Implementation Models for AI and Technology – A Review

Abstract This systematic review synthesizes and classifies diverse theoretical models and frameworks guiding technology and artificial intelligence (AI) implementation in organizations. Through analysis of literature, this study develops a novel classification framework identifying six critical dimensions of implementation models: implementation object, analysis level, transformation character, implementation method, adaptation focus, and implementation depth. The research reveals three significant trends: (1) an evolution from technology-centric to holistic socio-technical approaches, (2) the emergence of specialized AI implementation frameworks addressing unique challenges of artificial intelligence, and (3) the necessity of multi-level synchronization during implementation processes. This review makes four primary contributions: establishing a comprehensive classification system that coherently organizes existing models, identifying emerging patterns in contemporary implementation approaches, proposing an integrated framework that combines complementary perspectives, and providing evidence-based recommendations for practitioners navigating complex implementation challenges. This unified perspective bridges previously fragmented implementation approaches across disciplines and offers a more cohesive foundation for both theoretical advancement and practical application in organizational transformation.