AI in Legal Technologies, Use cases and Applications

How LLM and generative AI are changing the legal field

Sangsun Moon
AI in Legal Technologies, Use cases and Applications

In 2011, an article in The New York Times, part of a series on advances in AI, explained that "armies of expensive lawyers will be replaced by cheaper software." The implication was that the legal profession was about to undergo a massive transformation, one that would go beyond being heavily impacted by AI's automation. The GPT-4 in particular made headlines when it scored in the top 10% on the US Law School Admission Test (LSAT). In this article, I'll introduce the technology, use cases, benefits, and limitations of AI for lawyers.

What is an AI lawyer?


Generative AI in Legal Market
Generative AI in Legal Market to Expand at a CAGR of 30.7%, Driven by Demand for Automation

AI lawyers refer to systems and solutions that utilize artificial intelligence technology to fulfill the role of a lawyer in the legal field. It uses AI techniques such as Natural Language Processing (NLP), Machine learning, Pattern Recognition, and Reasoning to help analyze and solve legal problems.According to MarketResearch.Biz, the generative AI in law market size was estimated to exceed approximately $675.1 million by 2032. It also projected that the compound annual growth rate (CAGR) would reach 30.7% from 2023 onwards.AI enables lawyers to do their jobs more efficiently. More and more firms are stepping into the "legal tech" arena, as they realize the importance of AI through the example of their competitors.

Why AI lawyer is important

AI Enhances Efficiencies to Unlock Hidden Benefits for Legal
AI Enhances Efficiencies to Unlock Hidden Benefits for Legal - Wipro

1. Document analysis

Process and analyze large volumes of legal documents to identify relevant information and patterns. For example, you can extract the information you need from different kinds of legal documents, such as contracts, cases, and regulations.

2. Precedent search

Search past judgments and case databases for similar cases or rulings to provide lawyers with strategic advice and decision support.

3. Electronic evidence analysis

Process and analyze electronic evidence (emails, text messages, social media posts, etc.), which is becoming increasingly important in the digital age, to identify relevant information and patterns.

4. Predictive modeling

Use data mining and statistical modeling techniques to perform predictive modeling and risk assessment of litigation outcomes or trial processes.

5. Client consultation and response

Function as AI chatbots that interact with clients to answer questions and provide advice, using Natural Language Understanding techniques and Semantic Reasoning algorithms.

AI lawyers can analyze and process huge amounts of legal material quickly. AI lawyers excel at tasks such as searching large volumes of documents, analyzing electronic evidence, and reviewing legal rules and precedents, which means they can make decisions much faster and more accurately than human lawyers. AI lawyers can also provide affordable and accessible solutions in areas where access to professional legal advice and services is limited or for economically disadvantaged individuals. For example, as discussed later in the article, Fiscalnote can use AI to analyze the content of documents such as contracts, agreements, and complaints and identify important points or risk factors. Beyond that, the AI lawyer can be used to automatically generate documents based on templates.

While humans can make mistakes, AI lawyers always deliver consistent results. no human subjectivity or emotion is involved, allowing for fair and objective judgment. It also relies on a vast amount of legal data and case law. This information and knowledge can be shared with other lawyers, which will help spread expertise and allow for largely automated research and analysis.

AI technology is used to build data-driven predictive models. These models provide predictive information about case outcomes, litigation likelihood, and the trial process. These are then used by clients and attorneys to plan the best strategy.

AI lawyer real-world use cases


Based on the legislative and statutory information analyzed by FiskalNote, a company's government policy staff can understand the impact on each state. (Source: FiscalNote)

FiscalNote is the first company in the world to apply artificial intelligence to US Congressional and government data. It operates services such as Prophecy, which analyzes "legislative information," and Sonar, which analyzes "regulatory information". We provide real-time information on legislation and regulations to government policy makers at companies.

FiscalNote has information on bills and regulations in the federal government and all 50 states, as well as the influence of every member of the U.S. Senate and House of Representatives. FiscalNote has a whopping 94% accuracy rate in predicting the passage of bills in committees and on the floor. Companies across industries, including law firm Skaden, insurer Atena, Southwest Airlines, and pharmacy giant Walgreens, use FiscalNote to reduce their political risk.

The Ministry of Foreign Affairs of the Republic of Korea and FiscalNote recently signed a business agreement to share information on legislation and regulations of major countries, establish a preemptive response system, and exchange technologies related to big data analysis. FiscalNote, which applies artificial intelligence to legislation analysis, promised to collect and analyze data from more than 70 countries and cooperate in building a system for the Ministry of Foreign Affairs' global policy making.

U.S. Legal Database (DB) Corp. - LexisNexis

LexisNexis Adds Extractive AI Deal Analysis Tool to Lexis+
LexisNexis Adds Extractive AI Deal Analysis Tool to Lexis+ | Dewey B Strategic

Lexis+AI, developed by LexisNexis, is a generative AI platform to transform the practice of law. The platform helps lawyers and legal professionals work more efficiently by providing key features such as drafting, key summarization, and interactive search.

Lexis+AI analyzes user-entered legal materials to condense key topics and content and provide customized summaries and analysis. This allows users to quickly grasp important information without having to read long documents or multiple sources. You can also change the language and tone by utilizing prompts.

Chatbot-style conversations are also possible. For example, if you want to know the nuts and bolts of a civil case that happened in a certain area, it will provide that information along with relevant case law or sources. Armed with this information, users can then add to or supplement their legal drafting.

Not only that, but it also gives users the ability to check user-uploaded contracts or documents for legal violations, such as words or clauses, at a glance. This allows users to proactively detect and correct mistakes or errors, saving time and money on professional review.

What is Optical Character Recognition (OCR)?

Corporate Legal Automation Services LegalCare

legalcare platform

legalcare is a platform that combines AI and automates the entire process of diagnosing legal issues, creating and submitting relevant documents, and managing progress. Researchers who are lawyers and AI engineers worked together to build our own legal database (DB) and learning model. Based on this, the entire process of corporate legal, from general affairs to contracts, registration, and consultation, is can be done on the platform.



Law&Good is a B2B lawyer platform for businesses that provides services such as comparing lawyer quotes, legal lectures for businesses, and online consultations with advisory lawyers. In particular, Law&Good provides legal counseling and question answering through an interactive interface with users. When a user enters a question in natural language, the AI lawyer understands it and provides an appropriate answer, enabling users to receive quick and accurate legal advice.Law&Good combines AI technology and legal expertise to provide services that contribute to improving lawyers' work efficiency and client service. As an AI lawyer, Law&Good helps lawyers reduce the amount of work and time they need to do their jobs and provide fast and accurate legal assistance to their clients.

Technology applied to AI lawyers

    • Natural Language Processing (NLP)
      AI lawyers leverage natural language processing to interact with clients through conversational interfaces, analyze legal documents and case law, and answer legal questions.
    • Text Mining and Information Retrieval Technology
      AI lawyers can help with the high volume of legal Search and analyze documents. You can use this technology to extract and summarize relevant case law, precedents, regulations, and expertise.
    • Predictive Modeling
      AI lawyers use data mining and statistical modeling to predict the outcome of a case or the perform predictions. Predictive models based on historical sentencing data and case characteristics help clients and attorneys develop the best strategy.
    • Sentiment analysis
      AI attorneys use Sentiment analysis algorithm can be used.
    • Data visualization and decision support
      AI lawyers access legal rules and case law databases to provide specialized advice and decision support to clients. These systems are implemented in the form of validated legal knowledge graphs or recommendation systems.
    • Deep Learning and Cryptography
      Security and privacy of the large amounts of legal data and client information that AI lawyers deal with is critical. Help ensure data security and the safety of personally identifiable information.

    Limitations of AI lawyers and how to overcome them

    Limitations of data-dependent legal AI

    Generative AI systems generate sentences or provide answers based on training data. Recently, however, hallucinations in Generative AI have emerged as a problem. Hallucinations are when an AI generates information that doesn't actually exist or isn't true, especially when it comes to specific facts like numbers, statistics, people, or place names.

    AI lawyers use natural language processing and machine learning techniques to analyze and solve legal problems. However, unlike humans, AI cannot fully understand the meaning and context of the real world. As a result, it may lack judgment on complex legal issues or specific situations. In addition, AI systems are sometimes difficult to guarantee accuracy. Errors, bias, privacy, and other issues can arise, and a thorough algorithm needs improvement and user education.

    The performance of an AI lawyer relies primarily on training data. In the legal field, past precedents and various legal resources are important. However, the collection and analysis of this data requires a lot of time and effort. Therefore, for now2, it can be difficult for AI lawyers to obtain sufficient source data. In addition, in the legal field, Human judgment and the ability to develop strategies are important. While AI lawyers make decisions based on data and algorithms, they still need the expertise and experience of human lawyers to make judgments about complex cases or ethical issues.

    Conclusion: Lawyer AI and legal generative AI continue to make progress, but there is still work to be done to overcome the limitations of lack of data and error in generative AI.

    AI lawyers work based on a variety of data. For example, they can provide legal information to clients based on a variety of legal data and knowledge. For example, they can provide summaries and interpretations of specific statutes, regulations, case law, and more, or offer specialized advice on specific topics. In addition, AI lawyers utilize natural language processing (NLP) and semantic reasoning algorithms to interact with clients to answer questions and provide advice. They can help with everything from routine legal questions to counseling on complex cases.

    For an AI lawyer to work, it needs to be trained with this variety of data. Training datasets containing the knowledge and experience of human lawyers can also be utilized in the initial training phase, and then continue to evolve with additional real-world experience.

    The regtech trend has led to more attempts to use generative AI in the legal profession, but there are still concerns that it has clear limitations due to issues of accuracy and trust. In response, we've developed a Data-centric research will need to continue.


    1. A.I. Is Coming for Lawyers, Again - The New York Times
    2. Artificial Intelligence (AI) in the Law Industry: Key Trends, Examples, & Usages
    3. Legal materials summarized and drafted with a 'bang'...regtech-generated AI craze
    4. 'AI lawyers' are here... Finding case law and pretending to interpret contracts
    5. IBM’s Watson – A LegalTech Pioneer – Legal-AI
    6. How Artificial Intelligence Is Impacting the Legal Industry
    7. "Lawyer, use 'Legal AI' as a work assistant~"
    8. FiscalNote Resources & Best Practices
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