DEVELOPING A COMPREHENSIVE AI-POWERED DIGITAL TRANSFORMATION FRAMEWORK

Abstract

Digital transformation, powered by artificial intelligence (AI), is transforming, and reshaping organizational strategies and operational efficiencies. While much of the research has focused on the technical aspects of AI and digital transformation, there is a critical need to address the management dimensions. This dissertation aims to fill this gap by developing an AI-powered digital transformation framework that not only encompasses technological advancements but also strategic, organizational, and cultural shifts essential for success. The framework proposed in this study is structured around key pillars: People, Process, Infrastructure and Technology, Data, and Innovation. Each pillar is carefully designed to guide organizations through the complexities of digital transformation with a focus on AI integration. The methodology employed in this dissertation begins with an extensive literature review and an experience-driven approach. A two-phase survey was conducted to identify and validate the framework's pillars and sub-elements. A rigorous statistical analysis was applied to identify patterns and correlations. The framework, refined through survey results, was further endorsed, and validated through the Delphi Technique involving experts with extensive experience in digital transformation and AI technology. The proposed framework addresses various facets of AI-powered digital transformation, including challenges, solutions, ethics, governance, technology implementation, data strategy, integration, scalability, organizational culture, change management, skills, and future trends. By providing a holistic guide, this framework aims to assist organizations in implementing their digital transformation journey effectively. While this research contributes significantly to the understanding of AI-powered digital transformation, it acknowledges certain limitations. The rapidly evolving nature of technology and reliance on expert insights may impact the framework's applicability and generalizability. Nonetheless, this study provides valuable insights into the managerial aspects of AI-powered digital transformation and lays the groundwork for future research in this field.