Impact of Artificial Intelligence Adoption on Managerial Decision-Making and Organizational Performance: A Meta-Analytic and Empirical Investigation
DOI:
https://doi.org/10.31305/rrijm2026.v06.n01.015Keywords:
Artificial Intelligence Adoption, Managerial Decision-Making, Organizational Performance, Meta-Analysis, PLS-SEM, Indian EnterprisesAbstract
The integration of Artificial Intelligence (AI) into organizational decision-making processes has emerged as a transformative force reshaping managerial practices and performance outcomes. This study employs a meta-analytic approach to quantitatively synthesize empirical evidence on the relationship between AI adoption, managerial decision-making effectiveness, and organizational performance. Drawing on 25 peer-reviewed empirical studies published between 2019 and 2025, the meta-analysis examines effect sizes across 12,847 observations from organizational contexts globally, with specific focus on Indian enterprises. The analysis reveals a significant positive relationship between AI adoption and managerial decision-making effectiveness (r = 0.42, 95% CI [0.38, 0.46]), and between decision-making effectiveness and organizational performance (r = 0.48, 95% CI [0.44, 0.52]). The mediation analysis confirms that decision-making effectiveness significantly mediates the AI-performance relationship. Furthermore, the study incorporates primary empirical validation through survey data from 312 Indian organizations, analyzed using PLS-SEM. The findings provide robust evidence that AI adoption, when effectively integrated into decision-making processes, significantly enhances organizational performance. The study contributes to the theoretical understanding of AI's role in organizations and provides practical guidance for managers navigating AI implementation.
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