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February 2, 2026Accounting Horizons2 citations

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

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SEScott A. EmettMEMarc EulerichJPJason Pikoos

Key Points

  • The aim is to create and validate a governance framework for managing generative AI risks in businesses.
  • Employed design science research methodology
  • Conducted surveys and structured interviews with over 1,000 practitioners
  • Engaged with 18 organizations using the framework
  • Developed a governance framework including 69 control considerations
  • Identified five governance domains for managing generative AI risks
  • Framework found valuable by organizations of various sizes

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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Cite This Study

Emett et al. (2026) studied this question.

synapsesocial.com/papers/6980fecbc1c9540dea8112bdhttps://doi.org/10.2308/horizons-2025-056
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Also Consider

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  5. 5Bright sides and governance costs of GenAI in business processes: insights from a multi-case study analysis2026