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The Development of a Generative Artificial Intelligence (AI) Governance Framework

Scott A. Emett et al.

Accounting Horizons2026https://doi.org/10.2308/horizons-2025-056article
AJG 3ABDC A
Weight
0.37

Abstract

SYNOPSIS Generative artificial intelligence (GenAI) is rapidly disrupting the business world. Although it is increasingly used, there are significant risks to this technology, and practitioners want help in managing GenAI risks. We use design science research methodology to develop and validate a GenAI governance framework designed to help companies manage the risks associated with GenAI. The framework outlines 69 control considerations across five governance domains and provides a maturity model to assess readiness for each control consideration. To develop and validate the framework, we conducted surveys, in-depth discussions, and structured interviews with more than 1,000 practitioners, including GenAI specialists, audit committee members, C-suite executives, internal and external auditors, and regulators. We also report on the experience of 18 diverse organizations that have used the framework since its release. Our evidence suggests that the GenAI governance framework is valuable to organizations of diverse sizes in helping them effectively manage GenAI risks.

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https://doi.org/https://doi.org/10.2308/horizons-2025-056

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@article{scott2026,
  title        = {{The Development of a Generative Artificial Intelligence (AI) Governance Framework}},
  author       = {Scott A. Emett et al.},
  journal      = {Accounting Horizons},
  year         = {2026},
  doi          = {https://doi.org/https://doi.org/10.2308/horizons-2025-056},
}

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The Development of a Generative Artificial Intelligence (AI) Governance Framework

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Evidence weight

0.37

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.16 × 0.4 = 0.06
M · momentum0.53 × 0.15 = 0.08
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.