The Governance of AI-based Information Technologies within Corporate Environments

Abstract

Artificial Intelligence (AI) is making significant progress in recent times and is gaining a strong foothold in business. Currently, there is no generally accepted scholarly framework for the governance of AI-based information technologies within corporate environments. Boards of directors who have the responsibility of overseeing corporate operations need to know how best to govern AI technologies within their companies. In response, this dissertation aims to understand the key elements that can assist boards in the governance of AI-based information technologies. Further, it attempts to understand how AI governance elements dynamically interact within a holistic system. As AI governance is a novel phenomenon, an exploratory investigation was conducted via a qualitative approach. Specifically, the study adopted a grounded theory methodology, within the constructivist paradigm, with the intent of generating theory instead of validating existing theory. Data collection included in-depth interviews with key experts in AI research, development, management, and governance processes in corporate and academic settings. Data were further supplemented with data received from conference presentations given by AI experts. Findings from this dissertation elicited a theoretical model of AI governance that shows various AI governance areas and constituting elements, their dynamic interaction, as well as the impact of these elements in enhancing the organizational performance of AI-based projects and reducing the risks associated with those projects. This dissertation provides a scholarly contribution by comparing governance elements within the IT governance domain and the new AI governance domain. In addition to theoretical contributions, this study provides practical contributions for the benefit of the boards of directors. These include a holistic AI governance framework that pictorially represents twenty-two AI governance elements that boards can use to build their own custom AI governance frameworks. In addition, recommendations are provided to assist boards in starting or enhancing their AI governance journeys.