Artificial Intelligence and Public Sector Auditing: Challenges and Opportunities for Supreme Audit Institutions
The application of artificial intelligence (AI) is growing exponentially in public entities, contributing to the improvement of the design and provision of services, as well as to the internal management and efficiency of public institutions. However, the potential of artificial intelligence systems...
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MDPI AG
2025-06-01
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| author | Dolores Genaro-Moya Antonio Manuel López-Hernández Mariia Godz |
| author_facet | Dolores Genaro-Moya Antonio Manuel López-Hernández Mariia Godz |
| author_sort | Dolores Genaro-Moya |
| collection | DOAJ |
| description | The application of artificial intelligence (AI) is growing exponentially in public entities, contributing to the improvement of the design and provision of services, as well as to the internal management and efficiency of public institutions. However, the potential of artificial intelligence systems for the public sector also entails a set of risks related, among other areas, to privacy, confidentiality, security, transparency or bias and discrimination. The Supreme Audit Institutions (SAIs), when auditing public services and policies, must adapt their human and technological resources to this new scenario. This paper analyses the implications of AI penetration in the public sector, as well as the challenges that these technological developments pose to SAIs to improve effectiveness and efficiency in their auditing tasks. This paper presents a conceptual and exploratory analysis, informed by documentary evidence and case illustrations. Given the dynamic evolution of AI research, the findings should be interpreted as a contribution to ongoing debates, rather than definitive conclusions. It also reviews the status of the audits of systems based on algorithms carried out by some SAIs. |
| format | Article |
| id | doaj-art-70e8624955f94f6eb799d8eb06c18ec8 |
| institution | Kabale University |
| issn | 2673-4060 |
| language | English |
| publishDate | 2025-06-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | World |
| spelling | doaj-art-70e8624955f94f6eb799d8eb06c18ec82025-08-20T03:26:56ZengMDPI AGWorld2673-40602025-06-01627810.3390/world6020078Artificial Intelligence and Public Sector Auditing: Challenges and Opportunities for Supreme Audit InstitutionsDolores Genaro-Moya0Antonio Manuel López-Hernández1Mariia Godz2Department of International and Spanish Economics, Faculty of Economics and Business Studies, University of Granada, 18071 Granada, SpainDepartment of Accounting and Finance, Faculty of Economics and Business Studies, University of Granada, 18071 Granada, SpainDepartment of Computer Science and Artificial Intelligence, School of Computer and Telecommunication Engineering, University of Granada, 18014 Granada, SpainThe application of artificial intelligence (AI) is growing exponentially in public entities, contributing to the improvement of the design and provision of services, as well as to the internal management and efficiency of public institutions. However, the potential of artificial intelligence systems for the public sector also entails a set of risks related, among other areas, to privacy, confidentiality, security, transparency or bias and discrimination. The Supreme Audit Institutions (SAIs), when auditing public services and policies, must adapt their human and technological resources to this new scenario. This paper analyses the implications of AI penetration in the public sector, as well as the challenges that these technological developments pose to SAIs to improve effectiveness and efficiency in their auditing tasks. This paper presents a conceptual and exploratory analysis, informed by documentary evidence and case illustrations. Given the dynamic evolution of AI research, the findings should be interpreted as a contribution to ongoing debates, rather than definitive conclusions. It also reviews the status of the audits of systems based on algorithms carried out by some SAIs.https://www.mdpi.com/2673-4060/6/2/78artificial intelligencemachine learningsupreme audit institutionspublic auditing |
| spellingShingle | Dolores Genaro-Moya Antonio Manuel López-Hernández Mariia Godz Artificial Intelligence and Public Sector Auditing: Challenges and Opportunities for Supreme Audit Institutions World artificial intelligence machine learning supreme audit institutions public auditing |
| title | Artificial Intelligence and Public Sector Auditing: Challenges and Opportunities for Supreme Audit Institutions |
| title_full | Artificial Intelligence and Public Sector Auditing: Challenges and Opportunities for Supreme Audit Institutions |
| title_fullStr | Artificial Intelligence and Public Sector Auditing: Challenges and Opportunities for Supreme Audit Institutions |
| title_full_unstemmed | Artificial Intelligence and Public Sector Auditing: Challenges and Opportunities for Supreme Audit Institutions |
| title_short | Artificial Intelligence and Public Sector Auditing: Challenges and Opportunities for Supreme Audit Institutions |
| title_sort | artificial intelligence and public sector auditing challenges and opportunities for supreme audit institutions |
| topic | artificial intelligence machine learning supreme audit institutions public auditing |
| url | https://www.mdpi.com/2673-4060/6/2/78 |
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