Promoting User Adoption for an AI-Enabled MLR Review Platform
Using an Align-Embed-Reinforce change management approach, Clarkston Consulting recently promoted user adoption on a clients’ new AI-enabled MLR review platform. Read a synopsis of the project below or download the full case study.
Download the AI-Enabled MLR Review Platform Case Study Here
A global consumer health company launched an AI-enabled Medical, Legal, Regulatory (MLR) promotional review platform to improve how promotional materials were reviewed, approved, and managed across its U.S. brand portfolio. The platform used natural language processing and machine learning to support claims review for consistency, accuracy, and compliance. While the technology created an opportunity to improve review speed and quality, the organization needed an AI change management approach that addressed more than system usage.
Clarkston applied an AI change methodology focused on aligning ambition, embedding AI into workflows, and reinforcing adoption through governance, measurement, and continuous improvement. This approach treated AI adoption as an operating model shift, where success depended on stakeholder trust, “human in the loop”
oversight, and new ways of working.
During the Align phase, Clarkston helped establish a shared understanding of why the AI-enabled MLR platform was being introduced, how it would support the business, and what guardrails were needed to manage risk. The team supported stakeholder alignment, leadership messaging, and responsible AI considerations so users understood that AI would support decisions, not replace medical, legal, regulatory, marketing, or claims review accountability.
During the Embed phase, Clarkston helped redesign how work would get done. The team facilitated brand-based and cross-functional working sessions to gather requirements, define future-state workflows, clarify role impacts, and develop user guides, SOPs, and process documentation. Brands were onboarded in phases based on business priority and change readiness, helping protect active promotional review work while moving teams into the new process.
During the Reinforce phase, Clarkston supported adoption through branded communications, a change champion network, newsletters, feedback forms, repeatable training, UAT support, and ongoing governance recommendations.
As a result, the organization successfully onboarded the majority of U.S. brands, increased promotional review cycle speed, and created a scalable AI adoption model for future use. The client now also has an established and repeatable AI change management framework that can extend across functions and business processes.
