P2P

66 You cannot answer basic regu- latory questions about your AI deployment. State bar associa- tions and regulatory bodies are beginning to ask firms pointed questions: • What content do your AI tools have access to? • How do you ensure that AI- generated work product is reviewed before it reaches a client? • What safeguards prevent AI from accessing content outside the scope of a given matter? These are not hypothetical ques- tions. They are appearing in ethics opinions, in proposed rules, and in client outside counsel guidelines. The firms that cannot produce a content inventory -- that cannot say with specificity what their AI tools can and cannot access -- are the firms that will struggle most as these inquiries intensify. Your AI costs are climbing without a corresponding return. Generative AI tools that process content at volume charge based on that volume -- tokens processed, queries executed, storage indexed. Firms that never implemented retention policies, or that never decommissioned ROT (redundant, outdated, and trivial) content, are now paying AI vendors to index and process terabytes of data that has zero business value. They are paying a premium for an AI to get worse answers from content that should not have existed in the first place. THE DIAGNOSIS NO ONE WANTS TO HEAR These are not AI problems. They are information governance problems that AI made visible. Every one of these symptoms traces back to the same root cause: Firms deployed powerful AI tools on top of ungoverned content. They treated AI as an application layer problem -- something to configure, deploy, and manage -- when it is fundamentally a content layer problem. The quality of AI output is bounded by the quality of the content it can access. The se- curity of AI usage is bounded by the governance of the content it can reach. The cost efficiency of AI processing is bounded by the discipline of what content you allow to persist. The legal industry skipped a step. In the urgency to capture the competitive advantages of generative AI, firms bypassed the foundational work of under- standing what content they have, where it lives, who should access it, how long it should be retained, and what business value it serves. That foundation- al work has a name. It is called information governance. And the firms that did not do it before deploying AI are now paying the cost of that omission in declining output quality, escalating risk, and runaway expenses. This is not a novel observation. Information governance profes- sionals have been making this argument for years. What is new is that AI has compressed the timeline. The consequences of ungoverned content that might have taken a decade to materialize in a pre-AI environment are mate- rializing in 18 months in a post-AI one. The reckoning is not coming. For many firms, it is already here. WHY THE INSTINCT TO "FIX THE AI" WILL FAIL The natural response for a CIO fac- ing these symptoms is to address them at the AI layer. Tighten the AI access controls. Tune the AI prompts. Add a review workflow on top of AI outputs. Implement an AI-specific governance policy. These are not wrong moves. But they are insufficient ones, and in some cases, they are counterpro- ductive because they create a false sense of resolution. Tightening AI access controls That foundational work has a name. It is called information governance. And the firms that did not do it before deploying AI are now paying the cost of that omission in declining output quality, escalating risk, and runaway expenses.

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