A Systematic Review of Business Strategy Transformation Using AI, Machine Learning, And Deep Learning

Abstract

The integration of Artificial Intelligence (AI), Machine Learning (ML), and Deep Learning (DL) has revolutionized business strategies, enabling organizations to enhance decision-making, optimize operations, and achieve competitive advantages. This systematic review examines the transformative role of these technologies in reshaping business strategies across various industries. A total of 115 peer-reviewed articles were systematically analyzed following the PRISMA guidelines to ensure transparency, rigor, and reliability. The study identifies key applications of AI, ML, and DL in marketing, supply chain management, financial analytics, and human resource management, showcasing their ability to address complex business challenges. Additionally, emerging trends such as Explainable AI, AI integration with IoT and blockchain, and AI-powered sustainability initiatives are discussed, highlighting their potential to redefine traditional business practices. Despite these advancements, challenges such as algorithmic bias, data quality issues, implementation costs, and the lack of regulatory frameworks remain significant barriers to adoption. The review also identifies critical research gaps, including limited studies on AI adoption in small and medium-sized enterprises (SMEs) and developing economies. By synthesizing insights from these articles, this study provides a comprehensive understanding of how AI, ML, and DL are shaping modern business strategies, offering valuable directions for future research and practical implementation.