A Taylorian Approach for Managing Generative AI: Lessons from One Year of Collaborative Multi-Industry Workshops

Abstract

Abstract OVERVIEW: This article explores how “Taylorism,” the historical management approach created by Frederik Winslow Taylor, can be adapted to tackle contemporary management challenges posed by generative artificial intelligence (GenAI). Drawing on a longitudinal and collaborative study based on five multi-industry workshops conducted over one year, we developed a three-dimensional framework for managing GenAI in organizations. This framework offers a three-part action plan for practitioners: (1) establish dedicated GenAI labs to orchestrate experimentation and learning; (2) explore GenAI in a structured, capability-driven manner; and (3) redefine organizational roles and workflows to support generativity. Grounded in historical parallels with Taylor’s scientific management principles, our findings empirically extend existing GenAI management frameworks by revealing how organizations operationalize them. We discuss implications for practice and suggest avenues for future research at the intersection of GenAI, technology management, and organizational innovation. We present actionable insights for managers navigating the integration of GenAI technologies, emphasizing collective actions and cross-functional collaboration. PRACTITIONER TAKEAWAYS Build before you scale: Establish a dedicated GenAI laboratory to coordinate experimentation before scaling use cases across business units. Start with capabilities, not problems: Explore GenAI use cases by mapping the technology’s capabilities to your organizational activities. Slow down to go fast: Invest in reflective functions such as evaluation and governance roles. These may initially seem burdensome, but they are essential to preventing GenAI initiatives from becoming the next “AI winter.”