Navigating generative AI in legal departments is like performing a high-wire act: precision, balance, and meticulous preparation are essential — one misstep and the consequences could be severe. Legal departments increasingly adopt generative AI (GenAI) to streamline tasks such as document analysis, legal research, and drafting clear, concise contracts, policies and other legal terms. While GenAI promises increased efficiency and reduced workload, it poses unique challenges related to data protection, accountability, and compliance with legal standards.
In this article, we’ll explore how GenAI can support your legal team, how to select suitable AI models, structure tasks effectively, and mitigate risks.
Understanding GenAI in legal departments
Generative AI includes artificial intelligence systems that generate human-like text, conduct sophisticated analysis, and automate routine tasks. Examples include Microsoft’s Copilot, OpenAI’s ChatGPT, Anthropic’s Claude, and Google’s Gemini. In legal departments, this means quicker drafting of emails, summarising extensive documents, and executing accurate legal research. For instance, a compliance officer reviewing a service contract can use GenAI to swiftly generate a summary highlighting obligations under relevant data protection laws.
Choosing the right GenAI tool
Selecting the appropriate GenAI tool and the correct model within that tool significantly influences the quality and efficiency of legal outputs. Some are ideal for routine tasks like drafting internal emails or summarising documents due to their fast response times and high usage limits. But they may be less capable of complex reasoning. Others provide more substantial step-by-step reasoning for analysing legal problems and addressing intricate compliance queries. However, they may be less accessible due to lower usage limits and carry higher price tags.
Structuring tasks for using GenAI in legal departments
Effective GenAI use benefits from a structured process, such as:
- Identify the tasks, such as legal research, compliance checks, or summarising legislative provisions, and choose the right GenAI tools and models for your purposes within that tool.
- Gather necessary details, including contracts, policies, stakeholder input, and relevant context.
- Define clear limitations and confidentiality measures, using structured redaction or only using enterprise GenAI tools to maintain privacy.
- Explicitly reference relevant legislation, ensuring outputs align with those laws.
- Incorporate examples for consistency, such as previous successful responses or document templates.
Limitations and best practices of AI in legal tasks
Despite its capabilities, GenAI presents risks, including factual inaccuracies (so-called ‘hallucinations’) and confidentiality vulnerabilities. Hence, best practices include:
- Thoroughly fact-checking all AI-generated content against reliable legal sources.
- Ensuring human oversight to consistent with legal accountability (which GenAI service providers won’t generally take on for you).
- Using GenAI to draft preliminary outputs and reserve final decisions for qualified legal professionals.
Actions you can take next
Integrating GenAI can significantly enhance legal departments’ efficiency, accuracy, and responsiveness. However, the inherent risks of inaccuracies, non-compliance, and confidentiality breaches demand stringent adherence to best practices and regulatory compliance. Legal professionals must ensure vigilant oversight to realise GenAI’s full potential safely and responsibly. Your legal department can:
- Enhance compliance and efficiency by developing and adapting your GenAI workflows according to best practices. For example, the American Bar Association publishes guidance on mastering GenAI.
- Deepen your understanding of GenAI tools by accessing further guidance in our Trustworthy AI Programme.
- Contribute to the legal AI conversation by sharing your experiences, feedback, and insights into integrating AI effectively by engaging with us on social media. We’re most active on LinkedIn.
