workloads. This is backed by a rich set of over 300 cloud security tools and the trust of millions of customers, including government, healthcare, financial services, and other security-sensitive organizations.
Security is a shared responsibility model. Core security areas such as identity and access management, data protection, privacy and compliance, application security, and threat modeling remain critical for generative AI workloads, just as they are for any other workload. For example, if your generative AI application accesses a database, you need to know the database’s data classification, how to protect that data, how to monitor for threats, and how to manage access. However, in addition to focusing on long-standing security practices, it’s important to understand the unique risks and additional security considerations that generative AI workloads pose. For more information, see Securing Generative AI: An overview of the Generative AI Security Scope Matrix.
Sovereignty has been a priority for AWS since the beginning, when AWS was the only major cloud provider able to control the location and movement of customer data and address more stringent data retention requirements. The AWS Digital Sovereignty Pledge is our commitment to provide AWS customers with the most advanced sovereign controls and capabilities available in the cloud. We are committed to expanding our capabilities to help customers meet their digital sovereignty needs without sacrificing the performance, innovation, security, or scale of the AWS Cloud.
An AWS-Generated AI Approach to Legal Tech
AWS solutions enable legal professionals to refocus their expertise on higher-value tasks. AWS now makes generative AI solutions available to legal teams of all sizes. With virtually unlimited cloud computing capacity, the ability to fine-tune models for specific legal tasks, and services tailored to sensitive client data, AWS provides an ideal environment for applying generative AI to legal technology.
In the next section, we will share how we are working with customers across multiple legal industries on different use cases focused on improving productivity for various tasks in law firms.
Increase productivity by enabling search based on context and conversational Q&A
Legal professionals store information in a variety of ways: on-premise, in the cloud, or a combination of both. When documents are spread across different locations, it can take hours or days to consolidate documents before review. The legal industry relies on tools where search is limited to each domain and may not be flexible enough for users to find information.
To address this issue, AWS has provided a managed service that uses AI/ML and a search engine to ask a human-like, open-ended, generative AI-powered assistant to answer questions based on data and information. Users can instruct the assistant to extract key attributes that act as metadata, find relevant documents, and answer legal questions and condition inquiries. Tasks that previously took hours are now completed in minutes. Based on what we learned from our customers, AWS generative AI has been able to increase resource productivity by up to 15% compared to manual processes in the early stages.
Increase productivity with legal document summarization
Legaltech workers benefit from creating a first draft that can then be reviewed and revised by the process owner. Multiple use cases are implemented in this category.
- Contract summary for tax approval
- Approval Attachments Summary
- Case Summary
Document summaries can use existing documents and videos from your document management system, or users can upload documents and ask questions in real time. Instead of writing summaries, generative AI uses FM to create the content and allows lawyers to review the final content. This approach reduces these tedious tasks to 5-10 minutes instead of 20-60 minutes.
Increase lawyer productivity by using generative AI to draft and review legal documents
Generative AI helps lawyers increase productivity by automating the creation of legal documents. Tasks like writing contracts, summaries, and memos are time-consuming for lawyers. With generative AI, lawyers can explain key aspects of a document in easy-to-understand language and instantly generate a first draft. This new approach uses generative AI to add text that is allowed for initial validation before legal review through templates and chatbot interactions.
Another use case is using generative AI to improve contract review. Lawyers spend valuable time negotiating contracts. Generative AI can streamline this process by reviewing and redlining contracts to identify potential inconsistencies and conflicting clauses. This capability allows lawyers, given a set of documents, to ask open-ended and follow-up questions based on the documents, enabling a human-like conversational experience using enterprise data.
Start your AWS Generative AI journey today
We are at the beginning of a new and exciting foray into generative AI. We’ve only just scratched the surface of its potential applications in the legal sector, including text summarization, legal document creation, and context-based search. The AWS Generative AI stack provides you with the infrastructure to build and train your own FMs, services to build with your existing FMs, or applications that use other FMs. You can get started with the following services:
- Amazon Q Business is a new kind of generative assistant, powered by AI. It uses data and expertise from your company’s information repositories, code bases, and enterprise systems to tailor conversations, problem-solve, generate content, and take action for your business. Amazon Q Business delivers fast, relevant, and actionable information and advice to help you perform tasks more efficiently, make decisions and solve problems faster, and foster creativity and innovation.
- Amazon Bedrock is a fully managed service that offers a choice of high-performance FMs from leading AI companies such as AI21 Labs, Anthropic, Cohere, Meta, Mistral AI, Stability AI, and Amazon through a single API, along with a wide range of capabilities for building generative AI applications with security, privacy, and responsible AI. With Amazon Bedrock, you can try and evaluate the FMs that best suit your use case, customize them privately with your data using techniques such as fine-tuning and Retrieval Augmented Generation (RAG), and build agents that perform tasks using enterprise systems and data sources.
In upcoming posts, we will dive deeper into different architectural patterns that illustrate how you can use AWS AI services to solve these different use cases.
Conclusion
Generative AI solutions help legal professionals reduce the difficulty of searching and summarizing documents, and allow companies to standardize and modernize the creation and revision of contracts. These solutions are not intended to replace legal professionals, but rather to increase the productivity and time of legal professionals in the practice of law.
We are excited to enable legal professionals to build with generative AI on AWS. Explore our services and discover how generative AI can benefit your organization. Our mission is to enable developers of all skill levels and organizations of any size to innovate with generative AI in a secure and scalable way. This is just the beginning of what we believe will be the next wave of generative AI that will drive new possibilities in legal technology.
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About the Author
Victor Fiss As a Senior Solutions Architect Lead at AWS, he helps customers on their cloud journey from infrastructure to generative AI solutions at scale. In his spare time, he enjoys hiking and spending time with his family.
Vineet Kachhawaha is a Senior Solutions Architect at AWS focused 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 architect, deploy, and scale AI/ML applications to derive business value.
Pallavi Nargund Pallavi is a Principal Solutions Architect at AWS. She is the Generative AI leader at East – Greenfield and leads the AWS for Legal Tech team. She is passionate about women in technology and is a core member of Amazon’s Women in AI/ML. She speaks at internal and external conferences including AWS re:Invent, AWS Summits, and webinars. Pallavi holds a Bachelor of Engineering from the University of Pune, India. She lives in Edison, NJ with her husband, two daughters, and a Labrador puppy.
