Navigating Finance Transition: A Thematic Review of AI Revolution and its Implications

Résumé

Artificial intelligence is increasingly embedded in financial activity, yet the literature remains divided between technical studies of algorithmic capability and application-based studies on specific financial functions. This fragmentation limits the understanding of how AI is changing finance as an integrated decision environment. This article provides a thematic review of AI in finance, focusing on how AI alters information handling, decision support, automation, governance and accountability across financial domains. The review draws on a structured corpus of 70 sources, including peer-reviewed articles and institutional reports, selected through a staged screening process covering academic databases and targeted regulatory and institutional sources. The findings indicate that AI does not simply provide novel instruments to established financial practices, it reorganises the chain through which financial decisions are prepared, assessed, justified and controlled. Across corporate finance, capital markets and international finance, AI expands operational capacity while shifting pressure towards validation, explainability, human oversight and institutional responsibility. The review also identifies persistent constraints regarding data quality, model opacity, cyber exposure, third-party dependence, regulatory fragmentation and uneven evidence maturity. The article argues that the future value of AI in finance will depend less on technological sophistication alone than on the capacity of firms, investors, regulators and researchers to maintain accountability, resilience and trust within machine-assisted financial decision structures. Future research should therefore examine AI under actual institutional constraints, focusing more on governance performance, human intervention, systemic effects and decision accuracy.