Adaptive it Investment for Smarter Governance: A Framework for Ai-Based Decision Support Systems in Public Sector

Objective: This research aims to explore the development of an adaptive Information Technology (IT) investment framework for artificial intelligence-based decision support systems (AI-DSS) in government, with a focus on improving strategic decision-making, transparency, and inclusive public services in the Indonesian public sector. Research Design & Methods: The research used a systematic literature review approach that refers to the PRISMA protocol. It analyzed 14 Scopus-indexed articles published between 2015 and 2024. Bibliometric analysis was conducted with the help of VOSviewer software to identify keyword trends and research clusters relevant to AI, decision making, and governance. Findings: AI-DSS contributes to strengthening decision-making in the public sector through real-time data processing, predictive analytics, and more agile responses to policy dynamics. However, challenges remain, such as the digital divide, regulatory limitations, a lack of technical competencies, and integration difficulties with legacy systems. Implications & Recommendations: The government is advised to implement a phased investment strategy supported by agile governance principles, strengthen the legal framework, and integrate inclusive technologies such as Big Data and Blockchain. Contribution & Value Added: This research provides a conceptual and practical framework for adaptive IT investment in AI-DSS, bridging technology and governance.

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Publication Details

Journal
Breakthroughs Information Technology
Published
2025-06-30
DOI
https://doi.org/10.70764/gdpu-bit.2025.1(1)-05
Primary Topic
Big Data and Business Intelligence
Type
article
Field-Weighted Citation Impact
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article

Adaptive it Investment for Smarter Governance: A Framework for Ai-Based Decision Support Systems in Public Sector

Azanizawati Ma’aram, Shafiqul Islam
Breakthroughs Information Technology
Big Data and Business Intelligence
article

Adaptive it Investment for Smarter Governance: A Framework for Ai-Based Decision Support Systems in Public Sector

Azanizawati Ma’aram, Shafiqul Islam
article en

Abstract

Objective: This research aims to explore the development of an adaptive Information Technology (IT) investment framework for artificial intelligence-based decision support systems (AI-DSS) in government, with a focus on improving strategic decision-making, transparency, and inclusive public services in the Indonesian public sector. Research Design & Methods: The research used a systematic literature review approach that refers to the PRISMA protocol. It analyzed 14 Scopus-indexed articles published between 2015 and 2024. Bibliometric analysis was conducted with the help of VOSviewer software to identify keyword trends and research clusters relevant to AI, decision making, and governance. Findings: AI-DSS contributes to strengthening decision-making in the public sector through real-time data processing, predictive analytics, and more agile responses to policy dynamics. However, challenges remain, such as the digital divide, regulatory limitations, a lack of technical competencies, and integration difficulties with legacy systems. Implications & Recommendations: The government is advised to implement a phased investment strategy supported by agile governance principles, strengthen the legal framework, and integrate inclusive technologies such as Big Data and Blockchain. Contribution & Value Added: This research provides a conceptual and practical framework for adaptive IT investment in AI-DSS, bridging technology and governance.

Breakthroughs Information TechnologyVol. 1(1)
Bangladesh University of Engineering and Technology (BD), University of Technology Malaysia (MY)
Openalex Percentile: Top 60%
Big Data and Business Intelligence
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Adaptive it Investment for Smarter Governance: A Framework for Ai-Based Decision Support Systems in Public Sector — Azanizawati Ma’aram, Shafiqul Islam · Breakthroughs Information Technology (2025) | TGRS Research Map | TGRS