Artificial Intelligence and Organizational Performance: Mediating Factors, Integration Conditions, and Strategic Implications

Abstract

In a context of accelerating digital transformation, artificial intelligence (AI) has emerged as a key strategic driver for contemporary organizations. This paper examines the mechanisms through which AI adoption contributes to organizational performance improvement, as well as the organizational conditions that shape its effectiveness. Drawing on a systematic literature review conducted following the PRISMA 2020 protocol, yielding a final corpus of 60 sources from six academic databases (Scopus, Web of Science, ScienceDirect, Emerald Insight, SpringerLink, and Google Scholar) over the period 2015–2025, and grounded in four complementary theoretical frameworks (Resource-Based View, Dynamic Capabilities, TAM, and UTAUT), the study proposes an integrative conceptual framework linking AI adoption, mediating organizational factors, and performance outcomes. Findings suggest that AI could enhance operational efficiency, foster innovation, and strengthen competitive advantage, yet its impact is contingent upon organizational culture, strategic leadership, AI governance, data quality, and employee competencies. This research contributes to the strategic management literature by offering an integrated and structured account of AI's role in organizational value creation and provides practitioners with an analytical framework to guide their AI integration strategies.