Boomi™, a leader in bright integration and automation, together with Connor Group, a leading professional services company, in collaboration with professors David Wood (Brigham Newborn University Marriott School), Scott Emett (WP Carey School of Business WP Carey School of Business at Arizona State University) and Mark Eulerich (University Duisberg-Essen) Mercator School of Management), announced GenAI Enterprise Governance Framework — the first-ever enterprise risk framework for generative artificial intelligence (GenAI).
Built in partnership with over 1,000 business leaders, academics and industry organizations, the Enterprise GenAI Governance Framework provides a detailed guide and comprehensive methodology for organizations of all sizes to assess their AI readiness, identify and manage enterprise risks associated with GenAI technologies, and move responsibly GenAI adoption. The framework can be easily customized to fit a company’s unique goals, needs and risk appetite, and enables those responsible for risk management and governance – such as internal audit committees, IT/CISO, legal and audit – to identify, assess, and proactively respond to high-priority exposures. It also provides a structured approach to identifying vulnerabilities and implementing controls, facilitating the unthreatening and responsible deployment of GenAI technology.
Provided as a free resource by the Connor Group, the GenAI Framework includes extensive documentation and a strong set of risk and control considerations.
To enhance the usefulness of the GenAI Governance Framework, organizations can leverage the GenAI Governance Framework Maturity Model developed by David A. Wood, PhD Professor at Brigham Newborn University; Scott A. Emett, Associate Professor, Arizona State University; and Dr. Marc Eulerich, Dean and Professor of CIA at the University of Duisburg-Essen. The maturity model, along with consulting services offered by Connor Group, allows companies to evaluate their current management practices, identify areas for improvement and strategically plan for future improvements. By assessing maturity levels across different aspects of control, companies can gain insight into their strengths and weaknesses and take targeted actions to strengthen AI management.