Eksplorasi Peran Kecerdasan Buatan sebagai Pendorong Kinerja Keuangan dalam Transformasi Digital Berbasis Tinjauan Sistematis atas Metrik dan Dampak Jangka Panjang
DOI:
https://doi.org/10.63822/jem9mw94Keywords:
Artificial Intelligence; Financial Performance; Digital Transformation; Systematic Literature Review; Bibliometric Analysis.Abstract
The integration of Artificial Intelligence (AI) in the digital transformation process has fundamentally changed the operational and strategic landscape of various industrial sectors, redefining the boundaries of efficiency and value creation. This research presents an extensive systematic literature review (SLR) with a bibliometric analysis approach regarding the application of AI in financial management, identifying dominant technologies, their impact on financial performance metrics, as well as the technical and organizational requirements necessary for successful adoption. Based on the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines, this review analyzes 50 peer-reviewed articles published between 2020 and 2026, extracted from leading global and national academic databases such as Scopus, Web of Science (WoS), and Sinta. Network mapping analysis using VOSviewer software reveals a trend shift from basic algorithms to complex modeling that integrates Machine Learning, Deep Learning, and Natural Language Processing (NLP). This technology dominates the implementation of critical functions such as risk management, fraud detection, portfolio optimization, and sustainability reporting based on environmental, social, and governance (ESG) criteria. Empirically, AI has been shown to have an asymmetric relationship and sometimes a U-shaped relationship with financial performance. High initial capital and infrastructure costs have been shown to suppress short-term operational efficiency (reflected in the increase in the Operating Expense to Operating Revenue ratio/BOPO), but gradually provide exponential spikes in long-term market valuation (Tobin's Q) and profitability (ROA, ROE). This study synthesizes theoretical insights using the Technology-Organization-Environment (TOE) framework, Resource-Based View (RBV), and Agency Theory, and underscores the need for a balance between ethical algorithm governance and digital innovation to achieve sustainable competitive advantage.
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