Business Models

The Human Side of Generative Artificial Intelligence in Business Model Innovation

Norman Azabagic, Gerda Gemser, and Edward Giesen


 
Abstract
Generative artificial intelligence (GenAI) is growing in popularity, yet insights on its application to business model innovation (BMI) are scarce. Drawing on a qualitative, multiphase study involving interviews, focus groups, and digital diaries with strategy consultants, we explore how professionals engage with GenAI during BMI. Our findings suggest strategy professionals engage with GenAI through what we term reflexive augmentation, which represents the deliberate, critical engagement with GenAI to decide which tasks should and should not involve GenAI and which tasks to automate or augment through GenAI. We show how this process is shaped by four tensions related to trust, skills, value-add, and client disclosure. We offer actionable insights for managing human-AI collaboration, advancing debate on augmentation and automation at the micro-level, and suggest how organizations can support effective GenAI integration in innovation contexts.

California Management Review

Published at Berkeley Haas for more than sixty years, California Management Review seeks to share knowledge that challenges convention and shows a better way of doing business.

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