AI Readiness Index in the Public Administration, Bulgaria 2026

The second national study, “Artificial Intelligence Readiness Index,” tracks changes in attitudes, knowledge, and practices regarding the use of AI in the Bulgarian public administration between 2025 and 2026. The data was collected from 5,475 employees at the central, regional, and municipal levels. In 2026, the overall Index score increased, with the administration remaining in the “capacity-building” phase. The most noticeable progress was in the practical use of AI and employees’ readiness to work with such tools. At the same time, the institutional environment is evolving more slowly. Limited access to approved tools, the lack of clear internal rules, and poor knowledge sharing continue to be major obstacles. The results show that the sustainable implementation of AI in public administration requires not only more skills and training, but also clear responsibilities, secure access, and mechanisms for institutional learning. The raw data from the study are available in the open research repository Zenodo, DOI: 10.5281/zenodo.22026174.

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Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-10-08
DOI
https://doi.org/10.5281/zenodo.23229249
Primary Topic
E-Government and Public Services
Type
article
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article

AI Readiness Index in the Public Administration, Bulgaria 2026

Pavel Ivanov, Sava Stefanov, Tanya Ivanova-Chikova
Zenodo (CERN European Organization for Nuclear Research)
E-Government and Public Services
article

AI Readiness Index in the Public Administration, Bulgaria 2026

Pavel Ivanov, Sava Stefanov, Tanya Ivanova-Chikova
article en

Abstract

The second national study, “Artificial Intelligence Readiness Index,” tracks changes in attitudes, knowledge, and practices regarding the use of AI in the Bulgarian public administration between 2025 and 2026. The data was collected from 5,475 employees at the central, regional, and municipal levels. In 2026, the overall Index score increased, with the administration remaining in the “capacity-building” phase. The most noticeable progress was in the practical use of AI and employees’ readiness to work with such tools. At the same time, the institutional environment is evolving more slowly. Limited access to approved tools, the lack of clear internal rules, and poor knowledge sharing continue to be major obstacles. The results show that the sustainable implementation of AI in public administration requires not only more skills and training, but also clear responsibilities, secure access, and mechanisms for institutional learning. The raw data from the study are available in the open research repository Zenodo, DOI: 10.5281/zenodo.22026174.

Zenodo (CERN European Organization for Nuclear Research)
Institute of Mathematics and Informatics (BG)
Openalex Percentile: Top 3%
E-Government and Public Services
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