Analyzing AI Readiness through Digital Transformation and Data Management: A Case Study of Qatar's Government Sector

Abstract

This paper investigates the Artificial Intelligence (AI) readiness of government institutes, focusing on the criteria of the two critical areas of Digital Transformation and Data Management. We conduct interviews with 21 Information Technology directors (CIO) across various national government institutes and develop a comprehensive decision support index for assessing the readiness of government entities for AI adoption in their operations. The maturity of digital transformation includes strategy and vision, innovation, and service development. Data management practices such as data governance, data quality, data Privacy and Ethics. We calculate individual and aggregate TRL scores to estimate the overall AI readiness score for the case of government sectors in Qatar. The research contributes to the literature on AI readiness in public sector organizations by applying a combination of the Simple Additive Weighting (SAW) method and the Technology Readiness Level (TRL) framework to evaluate readiness across multiple dimensions. The primary objective of this study is to deepen the understanding of an organization's progression towards AI adoption. The findings offer insights for policymakers and organizational leaders in similar contexts, providing a framework and a roadmap for improving AI readiness. The study underscores the importance of a comprehensive approach to AI adoption, considering technological capabilities and strategic alignment, resource allocation, and skill development. The paper shows a framework for a purposeful decision in the AI adoption process for government organizations by identifying key readiness factors and their impact on AI adoption.