As most of the people reading this post would attest, the past several months have been a whirlwind of activity trying to keep up with generative AI (gen AI). The pace has been brisk. As part of my role leading global knowledge management (KM) for McKinsey Legal, I have been a party to numerous meetings, discussions, webinars, demos, and brainstorming sessions related to how gen AI is being deployed (or planning to be deployed) within the legal industry. And the common theme that keeps emerging is that legal—unlike the general public—has no immediate plans to delve into the wild, untamed vastness of the broader internet when utilizing gen AI for its core competencies. Hence the critical need for legal KM.
The most commonly used gen-AI platforms (for example, ChatGPT) draw from a vast amount of data that is available to the public on the internet. This data can include a wide range of sources, such as text, images, videos, audio recordings, and more. Some gen-AI platforms have been trained on massive data sets consisting of innumerable terabytes of text data, including everything from books and articles to social media posts and online forums.
But the legal industry relies on a mere subset of this data universe. Legal professionals use curated data sets to ensure that the content on which it operates is accurate, relevant, and compliant with legal requirements. Curated data sets (containing materials such as agreements, templates, guidance articles, slide decks, trainings, etcetera) have been carefully selected, organized, and labeled by legal professionals to ensure that they are relevant for the task/subject matter at hand. Even minor errors or inaccuracies in content relied upon by legal professionals in these curated data sets can potentially have significant consequences.
Therefore, while having a KM infrastructure up and running within your organization has always been important, it is now absolutely vital in the gen-AI era. The accuracy and reliability of AI-generated content will only be as good as the data sets that are used to train the gen-AI algorithms. A fully formed KM program will be critical for ensuring that the curated data sets upon which gen-AI functionality is built are up-to-date and relevant. As part of such a KM program, legal organizations need to invest in the people, processes, and technologies that will allow them to monitor and update their data sets to ensure that they are incorporating the latest legal developments.
Within McKinsey Legal, we’ve taken that vital first step. As I described here, the Legal Playbook we’ve developed is a data set of legal knowledge “generally organized by legal subject areas, key contract provisions, and regions … [containing] information [that] has been curated and developed by each legal team within the broader department with monitored updates occurring on a [consistent] basis.” And as I said back in early 2021, the success of new technology will be largely due to “managing, coordinating, and implementing the incredible ‘stuff’ that populates a piece of legal tech through a rigorous and dedicated process led by real-life human beings [who] will ultimately make the piece of legal tech successful. Here at McKinsey Legal, we see this as the answer, not just for the Legal Playbook but for contract management, matter management, and beyond [emphasis added].”
With gen AI upon us, we’ve reached the point of “beyond.” Legal KM is more important than ever in the era of gen AI because legal professionals rely on curated data sets to train gen-AI algorithms. This requires a comprehensive approach to KM—one that incorporates both people and technology that will empower legal professionals to work more efficiently and effectively. McKinsey Legal has already taken the lead on this approach, and we fully expect others to follow when navigating this exciting new world.