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Automatic ticket allocation
Description of the service
AGESIC works on developing use cases and implementing AI-based solutions to achieve improvements and share the methodology and lessons learned with other public agencies, generating economies of scale, efficiency, and better use of public resources.
This project considers the automatic assignment of problems, incidents, and requests reported by users to the Service Desk technical teams to reducing delays and/or errors in processing requests and incidents.
Problem that it solves
To optimize response times to incidents reported by government systems users, improve the continuity of services, and optimize value-added tasks to enhance the quality of the services provided to citizens.
Type of AI app used
Interaction support (chatbots, virtual assistants and others), Target-focused optimization, Recognition, Prediction
Main results to June 30, 2021
More than 106,000 tickets were processed, with an accuracy of 91% for classification by Group and 69% by Site.
Three main bottlenecks faced during implementation
- Pre-processing of text data.
- IT capacity for model training
- Interoperability with the ticketing system.
Lessons learned in the design or use of AI for social impact
Data quality is of utmost importance.
Country of origin
Geographic scope of operations
Uruguay
Type of executing entity
GovernmentSector/industry
Sustainable Development Goal(s) to which your AI solution contributes
16 (peace, justice, and strong institutions)
IA app developed internally or by a third party
Internally
Name of implementing entity
AGESIC - Agency for e-Government and the Information and Knowledge Society
Stakeholders involved
AGESIC
Percentage of the development team that are women
0%
Year they started using AI-based models
2019It may interest you
Este documento presenta el Informe Final de la auditoría algorítmica del sistema Laura, llevada a cabo por Eticas Research and Consulting.
This self-assessment tool is designed to allow the mitigation of ethical risks associated with the use/application of new technologies. It is available so that the ethical performance of each system can be evaluated from the beginning.
Globally, studies show that women in the labor force are paid less, hold fewer senior positions and participate less in science, technology, engineering and mathematics (STEM) fields.