Cyber-Resilient Public Infrastructure: Securing Government Systems in the Age of Cloud and AI

Governments around the globe are quickly moving strategic services to the cloud and integrating AI into systems spanning the public sector, including identity and benefits management, smart cities, and healthcare. This transformation is hypothetically efficient, large-scale, and data-driven, but it also increases attack surfaces, presents new vulnerabilities unique to AI, and makes public systems more highly coupled and interdependent. The paper presents a multi-dimensional and integrated cyber-resilience framework of GovTech platforms that (1) integrates the principles of Zero Trust architecture with AI confidence and privacy-preserving computation, (2) ingrains legal, procurement and governance reforms, and (3) operationalizes continuous threat knowledge, simulation, and employee development. The research methodologically combines standards and guidance (e.g., NIST Zero Trust and AI RMF), cross-sector case studies, comparative policy analysis (e.g., NIS2 and recent U.S. executive directives), and technical literature on adversarial machine learning and privacy technologies. The paper adds (i) a unified resilience model adapted to cloud+AI GovTech, (ii) tangible implementation roads and KPIs, and (iii) policy suggestions aimed at striking a balance between sovereignty, interoperability, and innovation.