TY - JOUR
T1 - The human side of generative artificial intelligence in business model innovation
AU - Azabagic, Norman
AU - Gemser, Gerda
AU - Giesen, Edward
N1 - Publisher Copyright:
© The Regents of the University of California 2026. This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 License (https://creativecommons.org/licenses/by-nc/4.0/) which permits non-commercial use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access pages (https://us.sagepub.com/en-us/nam/open-access-at-sage).
PY - 2026
Y1 - 2026
N2 - 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.
AB - 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.
KW - Artificial intelligence (2078)
KW - Business model innovation (570)
KW - Innovation (342)
KW - Innovation management (513)
KW - Organizational innovation (3367)
UR - https://www.scopus.com/pages/publications/105038657045
U2 - 10.1177/00081256261445458
DO - 10.1177/00081256261445458
M3 - Article
AN - SCOPUS:105038657045
SN - 0008-1256
JO - California Management Review
JF - California Management Review
ER -