Artificial intelligence (AI) is rapidly changing the legal profession. From contract review and e-discovery to legal research, case analysis, document drafting — the list goes on and on – AI can process enormous amounts of information far faster than a human team. This pertinent topic came to us from Wolters Kluwer in their article, “Would you bet your AI strategy on your current data? Why governance is key.”
But in the legal field, faster is only useful if the information is accurate, trustworthy and defensible. That makes data governance especially critical.
Legal work depends on sensitive, confidential and often privileged information. When AI systems interact with that data, organizations need clear policies governing where information comes from, who can access it, how it is classified, how long it is retained and whether it can be used to train or inform AI systems.
Data quality matters just as much. AI can produce impressive answers from unreliable information and sometimes confidently invent information that doesn’t exist. In legal settings, an incorrect citation, outdated regulation, misclassified document or incomplete record can have consequences far beyond an embarrassing chatbot response.
Strong data governance also creates traceability. Legal professionals need to understand not only what an AI system produced, but what information contributed to the result. Well-managed metadata, taxonomies, access controls, versioning, provenance and retention policies help create that accountability.
AI has enormous potential to make legal work more efficient and accessible, but it cannot eliminate the responsibility to manage information properly. If anything, it raises the stakes.
Melody K. Smith
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