IJEBM Vol:1, Issue:2 (2025), Pages 644-663. ISSN: 3079-4218 Ojo et al. (2025) Copyright© 2025 by authors; licensee IJEBM. This publication is open access and can be freely accessed and distributed. AI-driven decision-making in financial management 1 Osaloni Bankole Ojo, 2 Akinadewo Israel S, 3 Duduyegbe Simeon Sunday, 4 Fasakin Akinola Julius, 5 Owoeye Taiwo Omolade 1,2,3,4,5 Department of Accounting, Afe Babalola University, Ado Ekiti, Ekiti State, Nigeria Emails: 1 omoeri@abuad.edu.ng, 2 duduyegbe.simeon@pg.abuad.edu.ng, 3 osalonibo@pg.abuad.edu.ng, https://orcid.org/0009-0008-8634-3024, 4 fasakin.akinola@pg.abuad.edu.ng, 5 owoeyeomolade@pg.abuad.edu.ng, https://orcid.org/0009-0006- 2098-8029 Corresponding Author: osalonibo@pg.abuad.edu.ng Abstract The financial management of registered accounting firms in Lagos State, Nigeria, is assessed in this study using AI-driven decision-making. Specifically, the study aimed to determine how AI-driven financial planning enhances the reliability and effectiveness of organisational operations. The study employed a survey research design because data were collected directly from the respondents. The results indicate that AI-driven decision-making with machine learning, expert systems and natural language has a considerably significant relationship with financial management because its usage in organisational management will assist in enhancing the operation of financial management practice by 19.5% which will enable the financial management to gain more efficient and effective operation. Managing the complex interactions between regulatory frameworks and technological advancements. The study added to the body of knowledge already available on utilising AI-driven decision-making in financial management within registered accounting firms in Lagos State, Nigeria. Based on dialogue between technology developers and regulators that create adaptive frameworks in keeping pace with the rapid advancements in AI, this recommends the successful integration of innovative solutions into financial management. Keywords: Financial management, natural language, expert systems, machine learning, and artificial intelligence. JEL: O30, L80, L86, L68, L63 Introduction