Gene Quinn

As in-house patent teams rethink how work is allocated, the implications for outside counsel are unavoidable. Corporate clients are asking whether work being done by outside counsel is being performed as efficiently as possible and even starting to ask whether it needs to be performed by outside counsel at all. At least some in-house teams are wondering whether the same or better result can be achieved internally using AI-enabled tools. If the answer is yes, then clients can be expected to decrease reliance on outside counsel, looking to law firm attorneys for targeted support, not end-to-end project management.

Artificial intelligence has moved beyond the experimental phase in legal practice. The legal industry is no longer debating whether lawyers can or should use AI tools, or whether AI will affect the economics of law firm and in-house legal department operations. Those questions have been answered. AI is already reshaping how legal work is performed, how legal departments manage demand, how law firms are expected to price services, how patent teams analyze portfolios, and how clients evaluate outside counsel.

This week on IPWatchdog Unleashed, I spoke again with Fran Cruz, Senior Vice President of IP Solutions for Juristat. Our conversation was about a topic that should be top of mind for every patent prosecution firm, every in-house IP department, and every legal operations professional trying to make sense of the current market for patent related legal work. Where is patent prosecution work going, when does work move from firm to firm, when it does move, where is it moving, and what will firms have to do to win—or keep—the patent preparation and prosecution work?

Artificial intelligence (AI) is moving faster than traditional intellectual property (IP) strategy was designed to handle. The issue is not simply speed, although speed is certainly part of the problem. The deeper challenge is that AI innovation does not fit neatly into the legacy IP operating model. The assets, development cycles, regulatory environment, and commercial pathways are all different. And the value drivers are increasingly distributed across a spectrum of AI-related intangible domains, which include patents, trade secrets, data rights, software architecture, licensing models, and customer contracts.

Artificial intelligence is no longer a futuristic talking point in patent practice. It is already being deployed by patent practitioners who understand a simple truth: AI is not a substitute for legal judgment, technical understanding, claim strategy, or client counseling. When implemented properly, AI is a force multiplier. It can compress timelines, improve consistency, reduce low-value friction, provide meaningful portfolio intelligence, and allow practitioners to spend more time on the work that actually requires professional expertise.