Strategic decision making in post-merge and acquisition in the software industry : the role of AI-powered business intelligence

Abstract

This study investigates the complex challenges faced by leadership during post-merger and acquisition (M&A) integration within the software industry and explores how AIpowered Business Intelligence (BI) tools can support strategic decision-making, operational efficiency, quality maintenance, and process improvements. Additionally, it examines the ethical implications of using such tools in organizational decision-making. Using quantitative research design, multiple linear regression and independent samples t-tests were applied to assess the impact of three main independent variable groups which are M&A integration factors, AI-powered BI tool capabilities, and ethical considerations on key organizational performance outcomes. The findings reveal that cultural challenges are the most significant barriers to successful integration, consistently affecting decision-making effectiveness, quality consistency, and operational efficiency. Conversely, BI capabilities such as data consolidation, real-time insights, and communication support were found to significantly enhance organizational performance post-M&A. Ethical factors, particularly data transparency and clear governance, also contributed meaningfully to effective strategic decision-making and quality outcomes. The research concludes that while M&A integration challenges can undermine organizational success, their impact can be mitigated through targeted use of AI-powered BI tools and adherence to ethical practices. The study offers actionable recommendations for integrating BI systems and ethical governance into M&A strategies, contributing both to academic understanding and real-world application in the context of digital transformation.