Artificial Intelligence Implementation Strategies in Business: A Systematic Review

Businesses and economies are eager to adopt AI to enhance operational efficiency and maximise profits. However, managers often struggle to identify the best practices for effectively implementing AI, and the successful integration of AI poses a significant challenge for many organisations. This study aims to identify the most effective strategies for integrating AI into business and to provide guidelines for implementation based on existing literature and industry practices. Using the PRISMA protocol, a systematic review with bibliometric analysis was conducted on 76 articles retrieved from the Scopus and Clarivate Web of Science databases. Literature supports the implementation of AI in three major stages. First, the pre-implementation stage involves organisations planning and developing the aims, objectives, and policies for AI implementation. This is followed by the implementation stage, where organisational, process, technological, environmental, and individual factors are considered. Finally, in the post-implementation stage, organisations must monitor, evaluate, and make necessary adjustments and corrections to ensure effective and timely communication. Companies should consider redesigning jobs to augment AI with human capabilities. The study offers a structured approach for organisations to select and tailor AI systems that align with their unique business models, cultures, and capabilities.