Capacity Building for the Implementation of Artificial Intelligence in Public Organizations

Abstract

In recent years, artificial intelligence (AI) has emerged as a remarkable phenomenon, creating a massive transformation globally and becoming a necessary condition for the development and progress of both private and public organizations. The successful implementation of any project requires capacity building, which involves identifying needs, challenges, capabilities, and strengthening systems along the path to development. Accordingly, the aim of this research is to identify the necessary capacities for the implementation of AI in public organizations and to propose a comprehensive model for this. Using a qualitative method based on grounded theory, 15 academic experts and public sector managers were selected through snowball sampling and responded to the research questions through semi-structured interviews. In the data analysis, using thematic analysis and open coding, 10 overarching themes, 36 organizing themes, and 66 basic themes with varying degrees of recurrence were identified. Based on the research findings, effective and successful AI implementation in public organizations requires attention and action in several areas: resource and infrastructure provision, policy-making and planning, data management, strengthening human resources, inter-organizational interactions, governance commitment, enhancing organizational culture, socialization, supervision and evaluation, and innovation. Each of these areas includes organizing and foundational themes necessary for implementation. In conclusion, a comprehensive model for AI capacity building was presented for use by public organizations and public management.