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<p>This study explores the critical role of flexible management practices in fostering frugal innovation using Generative AI (GenAI) in resource-constrained environments. Drawing on qualitative data from 13 social entrepreneurs, this study employs the Gioia method and triangulation to identify the following key themes: flexible management practices, frugal innovation, the critical role of GenAI, and structural enablers and barriers. The findings reveal that flexible management practices, combined with GenAI, enable resource-efficient innovation, while structural factors serve as key moderators in this process. This study proposes a conceptual model illustrating how these elements interact to drive cost-effective innovation. These contributions extend existing theories on innovation management and digital transformation, offering practical insights for managers and policymakers aiming to leverage AI for cost-effective and scalable impacts. The study establishes a foundation for future quantitative validation across diverse sectors and geographic contexts, advancing the understanding of how emerging technologies can be leveraged for inclusive development.</p>

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Generative AI as a Catalyst: How Flexible Management Practices Drive Frugal Innovation in Resource-Constrained Environments

  • 期刊论文

  • 发表日期：

    2026年1月20日

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  • Priya Chaudhary,
  • Reetesh Singh

摘要

This study explores the critical role of flexible management practices in fostering frugal innovation using Generative AI (GenAI) in resource-constrained environments. Drawing on qualitative data from 13 social entrepreneurs, this study employs the Gioia method and triangulation to identify the following key themes: flexible management practices, frugal innovation, the critical role of GenAI, and structural enablers and barriers. The findings reveal that flexible management practices, combined with GenAI, enable resource-efficient innovation, while structural factors serve as key moderators in this process. This study proposes a conceptual model illustrating how these elements interact to drive cost-effective innovation. These contributions extend existing theories on innovation management and digital transformation, offering practical insights for managers and policymakers aiming to leverage AI for cost-effective and scalable impacts. The study establishes a foundation for future quantitative validation across diverse sectors and geographic contexts, advancing the understanding of how emerging technologies can be leveraged for inclusive development.