AI meets IA: A typology of GenAI-supported work through individual ambidexterity

Abstract

As generative artificial intelligence (GenAI) reshapes job roles and creates new challenges for workforce adaptation, managers require a clear framework to navigate this transformation. This study develops a typology of GenAI-supported work grounded in individual ambidexterity (IA), which highlights employees’ capacity to balance exploration and exploitation while navigating competing demands. A thorough review of the literature and empirical examples revealed four GenAI-enabled work types: (1) design and innovation, (2) data analysis and insight evocation, (3) customer service and engagement, and (4) content generation and optimization. These work types reflect the interplay of two critical IA tensions: (1) specialization [generalist vs. specialist] and (2) task routinization [routine vs. nonroutine], offering insights into how employees can adapt their skills and roles. Our findings provide actionable recommendations for workforce development, including designing targeted skill-building programs, implementing ethical guidelines, and fostering empowering organizational environments. We address the psychological and procedural challenges of integrating GenAI into workplaces and propose strategies to align workforce transformation with policy objectives. By bridging theoretical insights with practical recommendations, this study provides managers with a structured roadmap for cultivating an ambidextrous and resilient workforce in the era of GenAI.