Generative AI and Institutional Reform in Sudan: Foundations, Mechanisms, and Transformative Applications

Sudan's post-conflict transition presents a critical opportunity to reimagine state institutions through inclusive, resilient, and ethically grounded reform.This paper explores the potential for generative artificial intelligence (AI) specifically Generative Adversarial Networks (GANs), Variational Autoencoders (VAEs), and transformer-based models to support this complex process of institutional reconstruction.Moving beyond technocratic solutions, the study examines the theoretical foundations of these models and maps their operational mechanisms onto key domains of reform, including constitutional design, budget simulation, civic engagement, and transitional justice.It argues that generative AI, when locally adapted and ethically governed, can serve as a catalyst for reimagining governance, amplifying civic agency, and embedding pluralistic narratives into the fabric of institutional renewal.The paper concludes with ethical reflections and comparative insights from Rwanda, Colombia, and Tunisia, outlining a framework for contextually sensitive implementation.