The underlying problem is structural. Companies have invested heavily in generative AI infrastructure but struggle to realize returns. Many have launched internal adoption campaigns designed to push employee usage higher. These programs typically reward activity rather than outcomes—more users, more queries, more integrations—which can encourage shallow use cases and inadvertently undermine employees' ability to perform business-critical work. Gagen MacDonald's white paper and related HBR IdeaCast discussion argue that organizational change management, not technology, is central to extracting actual value from AI systems.
For in-house counsel and legal operations leaders, this matters now because enterprise AI adoption is entering a scaling phase. Companies are moving past experimentation into workforce-wide rollout, and the conversation has shifted from whether employees use AI to whether that use moves the needle on business metrics. Adoption programs built around vanity metrics risk wasting investment and creating perverse incentives precisely when firms need disciplined, outcome-focused implementation. Legal departments considering AI tools should audit their own adoption strategies against actual business impact, not activity levels.