A Knowledge Space for the Upskilling of Management Professionals in the Domain of Artificial Intelligence

The development of powerful, multimodal Artificial Intelligence foundation models brought back into the spotlight the massive transformative potential of AI for both our personal life and in business. Use of these new tools, methods and algorithms is no longer a privilege of the subject matter experts but rather a way of remaining relevant and competitive regardless of profession and domain of activity. In our research, we aim to answer to two important questions: Q1: What specific knowledge, skills, attitudes and other personal characteristics in the domain of Artificial Intelligence support the effective performance of business professionals in a managerial role? Q2: How can one use adaptive learning technologies in the process of upskilling managers in the domain of AI? The topic lies at the intersection of at least three domains that are brought together to the benefit of the business professionals: the knowledge domain of AI, competency-based managerial assessment, and use of AI in education. The use of Artificial Intelligence in education is a 50-year old endeavour but the more recent developments of powerful deep neural networks, semantic networks and large language models call for reviews of the domain, student, pedagogical and communication models of Intelligent Tutoring Systems (ITS). By analogy with the many ITSs developed for the domain of education, we propose the development of an ITS targeted at tutoring management professionals in the development of competencies in the field of AI. We thus introduce three different components of such an intelligent system: 1) a domain model of the Artificial Intelligence sphere of knowledge implemented in a Neo4j knowledge graph, 2) an AI competency framework for managers, and 3) a knowledge space to be used for tracing the knowledge of managers in the domain of Artificial Intelligence as they progress from the complete novice state to an expert level.