Do you remember when lawyers had to rely on mountains of paper and endless hours of research? No? That's probably because Generative AI (GenAI) appeared like a legal superhero, swooping in to save the day (and perhaps a few trees). This article delves into the top 8 uses of GenAI in the legal sector, demonstrating that while lawyers still can't fly, they can now navigate the skies of legal challenges more easily and efficiently.
But first, let's start with the basics.
Understanding Generative AI
Firstly, it's crucial to comprehend the nature of GenAI and its underlying Large Language Models (LLMs). Unlike conventional machine learning models designed for specific tasks, LLMs ingest vast data, forming a 'worldview' to generate new content. The challenge is ensuring these models have an accurate worldview. This is achieved through 'grounding,' ensuring that generative AI's outputs are based on high-quality content, such as a law firm's precedent database or document management systems. This grounding is essential to harness generative AI effectively in the legal sector.
Now, let's explore 8 GenAI use cases that can revolutionise the legal sector.
#1 Transforming client service with Generative Agents
Generative Agents can provide clear, human-like responses and tailored lawyer and service recommendations. Consider a law firm using a Generative Agent to respond to client inquiries quickly. The agent reviews contracts, offers amendments, and assists in drafting legal documents. Clients get prompt, accurate advice, enhancing satisfaction and retention.
Imagine a client needing urgent contract help. They consult the AI agent, which efficiently revises the document and offers guidance, expediting the process and ensuring consistent legal support. This application of Generative AI significantly enhances client service in the legal sector.
In fact, according to Accenture, 54% of executives plan to invest in Generative AI to improve customer service, and 44% plan to invest in marketing.
#2 Facilitating access to knowledge
Generative AI can significantly enhance access to knowledge. Imagine a knowledge management system with a ChatGPT-like interface where users query and the AI retrieves the best documents from its repository or external legal sources. This would streamline tasks like identifying employment laws in specific jurisdictions. Grounding is vital here, ensuring that the AI's responses are based on reliable, high-quality sources, enhancing user confidence in its outputs.
#3 Revolutionising eDiscovery
In eDiscovery, GenAI could represent a significant advancement. While traditional machine learning models classify and tag data, Generative AI could further refine this process. It could determine the relevance of automatically tagged files or generate summaries of legal documents to assist professionals in quickly grasping key points.
#4 Enhancing operational efficiency
Generative AI has potential applications in operational tasks within legal settings, such as client reporting or summarising meetings. Transforming key points or notes into comprehensive reports enables lawyers to focus on more intellectually stimulating tasks.
According to a 2023 survey by Lexis Nexis, 77% of lawyers believe that GenAI tools will boost the efficiency of lawyers, paralegals, or law clerks, and 63% also believe GenAI will transform the way law is taught and studied.
#5 Streamlining legal drafting
GenAI also shows promise in aiding legal drafting. It could use organisational standards and templates as a basis, tapping into internal expertise to draft documents like share purchase agreements for specific industries. While AI aids the drafting process, the essential legal reasoning and document structuring remain human-led tasks. This application reduces mundane aspects of drafting and ensures the inclusion of standardised, expert-approved language.
#6 Enhancing compliance and risk management
Adherence to the continuously evolving landscape of legal regulations is paramount for businesses. Generative AI plays a pivotal role in ensuring up-to-date compliance by constantly monitoring and analysing changes in legal frameworks. This proactive approach allows organisations to be immediately aware of any regulatory shifts impacting their operations, enabling them to adjust their procedures accordingly to maintain compliance.
#7 Advancing predictive analytics in law
Generative AI's proficiency in processing extensive legal datasets paves the way for the development of predictive models. By evaluating historical legal cases and trend data, these models are capable of projecting possible outcomes in legal disputes. This predictive power grants legal professionals the ability to offer more precise guidance to clients and base strategic legal decisions on robust data-driven insights.
#8 Overcoming language barriers in global law practices
For international law firms and multinational corporations, overcoming language barriers is crucial. The multilingual capabilities of Generative AI facilitate the automatic translation of legal documents, thus enhancing communication and collaboration across different languages and cultures. This functionality is instrumental in streamlining legal processes and ensuring clarity in multinational legal proceedings.
Mitigating potential challenges with Generative AI
As with any transformative technology, it is crucial to be mindful of potential issues to guarantee the secure and effective implementation of Generative AI in your firm's practices. Here are five areas to consider:
- Safeguarding Confidential Information: It's imperative to avoid entering any data covered by attorney-client privilege or containing your client's confidential, sensitive, or proprietary information into generative AI systems. Such a disclosure could lead to a breach of your duty to maintain confidentiality.
- Awareness of AI 'Hallucinations': Users should be cautious of misinformation or fabricated responses ('hallucinations') from open-web generative AI applications like ChatGPT. It's crucial to independently verify the accuracy of any information provided by large language models (LLMs).
- Balancing Trust with Verification: Given that a AI tool is trained on developer-selected data, there's a risk of receiving inaccurate responses if the data set is flawed. It is advisable to cross-check all research findings against a trustworthy legal research database to confirm their precision.
- Meeting Client Requirements: Generative AI models do not engage in reading and interpreting cases or secondary sources to respond to queries. Therefore, it's essential to complement AI-generated results with thorough personal research and analysis to address your client's requirements adequately.
- Navigating Plagiarism Risks: The sources used by an LLM are often not transparent to the end user. When drafting documents based on legal research assisted by generative AI, exercise caution to avoid unintentional plagiarism and potential legal liabilities for your firm.
Getting Started with End-to-End AI Transformation
Partner with Calls9, a leading Generative AI agency, through our AI Fast Lane programme, designed to identify where AI will give you a strategic advantage and help you rapidly build AI solutions in your organisation. As an AI specialist, we are here to facilitate the development of your AI strategy and solutions within your organisation, guiding you every step of the way:
- Audit your existing AI capabilities
- Create your Generative AI strategy
- Identify Generative AI use cases
- Build and deploy Generative AI solutions
- Testing and continuous improvement