A Review of Strategic Integration of AI in Business Management and Its Effect on Organizational Behaviors & Efficiency

Abstract

The incorporation of artificial intelligence into business management has become an increasingly important factor influencing organizational efficiency due to increased competition and rapid technological changes worldwide. This literature review, conducted following PRISMA 2020 guidelines, reviews the empirical and theoretical evidence of scholarly works published from 2016 until 2024 about the influence that adopting artificial intelligence as a strategic management tool has on organizational efficiency results. Based on the principles outlined in the Resource Based View and Dynamic Capabilities theoretical paradigms by Barney and Teece, the review finds that there are three principal mechanisms for creating efficiencies from the use of AI data driven decision-making, intelligent automation of processes, and strategic foresight with machine learning models. Barriers to achieving success in implementing AI for organizational efficiency, such as managers' lack of understanding of AI and its capabilities, poor data quality, black box modeling, organizational silo mentality, and unethical AI policies, are identified. Five evidence-based solutions to overcoming barriers, which include AI readiness models, using Explainable AI technologies, cross-functional data governance, scalable small business solutions for AI, and incorporating ethical considerations into AI policy, are offered as means of closing the gap between AI ambitions and its implementation.