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Artificial intelligence and decision-making in government functions: opportunities, challenges and future research

Albandari Alshahrani, Anastasia Griva, Denis Dennehy Orcid Logo, Matti Mäntymäki

Transforming Government: People, Process and Policy, Volume: 18, Issue: 4, Pages: 678 - 698

Swansea University Author: Denis Dennehy Orcid Logo

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DOI (Published version): 10.1108/tg-06-2024-0131

Abstract

Purpose – Artificial intelligence (AI) has received much attention due to its promethean-like powers to transform the management and delivery of public sector services. Due to the proliferation of research articles in this context, research to date is fragmented into research streams based on differ...

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Published in: Transforming Government: People, Process and Policy
ISSN: 1750-6166 1750-6174
Published: Emerald Publishing Limited 2024
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URI: https://cronfa.swan.ac.uk/Record/cronfa66991
first_indexed 2024-07-08T16:15:02Z
last_indexed 2025-07-08T04:51:02Z
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spelling 2025-07-07T15:30:46.5047138 v2 66991 2024-07-08 Artificial intelligence and decision-making in government functions: opportunities, challenges and future research ba782cbe94139075e5418dc9274e8304 0000-0001-9931-762X Denis Dennehy Denis Dennehy true false 2024-07-08 CBAE Purpose – Artificial intelligence (AI) has received much attention due to its promethean-like powers to transform the management and delivery of public sector services. Due to the proliferation of research articles in this context, research to date is fragmented into research streams based on different types of AI technologies or a specific government function of the public sector (e.g. health, education). The purpose of this study is to synthesize this literature, identify challenges and opportunities, and offer a research agenda that guides future inquiry. Design/methodology/approach – This paper aggregates this fragmented body of knowledge by conducting a systematic literature review of AI research in public sector organisations in the Chartered Association of Business Schools (CABS)-ranked journals between 2012 and 2023. Findings – The search strategy resulted in the retrieval of 2,870 papers, of which 61 were identified as primary papers relevant to this research. These primary papers are mapped to the ten classifications of the functions of government as classified by the Organisation for Economic Co-operation and Development (OECD), and the reported challenges and benefits aggregated. Originality/value – This study advances knowledge by providing a state-of-the-art of AI research based the OECD classifications of government functions, reporting of claimed benefits and challenges and providing a research agenda for future research. Journal Article Transforming Government: People, Process and Policy 18 4 678 698 Emerald Publishing Limited 1750-6166 1750-6174 AI; Artificial intelligence; Public sector; Decision-making 31 10 2024 2024-10-31 10.1108/tg-06-2024-0131 COLLEGE NANME Management School COLLEGE CODE CBAE Swansea University Not Required 2025-07-07T15:30:46.5047138 2024-07-08T17:11:27.3675963 Faculty of Humanities and Social Sciences School of Management - Business Management Albandari Alshahrani 1 Anastasia Griva 2 Denis Dennehy 0000-0001-9931-762X 3 Matti Mäntymäki 4 66991__31279__00ef781d657f4b39a296245982131c9c.pdf 66991.AAM.pdf 2024-09-06T15:40:17.9370867 Output 517829 application/pdf Accepted Manuscript true Author accepted manuscript document released under the terms of a Creative Commons CC-BY licence using the Swansea University Research Publications Policy true eng https://creativecommons.org/licenses/by-sa/4.0/
title Artificial intelligence and decision-making in government functions: opportunities, challenges and future research
spellingShingle Artificial intelligence and decision-making in government functions: opportunities, challenges and future research
Denis Dennehy
title_short Artificial intelligence and decision-making in government functions: opportunities, challenges and future research
title_full Artificial intelligence and decision-making in government functions: opportunities, challenges and future research
title_fullStr Artificial intelligence and decision-making in government functions: opportunities, challenges and future research
title_full_unstemmed Artificial intelligence and decision-making in government functions: opportunities, challenges and future research
title_sort Artificial intelligence and decision-making in government functions: opportunities, challenges and future research
author_id_str_mv ba782cbe94139075e5418dc9274e8304
author_id_fullname_str_mv ba782cbe94139075e5418dc9274e8304_***_Denis Dennehy
author Denis Dennehy
author2 Albandari Alshahrani
Anastasia Griva
Denis Dennehy
Matti Mäntymäki
format Journal article
container_title Transforming Government: People, Process and Policy
container_volume 18
container_issue 4
container_start_page 678
publishDate 2024
institution Swansea University
issn 1750-6166
1750-6174
doi_str_mv 10.1108/tg-06-2024-0131
publisher Emerald Publishing Limited
college_str Faculty of Humanities and Social Sciences
hierarchytype
hierarchy_top_id facultyofhumanitiesandsocialsciences
hierarchy_top_title Faculty of Humanities and Social Sciences
hierarchy_parent_id facultyofhumanitiesandsocialsciences
hierarchy_parent_title Faculty of Humanities and Social Sciences
department_str School of Management - Business Management{{{_:::_}}}Faculty of Humanities and Social Sciences{{{_:::_}}}School of Management - Business Management
document_store_str 1
active_str 0
description Purpose – Artificial intelligence (AI) has received much attention due to its promethean-like powers to transform the management and delivery of public sector services. Due to the proliferation of research articles in this context, research to date is fragmented into research streams based on different types of AI technologies or a specific government function of the public sector (e.g. health, education). The purpose of this study is to synthesize this literature, identify challenges and opportunities, and offer a research agenda that guides future inquiry. Design/methodology/approach – This paper aggregates this fragmented body of knowledge by conducting a systematic literature review of AI research in public sector organisations in the Chartered Association of Business Schools (CABS)-ranked journals between 2012 and 2023. Findings – The search strategy resulted in the retrieval of 2,870 papers, of which 61 were identified as primary papers relevant to this research. These primary papers are mapped to the ten classifications of the functions of government as classified by the Organisation for Economic Co-operation and Development (OECD), and the reported challenges and benefits aggregated. Originality/value – This study advances knowledge by providing a state-of-the-art of AI research based the OECD classifications of government functions, reporting of claimed benefits and challenges and providing a research agenda for future research.
published_date 2024-10-31T05:23:20Z
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score 11.096068

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