Generative AI in Legal: Use Cases

In this article I will cover Generative AI use cases in Legal industry. This is the 2nd article in the 'Generative AI in Legal' series where the first article focused on solution providers in this space.

The global legal technology market was valued at $23.45B in 2022 and is estimated to reach $45.73B by 2030 with a CAGR of 9.1% according to a report by Grand View Research, Inc. Specifically, the generative AI in legal market is expected to grow to $675M by 2032 with a CAGR of 30% according to a research study by MarketResearchBiz (link).

For these generative AI use cases in legal the target customers are typically legal technology providers, solo lawyers, small and medium law firms, large law firms, corporate general counsels and in-house lawyers, and government counsels. Target users can also extend to citizens and end-users of legal services.

• Legal research and discovery: Generative AI enables natural language interaction with case law, legislation & precedents. With techniques like Retrieval Augmented Generation (RAG) on public (legal databases, libraries, federal, state and local government records, and business databases) and private sources of data (internal systems, contract management systems) legal professionals can fast track the legal research. Legal professionals can also do international searches and comparative searches.

• Document review and summarization: Generative AI can help review and analyze precedents and other large volumes of legal documents such as contracts, legal records etc. and can reduce time to insights. Through summarization of long statutes and regulations, generative AI can further improve productivity of legal professionals.

• Drafting the brief, litigation strategy and legal arguments: Legal professionals can increase their productivity by using generative AI for drafting legal documents based on pre-defined templates, and user, proprietary and input data. This can give them a head start in drafting by giving them a starting point which is 80-90% there and can be finalized with further human edits and review. With generative AI, lawyers can receive quick/directional answers to hypothetical questions with facts and patterns. This can help them prepare for the case more effectively.

• Contract analysis and negotiation: With generative AI legal teams can review contracts, identify relevant clauses, flag potential issues and suggest changes based on prior examples and best practices more efficiently and faster. This can expedite the negotiation process and reduce the chances of disputes.

• Due diligence: Generative AI can help legal teams review large volumes of documents, identify legal risks and generate insights during corporate transactions such as mergers, acquisitions, divestitures, investments etc. The due diligence use case can be extended beyond corporate transactions to property and other high value asset transactions.

• Market intelligence, compliance and regulatory monitoring: Generative AI can help monitor regulatory changes and compliance standards and thus help ensure businesses remain compliant and can do risk assessment based on changes. Clients can thus avoid costly penalties and fines for non-compliance. Generative AI can help identify bills, regulatory changes and news impacting clients, their competitive positioning and potential events that can trigger need for legal counsel services.

• Intellectual property management: Generative AI can support law professionals in managing their client’s intellectual property portfolios through analysis of patents, search of trademarks and copyrights and by helping detect potential violations or infringements.

• Case outcome prediction: Generative AI can analyze large volumes of historical case data, legal precedents, patterns and trends to more accurately and objectively predict case outcomes without any human biases. It can also help legal professionals understand factors affecting the case outcomes that may impact the likelihood of success or failure and inform their litigation strategies. As generative AI learns from new data and outcomes, the predictions can be expected to be faster and more accurate overtime. Generative AI can also help assess the financial value of a case.

• Industry specific use cases: Generative can be used for gaining insights from corporate debt contracts and transactions (financial services, capital markets), for property due diligence (real estate and construction), and for insights, outcome and financial predictions for injury related cases (healthcare and automotive).

• Hyper-personalized marketing and thought leadership: With generative AI, law firms of all sizes can create personalized newsletters and marketing content for clients based on the data they have about the clients and can improve their customer acquisition and conversion cycles.

• Democratize legal assistance: Through legal AI assistants which can be in the form of virtual assistants or even digital avatars, customers can receive basic legal guidance, get answers to their legal questions or can be guided to relevant resources and services. This can be a great use case for governments, corporate legal counsels (for internal employees) and law firms.

As customers adopt generative AI, they need to ensure they are doing so while following the best practices on privacy, security, accuracy and IP concerns. While generative AI offers benefits such as higher efficiency, improved accuracy, more standardization and lower costs, legal professionals should also be aware of limitations and risks such as privacy and security, hallucinations and lack of transparency.