Artificial Intelligence and Strategic Decision-Making for Sustainable Governance

Authors

  • Mohamed Ibrahim Hassan Farag Department of Business Administration, Military College of Management Sciences, Helwan University, Helwan, Egypt and Department of Political Science, Faculty of Economics and Political Science, Cairo University, Giza, Egypt. https://orcid.org/0009-0004-4989-9261 Author

DOI:

https://doi.org/10.59543/aspp4925

Keywords:

Artificial Intelligence, Strategic Decision-Making, Sustainable Governance, Ethical Governance

Abstract

The increasing use of artificial intelligence (AI) in global governance systems could influence how sustainable strategies are developed by governments and other organizations; however, issues related to accountability, ethical alignment, and inclusivity remain challenges for AI analytical precision and prediction capabilities. This study addresses this question about how AI can be systematically integrated into strategic decision-making processes that enhance transparency, adaptability, and long-term sustainability through the development of a theoretical framework connecting artificial intelligence-driven analysis with structures in ethics and institutions to support sustainable governance via data-based evidence from multidisciplinary literature on AI management, sustainability studies, and governance theory using conceptual analytical methods for synthesizing ideas. The main findings are that good AI governance needs clear accountability mechanisms, open data ecosystem transparency, and the inclusion of sustainability metrics within decision algorithms; however, when governed responsibly, artificial intelligence can shift decisions to strategy instead of administration so institutions can maintain innovation while achieving balance between equity and long-term societal value. 

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Published

2026-04-06

How to Cite

Farag, M. I. H. (2026). Artificial Intelligence and Strategic Decision-Making for Sustainable Governance. Knowledge and Decision Systems With Applications, 2, 447-468. https://doi.org/10.59543/aspp4925

Issue

Section

Articles