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Introduction

Generative AI (gen AI) has ushered in a wave of significant transformations across a range of business functions, including corporate legal functions. This innovative technology has the potential to transform legal departments and enhance efficiency across a spectrum of tasks, such as analyzing data, researching legal issues, summarizing documents, and comparing information. Legal organizations are attempting to embrace these new tools. However, they frequently fail to consider a key component needed for success: a robust data strategy.

What Is a 'Data Strategy'?

Before exploring its role in powering the effective use of gen AI tools, it is critical to understand what a "data strategy" entails in a corporate legal setting. In general, a data strategy is a comprehensive plan that outlines how an organization collects, stores, manages, shares, and uses data. It is a roadmap that aligns the organization's data initiatives with its strategic business goals. A robust data strategy addresses issues including data governance, data quality, data architecture, and data literacy, helping to ensure that enterprise data are treated as assets that can drive decision-making and innovation. Finally, a foundational component of a data strategy is a blueprint that provides tactical insights into the systems where data resides, the interconnectivity of those systems, and the data stored there, as well as the business questions/considerations that each system (and its associated data) is intended to address. In the context of a corporate legal function, this will typically influence how department resources are capturing and storing information related to legal matters, contracting, and law department knowledge.

The Role of a Defined Data Strategy in the Successful Implementation of Gen AI

Generative AI, a subset of artificial intelligence (AI), uses machine learning models to create, review, and analyze content including text, images, and even software code based on user input and the data it can access. As an example, in the context of corporate legal functions, gen AI can be leveraged or trained to support the following use cases:

  • Review contract templates to help identify deviations in third-party paper and generate responsive positions that the legal team has pre-approved.
  • Organize and manage the vast amount of knowledge within a legal department. It can help in categorizing, searching, and retrieving information quickly and efficiently.
  • Analyze historical case history to generate strategic insights, aiding in the creation of tailored legal content to enhance a company's negotiations and litigation strategy and results.
  • Streamline the process of reviewing legal invoices. It can analyze line items, compare them against agreed-upon rates and rules, identify billing errors or discrepancies, and help ensure compliance with the company's billing guidelines.

However, the quality and accuracy of the output heavily relies on the quality and depth of the underlying data available to the AI tool.