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<p>The use of Artificial Intelligence (AI), and more recently the rise of Generative AI (GenAI), is fundamentally transforming businesses. This study explores the emerging role of GenAI in business, identifying and analyzing concrete use cases from business practice. Despite recent growth, research on GenAI in business is still in its infancy and lacks comprehensive foundational studies for understanding the phenomenon. To address this gap, the study’s objective is to organize the landscape of GenAI use cases in business, enabling theory building, while also offering practical insights for managers. To achieve this objective, a scoping review was conducted, collecting 680 real-world use cases of GenAI in business from both academic and non-academic sources. This sample was analyzed using an inductive concept development approach. First, a typology was developed, providing an understanding of six main types and 21 subtypes organized along two dimensions: existing business enhancement and new business enablement. Second, a framework was derived, extending the typology by mapping the configuration of human-AI collaboration in each subtype, showing how GenAI is assisting, augmenting, or automating business activities. Overall, this study provides a comprehensive typology and application framework for the growing academic discussion and equips practitioners with guidance on navigating and deploying GenAI within organizations.</p>

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Beyond the GenAI hype: a framework for Generative AI in business

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年6月29日

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  • Julia Bauch,
  • Dominik K. Kanbach,
  • Katharina Brenk,
  • Adrian Schadl,
  • Marina Dabic

摘要

The use of Artificial Intelligence (AI), and more recently the rise of Generative AI (GenAI), is fundamentally transforming businesses. This study explores the emerging role of GenAI in business, identifying and analyzing concrete use cases from business practice. Despite recent growth, research on GenAI in business is still in its infancy and lacks comprehensive foundational studies for understanding the phenomenon. To address this gap, the study’s objective is to organize the landscape of GenAI use cases in business, enabling theory building, while also offering practical insights for managers. To achieve this objective, a scoping review was conducted, collecting 680 real-world use cases of GenAI in business from both academic and non-academic sources. This sample was analyzed using an inductive concept development approach. First, a typology was developed, providing an understanding of six main types and 21 subtypes organized along two dimensions: existing business enhancement and new business enablement. Second, a framework was derived, extending the typology by mapping the configuration of human-AI collaboration in each subtype, showing how GenAI is assisting, augmenting, or automating business activities. Overall, this study provides a comprehensive typology and application framework for the growing academic discussion and equips practitioners with guidance on navigating and deploying GenAI within organizations.