Integrated AI and Business Intelligence Maturity: Drivers of FP&A Decision Making Quality

Abstract

Business Intelligence (BI) constitutes a suite of technologies that enhance managerial and analytical decision-making, while the integration of Artificial Intelligence (AI) into accounting and finance has expanded considerably in recent years. This study proposes an evaluation framework structured around four critical dimensions—technology, data, processes, and organizational readiness—and applies it through comparative case analyses of Tencent, Lenovo, and Dah Sing Bank. By combining qualitative insights with quantitative assessment, the research empirically demonstrates a positive correlation between AI/BI maturity and the quality of Financial Planning and Analysis (FP&A) outcomes, specifically in prediction accuracy, decision timeliness, scenario and sensitivity analysis, and strategic influence. The results indicate that enterprises with high AI/BI maturity achieve substantial improvements in predictive capability, operational agility, and strategic impact, whereas low-maturity firms remain dependent on traditional spreadsheet-based tools such as Excel, which constrain efficiency and adaptability. The findings contribute to the literature on digital transformation in accounting and finance, while also offering practical guidance for enterprises seeking to optimize FP&A practices through the systematic advancement of AI and BI maturity.