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67 I L T A N E T . O R G T he legal industry is redefining itself under a flood of AI applications that emerge at a staggering speed. During a panel discussion at ILTACON 2023 in Orlando, I talked about the role of Artificial Intelligence in legal. This blog post summarizes my personal takeaways on how to successfully implement AI within law teams globally. There is significant momentum and a perfect opportunity to redefine the legal profession for the better. AI-powered tools are not only putting pressure on pricing, as certain services are being commoditized at a high speed, but also changing the nature of the legal profession. As clients are no longer willing to pay for a lot of the low-value services, like generating a non-disclosure agreement (NDA), firms are shifting towards a model where they focus on high- value services (such as client advisory on complex contracts with extensive tailoring and negotiation requirements) and looking to charge based on added value. AI can help meet changed client expectations and attract and retain talent. By automating tedious and unrewarding tasks, these technologies give skilled legal professionals more time to focus on high-value and intellectually stimulating tasks. This enhances job satisfaction among legal talent and maximizes their contributions to the firm's success, ultimately benefiting the professionals and the firm. Lawyers often possess a competitive drive to excel in their work, and AI can assist them in achieving greater efficiency and accuracy, contributing to their success. Building Trust in Generative AI and Vendors Generative AI is different from most other tech because the legislation around it is still in its early stages and is constantly being refined. Nowadays, top legal AI vendors set specific standards, while regulators are lagging behind efficient legislation. That is why it is important, especially as a law firm, to do your homework by challenging vendors on their ethics and reliability. Here are some key principles to remember when selecting AI for your firm. • Explainability: Avoid black boxes. To date, technology has been rule-based. This means you can predict what the outcome will or should be. With Gen AI there is some unpredictability about the outcome, but, as a user, you should know how a machine learning model functions and how it generates output. Try to understand the model's source and behavior, so that the user understands why and how it got to its production. Providing this level of explainability should be the responsibility of the vendor. • Context Awareness: Context is crucial as it helps us understand and place everything in perspective. Without context, informed decision-making becomes challenging. This is why it's essential to ensure that the outcome provided by Gen AI includes a reference to the original source. For example, if a clause is suggested, it should specify the contract it originates from, the context in which it applies, and who approved or authored it. At Henchman, we also believe that generative AI should be combined with your own data, understand the context, and be built-in into your specific workflow. In other words, the Gen AI solution should be context-aware. For example, in the drafting process, we expect the tool to understand which kind of contract you're working on, in which industry, for which party and deal value, and so on. Context-aware AI will increase the quality and relevancy of the suggestions. • Multi-LLM Approach: Most Generative AI tools used in the legal space are, in fact, Large Language Models (LLMs). LLMs are artificial intelligence designed to

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