Emerging & data technologies applied to public sector: An AI- copiloted systematic literature review

Authors

  • Maurício Vasconcellos Leão Lyrio Universidade Federal de Santa Catarina - UFSC https://orcid.org/0000-0003-2024-5008

    PhD in Business Administration, Universidade Federal de Santa Catarina - UFSC. Bachelor 's degree in Business Administration, Pontifícia Universidade Católica de Minas Gerais – PUC/MG. Currently undertaking postdoctoral research at the Universidade Federal de Santa Catarina, UFSC, , with a visiting scholar period at the Department of Accounting Information Systems at Rutgers University – Newark.

  • Rogério João Lunkes Universidade Federal de Santa Catarina - UFSC https://orcid.org/0000-0003-4232-5746

    Doctor and Master in Production Engineering, Universidade Federal de Santa Catarina - UFSC. Graduated in Accounting, Universidade Federal de Santa Catarina, UFSC. Post-Doctorate in Accounting, Universitat de Valencia - UV. Professor of Accounting, Universidade Federal de Santa Catarina, UFSC.

  • Miklos Vasarhelyi Rutgers Business School - RBS https://orcid.org/0000-0003-3205-476X

    KPMG distinguished Professor of Accounting Information Systems and Director of the Rutgers Accounting Research Center (RARC) & Continuous Auditing and Reporting Laboratory (CARLAB) at Rutgers University. Ph.D. in Management Information Systems from University of California, Los Angeles - UCLA. MBA in Management of Technology from Massachusetts Institute of Technology - MIT. Bachelor of Science in Economics and Electrical Engineering from the State University of Guanabara and the Catholic University of Rio de Janeiro.

DOI:

https://doi.org/10.18800/contabilidad.202502.003

Keywords:

Emerging technologies, Artificial intelligence, Public sector, Systematic literature review

Abstract

This study aimed to explore the use of emerging and data technologies (Rotolo et al., 2015) in the public sector, investigating their applications, challenges, and benefits through the analytical perspectives proposed by Criado et al. (2024). To amplify the analytical capacity, minimize data processing time and analyze relevant studies on the topic in high-impact journals, the study adopts a systematic literature review process, inspired by H. Gu's et al. (2024) co-piloted artificial intelligence (AI) in audit studies and informed by prior literature review methods (Lyrio et al., 2018; Page et al., 2021; Ruijer et al., 2023; Straub et al., 2023). Based on Criado’s et al. (2024) perspectives, the results showed that, at a macro level, AI and big data stand out in the formulation of public policies. At a meso level, use cases demonstrated the potential of these technologies to optimize processes and improve organizational efficiency. At a micro level, the studies highlighted the personalization of public services and improvements in interaction with citizens, although they also warned of risks such as digital exclusion and loss of trust in governments. The study concludes that research on the topic is still in an evolving phase and has prioritized ethical and regulatory issues to balance efficiency, innovation, and the democratic values of the public sector.

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Published

2025-11-24

How to Cite

Vasconcellos Leão Lyrio, M., João Lunkes, R., & Vasarhelyi, M. (2025). Emerging & data technologies applied to public sector: An AI- copiloted systematic literature review. Contabilidad Y Negocios, 20(40), 58–67. https://doi.org/10.18800/contabilidad.202502.003

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Section

Artículos