Name in original language
Incorporación de la Inteligencia Artificial al Sistema de expediente administrativo electrónico
Initiative overview
The obligation of public administrations to resolve administrative procedures within the legal timeframe, the right of citizens to effective judicial protection, and the increasing volume of appeals against decisions issued by the General Treasury of Social Security (TGSS) have made it necessary to consider technological alternatives to expedite the processing and resolution of appeals.
In this project, the first phase involved using AI to summarise the content of appeals received and processed through the SIMAD-SIEE (Electronic Administrative File System) application. These appeals were then classified for proper processing or redistribution to the appropriate management area. This first phase was implemented in January 2026.
In a subsequent phase, the plan is for AI to suggest resolution proposals to the case manager regarding the issues raised in the appeal document, as well as for AI to process the information on appeals collected in our computer application. This will allow the Administration to anticipate future actions aimed at reducing administrative burdens and costs, better redistributing workloads, or preparing for future increases in workload.
Results, outcomes and impacts
Since its implementation in January 2026, the initiative has enabled the automatic summarisation and classification of appeals received by the Social Security administration, supporting caseworkers in the initial review of each file. This has reduced the time needed to understand the content of appeals and has facilitated their faster and more consistent routing to the appropriate management area.
Results are measured through operational use of the system, review of generated summaries by caseworkers, and monitoring of processing workflows within the electronic administrative file system.
In the future, the initiative is expected to support greater efficiency in appeal handling, better workload distribution and improved capacity to manage cases.




























