A carregar...
Publicação
Agentic AI in Central Public Administration: Exploring Opportunities and Challenges for Workflow Integration and Task Automation
| Nome: | Descrição: | Tamanho: | Formato: | |
|---|---|---|---|---|
| 2.74 MB | Adobe PDF |
Autores
Orientador(es)
Resumo(s)
This thesis examines the application of Agentic AI in Central Public Administration and proposes practical guidelines for its adoption. The study is motivated by persistent inefficiencies in public administration, including fragmented workflows, coordination challenges, and repetitive administrative tasks. While AI adoption has increased, most implementations remain limited to assistive or predictive systems, with limited exploration of autonomous, agent-based approaches. To address this gap, a Design Science Research methodology was applied. A literature review was conducted to assess the current state of Agentic AI in public administration, identifying key challenges, technologies, and use cases. Based on these findings, a set of guidelines was developed to identify suitable processes for Agentic AI application, along with a structured implementation framework covering use case selection, readiness assessment, implementation, deployment, and evaluation. The framework was illustrated through a simplified use case and evaluated through semi-structured interviews with three experts. The results indicate that the proposed approach is useful and applicable, particularly due to its structured and gradual implementation. Some improvements were identified, namely in process selection and monitoring. Overall, this research contributes a practical framework to support the integration of Agentic AI into public administration workflows.
Descrição
Dissertation presented as the partial requirement for obtaining a Master's degree in Data Science and Advanced Analytics, specialization in Data Science
Palavras-chave
Agentic AI Digital Transformation Process Redesign Public Sector Innovation