From Descriptive Analytics to Predictive and Prescriptive Analytics: Navigating the “In-Between Times” of Generative AI in a Global Solution Services Company

Abstract

Introducing generative artificial intelligence (AI) into organizational processes represents a watershed moment, demanding a fundamental rethinking of processes and culture (Benbya et al., 2020). Traditional change management processes, like ADKAR (Hiatt, 2006), offer research-based tools and strategies to assess readiness for AI adoption but are more effective when adapted and infused with sensemaking to help employees navigate an unknown future state. In this qualitative study, employees in a global solutions services company (“The Company”) revealed a strong desire and readiness to adopt AI-powered advanced analytics. This desire exceeded employees’ awareness of the change and how it would be applied. Drawing from the literature on change management and sensemaking, interviews, observations, and document analysis from The Company, we recommend adopting an AI-specific change management methodology and strategy focusing on what we call the “AI Change Catalyst Loop,” in which The Company simultaneously focuses on desire, awareness, and knowledge infused with sensemaking. Intentional sensemaking for shared use cases and articulation of the value of advanced analytics will help The Company create a flywheel of momentum to build the ability and skills needed to adopt and utilize advanced analytics successfully. For The Company, we recommend applying the methodology in three phases. Phase 1 involves establishing an internal change management office focused on data analytics to guide employees through this mindset shift, ensuring continuous learning and leadership alignment. Phase 2 recommends an internal communications strategy emphasizing sensemaking, using narratives and clear messaging to help employees understand their role in the broader organizational goal. Lastly, phase 3 links business success metrics with role-based training to foster continuous improvement and innovation. The new change management approach aims to build a culture of trust, relevancy, and a data-driven decision mindset.