Digital Transformation and Artificial Intelligence in Public Administration

Abstract

Digital platforms, cloud services, automation, analytics, electronic records, and artificial intelligence are becoming embedded in public administration. Yet acquisition of new technology does not by itself constitute digital transformation. This editorial argues that government digitalization is fundamentally an organizational and institutional transformation in which technical systems interact with administrative rules, data practices, professional roles, procurement, accountability, and service design. The contemporary landscape spans digital government, algorithmic decision support, generative AI, integrated administrative systems, robotic process automation, and data-intensive public services. Major constraints include legacy systems, weak interoperability, data quality, workforce skills, vendor dependence, cybersecurity, privacy, automation bias, digital exclusion, and limited evidence about realized productivity or service-quality gains. The research agenda should prioritize public-sector AI evaluation, administrative process redesign, interoperable data systems, workforce development, responsible procurement, algorithmic auditing, cybersecurity, human oversight, and longitudinal assessment of outcomes. Digital transformation should ultimately be judged by whether technology strengthens public capability and public value, not by the number of systems procured or automated.