Artificial intelligence (AI) is gaining rapid traction across various industries, bringing about a significant transformation in business operations. However, as this technology evolves, there are potential risks that organizations must mitigate. Scott Emett, an associate professor at the W. P. Carey School of Business at Arizona State University, has been instrumental in developing the GenAI Governance Framework – the first enterprise risk framework for generative AI. This framework is designed to assist organizations in responsibly navigating the complexities of adopting and managing AI.
Emett’s collaborative effort involved working with professors from Brigham Young University and the University of Duisburg-Essen, as well as experts from Boomi and the Connor Group. The framework was developed in consultation with more than 1,000 business leaders, academics, and industry contacts. With a 20-page detailed guide and a comprehensive methodology known as the GenAI Maturity Model, organizations can assess their AI readiness, identify and manage risks associated with generative AI technologies, and make informed decisions about AI adoption.
In an interview, Emett emphasized the necessity for a framework that addresses the potential risks associated with the enthusiastic adoption of generative AI by organizations. While companies are eager to harness the transformative power of AI, they must also be attentive to its risks, ensuring that it is used in ways that do not compromise stakeholders. The GenAI Governance Framework aims to provide practical steps and clear guidance to help organizations maximize the benefits of AI while mitigating potential risks.
Emett highlighted the invaluable input of over 1,000 contributors, including GenAI specialists, auditors, regulators, and executives, whose insights shaped the development of the framework. Their extensive experience and diverse backgrounds were crucial in identifying and categorizing the most important risks associated with generative AI. By incorporating their feedback, the framework was refined to be as comprehensive and practical as possible.
The GenAI Governance Framework encompasses five critical areas essential for effective AI management, including strategic alignment and control environment, data and compliance management, operational and technology management, human, ethical, and social considerations, and transparency, accountability, and continuous improvement. Each area outlines specific control considerations and a maturity model to aid companies in assessing and enhancing their AI practices.
One of the key strengths of the framework is its adaptability to organizations of all sizes, allowing them to customize it to their unique goals, risk appetite, and available resources. Whether a small startup or a large multinational, companies can tailor the framework to focus on the most relevant domains and key risks. By involving the right stakeholders and regularly reviewing and updating their approach, organizations can ensure that their AI practices are effective and sustainable.
In conclusion, the GenAI Governance Framework offers a systematic approach to AI adoption and management, enabling organizations to navigate the risks and benefits of AI with a responsible and proactive mindset. With the collaborative efforts of experts across various domains, this framework equips organizations with the necessary tools to make informed decisions and harness the potential of AI in their operations.