Building a Legal Function That Can Scale

## Summary Nikki Rahimzadeh joined Analog Devices as the legal department was working through a "big T" transformation, triggered by an acquisition that doubled the company's size overnight. She walks Stephanie through what she found (a lot of vision, not much infrastructure) and what she built since: new people, new processes, and a technology stack rebuilt around project management rigor and clean data. The two dig into how Legal Ops professionals without a budget-holding champion can still make the case for investment, and why "fail fast" has become a legitimate strategy for building leadership buy-in. From there, the conversation turns to AI. Nikki argues that no legal team can use AI well without first doing the unglamorous work of data governance, since most legal departments have no idea how much data they actually generate. She also describes how ADI went from a department that had never led on tech to the most active enterprise-AI-tool users in the company, and how proactive communication (use AI, but bring the judgment call to legal) is helping the department stay the trusted advisor even as self-service AI use grows. ## Key Takeaways - A "big T" transformation needs a vision and a budget, but you can build the case without either. Nikki recommends showing incremental, imperfect proof of what's possible before asking for the big investment. - Fail fast is now a legitimate Legal Ops strategy. Build something that's a quarter good, use it to show leadership the art of the possible, and leave breadcrumbs toward the bigger ask. - AI adoption starts with data governance, not tools. You can't connect anything until you know what data exists, where it lives, and how reliable it is, and legal teams routinely underestimate how much data they generate. - Legal Ops has an opening to own AI strategy for the whole enterprise, not just adopt whatever the business hands down, a flip from Legal's historical position as the last department to get new tech. - Scalability today is a ways-of-working question, not a headcount question. When someone leaves, the first question is whether the work can be redeployed through better tools before backfilling the role. ## Links and Resources - Operating Readiness Engagement led by UpLevel Ops: UpLevelOps.com/ULO\ADI\OperatingReadiness - General Legal: generallegal.com - UpLevel Ops: uplevelops.com - Ken Callander's Above the Law article series, "Why You Should Choose Legal Ops Tools You Can Build On" (Parts 1 and 2) ## Keywords Legal Ops scalability, legal ops transformation, Analog Devices legal, in-house AI adoption, data governance legal, legal ops strategy, AI strategy legal department, legal ops budget, fail fast legal ops, legal ops org design, headcount redeployment, responsible AI legal, legal ops leadership, ACC Value Champion, legal department scale, enterprise AI adoption, legal ops resource model, in-house legal innovation, legal ops case for resources, AI guardrails legal ## Episode Highlights - \[00:00:47 - 00:01:27] Nikki describes ADI's "big T" transformation following a major acquisition - \[00:05:40 - 00:06:23] Stephanie names the real problem: making the case for resources without a budget-holding vision - \[00:07:04 - 00:08:41] Nikki's blueprint for buy-in: fail fast, use what you have, leave breadcrumbs - \[00:09:20 - 00:10:31] Stephanie's Copilot vs. ChatGPT story: failing fast to justify a non-standard tool - \[00:11:25 - 00:12:25] Why readiness work still can't be skipped, even as implementation speeds up - \[00:12:31 - 00:14:26] Data governance as a blind spot: legal teams don't realize how much data they generate - \[00:16:01 - 00:17:20] Legal Ops as the strategic bridge between legal and enterprise data and AI initiatives - \[00:20:25 - 00:20:48] ADI's CLO tells the organization: use AI, but bring judgment calls to legal - \[00:23:56 - 00:24:38] Redefining scalability: it's about ways of working, not headcount - \[00:29:36 - 00:31:39] Advice for resource-constrained Legal Ops leaders: get creative, use IT pilots and vendors