AI Governance Deficiency: A Barrier to Industry 4.0 Readiness

I am a doctoral candidate of the Swiss School of Business and Management (SSBM) and learning consultant researching the integration of Artificial Intelligence (AI) in teaching and learning. My work — documented in my concept note (Tse, 2024) and dissertation proposal (Tse, 2025) — focuses on Ontario’s community colleges’ readiness for the Fourth Industrial Revolution (Industry 4.0). My research reveals significant ethical and social challenges that directly impact both teaching practices and learning outcomes. This assignment is divided into two parts: · Part 1 outlines the ethical and social challenges stemming from AI governance deficiencies in education. · Part 2 introduces a comprehensive, AI-specific governance framework to measure and address these challenges, aiming to provide structured guidance for AI adoption in education. AI governance and leadership in educational institutions directly correlates with workforce readiness in Ontario communities. This study also introduces ConnectivAI, an extension of Connectivism (Siemens, 2005; Downes, 2010), to conceptualize AI's role in organizational learning, workforce training, and talent development. ConnectivAI expands Connectivism’s principles by leveraging generative and analytical AI to shape knowledge networks, enhance adaptability, and foster real-time human-AI interaction in education. Note The research methodology described in this document, including the AI-Readiness Index (ARI) and the G-PLANET-X framework, is currently in the proposal stage and awaits academic supervisor approval. As such, the framework and related metrics are preliminary constructs intended to guide future data collection and analysis.