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Developing an artificial intelligence-driven smart financial management model for strengthening corporate financial resilience amid technological disruption and market volatility Kusiyah Kusiyah; Loso Judijanto; Gregorius Paulus Tahu; Budi Setiadi; Moh Sholeh
Lentera Negeri Vol. 7 No. 1 (2026): Lentera Negeri
Publisher : Indonesian Institute For Counseling, Education and Therapy

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29210/993210

Abstract

Technological disruption and increasing market volatility have challenged the effectiveness of conventional corporate financial management systems, creating an urgent need for more adaptive and intelligent financial strategies. This study aims to develop an Artificial Intelligence-driven Smart Financial Management model for strengthening corporate financial resilience through a qualitative library research approach. Data were collected from books, peer-reviewed journals, conference proceedings, institutional reports, and other relevant academic literature, and analyzed using qualitative content analysis. The findings indicate that Artificial Intelligence significantly enhances financial intelligence, predictive analytics, intelligent decision-making, continuous risk monitoring, and adaptive organizational learning, enabling organizations to respond proactively to financial uncertainty. The study further proposes an integrated conceptual framework that positions AI-driven Smart Financial Management as a strategic organizational capability supporting financial flexibility, organizational adaptability, and sustainable performance. The proposed model extends Dynamic Capabilities Theory by explaining how AI strengthens organizational sensing, seizing, and transforming capabilities within financial management. The study offers theoretical contributions by integrating fragmented research streams while providing practical implications for organizations seeking to improve financial resilience and sustain competitiveness in rapidly changing technological and economic environments.