Paper Type
ERF
Abstract
The rapid integration of generative artificial intelligence (GenAI) into organizational operations has elevated its governance to a critical concern for leadership. Information technology, data, and artificial intelligence governance frameworks, while foundational, do not fully address the unique challenges posed by GenAI's dynamic and pervasive nature. This ERF paper applies qualitative comparative analysis (QCA) to investigate how governance mechanisms can be combined to enable organizations to harness the benefits of GenAI while mitigating its risks. By examining governance configurations in two Fortune 500 companies deploying GenAI, we will identify enabling and constraining mechanisms contributing to effective GenAI governance. Our findings aim to advance governance research by proposing governance structures, processes, and relational mechanisms tailored to the dynamic nature of GenAI. The study also aims to offer insights for organizations seeking to refine their governance strategies to responsibly manage GenAI-driven transformations while aligning them with strategic objectives.
Paper Number
1998
Recommended Citation
Jewer, Jennifer; Levallet, Nadege; van der Meulen, Nick; and Chan, Yolande E., "The Governance of Generative AI" (2025). AMCIS 2025 Proceedings. 30.
https://aisel.aisnet.org/amcis2025/sig_osra/sig_osra/30
The Governance of Generative AI
The rapid integration of generative artificial intelligence (GenAI) into organizational operations has elevated its governance to a critical concern for leadership. Information technology, data, and artificial intelligence governance frameworks, while foundational, do not fully address the unique challenges posed by GenAI's dynamic and pervasive nature. This ERF paper applies qualitative comparative analysis (QCA) to investigate how governance mechanisms can be combined to enable organizations to harness the benefits of GenAI while mitigating its risks. By examining governance configurations in two Fortune 500 companies deploying GenAI, we will identify enabling and constraining mechanisms contributing to effective GenAI governance. Our findings aim to advance governance research by proposing governance structures, processes, and relational mechanisms tailored to the dynamic nature of GenAI. The study also aims to offer insights for organizations seeking to refine their governance strategies to responsibly manage GenAI-driven transformations while aligning them with strategic objectives.
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