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T he legal sector has embraced a range of new legal technologies such as document automation, e-signatures, and electronic discovery over the years. Now, with the emergence of generative AI, the industry has reached its next technology adoption juncture. ChatGPT and other large language model (LLM) AI are all the rage at the moment. A new report shows 95% of UK-based legal professionals say generative AI tools will have a noticeable impact on their current practice. And a large percentage of in-house legal counsel are either expecting their firms (70%) or their clients (55%) to use AI. But what really is generative AI? How will it impact the legal sector? Generative AI using the new breed of LLMs promises to be a real game changer for the legal sector. For instance, legal professionals could quickly draft documents such as detailed contracts. Or instead of just extracting data points like courts, addresses and jurisdictions, legal professionals could turn text into actionable insights that help clients to understand and track their legal obligations. Ultimately, LLM AI can easily use data to extract meaning and context to create real intelligence. It addresses the fundamental challenge that has frustrated the legal industry for decades: turning the copious amounts of unstructured data embedded in all manner of legal documents into categorical knowledge. Understanding the pitfalls of AI The possibilities of the technology are exciting and seemingly limitless. However, when looking to use generative AI, legal organisations must avoid taking a gung- ho approach. Despite the many benefits the technology can bring, there are also many pitfalls to consider. It's important to make a clear-eyed assessment of what value they expect to gain from the adoption and weigh that against the potential downsides. Firstly, there is an ongoing challenge with AI technologies: the results are only as good as the prompt provided by the user. For example, if you provided a prompt like "draft a contract for a commercial lease in London," it might generate a passable version of the desired document. But when real experts look closely at those drafts, the content can seem amateurish and may contain subtle or obvious errors. Many of the solutions announced to date are thin application layers on top of publicly available chatbots or retail AI models. Without the ability to design prompts intelligently and incorporate crucial context, firms will struggle to produce accurate and valuable results. Unlocking data and documents The most valuable generative AI use cases arise from leveraging a firm's corpus of documents and associated data – whether to search that corpus, classify documents, analyse, and extract data from its contents, or generate new drafts based on prior precedent. To provide more accurate 29 I L T A N E T . O R G "The possibilities of the technology are exciting and seemingly limitless."

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