Jul 2026· Krakatoa Management Research Journal· Vol 1, pp. 153-168· 0 citations· 31 references
TL;DR
Artificial intelligence should be treated as an organizational capability rather than a stand-alone technology because its financial value depends on responsible integration with financial processes and governance systems.
Abstract
Purpose: This study examines the relationship between artificial intelligence (AI) integration and organizational financial performance and identifies the conditions that strengthen or weaken this relationship.Methodology: The study uses a qualitative literature-review design. Twenty peer-reviewed journal articles published between 2019 and 2026 were synthesized through thematic content analysis.Results: The literature identifies four recurring mechanisms: operational efficiency and cost control, risk and fraud reduction, revenue and investment optimization, and financial reporting and assurance. AI is generally associated with stronger profitability, cost efficiency, risk-adjusted returns, asset allocation, and firm value when supported by reliable data, adequate infrastructure, skilled personnel, explainable models, and effective governance.Conclusions: AI should be treated as an organizational capability rather than a stand-alone technology because its financial value depends on responsible integration with financial processes and governance systems.Limitations: The review is limited to twenty articles, uses qualitative synthesis rather than meta-analysis, and includes more evidence from banking, auditing, and investment than from nonfinancial sectors.Contributions: The study integrates fragmented evidence into a direct conceptual account of the AI-financial performance relationship and provides a basis for future company-level empirical research.
Financial Risk Management (FRM) has evolved from a conventional financial control mechanism into a strategic capability that supports organizational resilience and long-term performance amid increasing economic, technological, and environmental uncertainty. This study aims to synthesize contemporary research on the rel...
M. B. Utama, Adi Purmanto· Business and management· 0 citations
Across the reviewed studies, machine learning, AI-based computational modeling, text mining, natural language processing, and bibliometric analysis were the most frequently used methodological approaches.
L. M. De La Fuente, F. Yambao· Journal of Interdisciplinary...· 0 citations
This study investigates the relationship between artificial intelligence, AI capability and financial performance in Islamic banks and examines whether risk management serves as a mediating mechanism in this relationship. Drawing on the resource-based view and dynamic capabilities theory, the study further examines whe...
Quratulain Zafar, Haris Mehmood, Surayya Jamal et al.· SOCIAL PRISM· 0 citations
The empirical findings reveal that both PMC and leverage exert a positive and statistically significant influence on financial performance, whereas capital structure does not demonstrate a significant effect, and moderation analysis indicates that corporate governance strengthens the impact of capital structure and lev...
M. Septriawan, Zuliana Zulkarnen, R. N. Fonna et al.· Jurnal Investasi Islam· 0 citations
This systematic review examines how artificial intelligence can support strategic decision-making in private universities, the organizational conditions shaping its value, and the governance and implementation risks that constrain responsible use and identifies four interconnected roles of AI: environmental intelligenc...
Yun-Dong Wu, Wei-Jian Kong· Artificial Intelligence in E...· 0 citations
Artificial intelligence has moved from specialised analytical support to a strategic infrastructure for banking, yet evidence of transformation remains more uneven than the prevailing innovation narrative suggests. This critical narrative review examines how artificial intelligence is changing bank operations, customer...
Mesud Mohammed, G. Japee· Asian Journal of Economics B...· 0 citations
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