This study intends to scrutinize the role of Artificial Intelligence (AI) in Product-Service Innovation (PSI). The literature on AI enabled PSI, other related innovation business models, product-service systems, and servitization has grown significantly since 2018; therefore, there is a need to structure the literature in a systematic manner and add to what has been studied thus far. Product-service innovation is used to represent the relevance of achieving innovation in business models dealing with innovation outcomes including artificial intelligence. This study used bibliographic coupling to analyze 159 articles emerging from the fields of computer sciences, engineering, social sciences, decision sciences, and management. This review depicts structures of the literature comprising five (5) clusters, namely, (1) technology adoption and transformational barriers, which depicts the barriers faced during the adoption of AI-enabled technologies and following transformation; (2) data-driven capabilities and innovation, which highlights the data-based capabilities supported through AI and innovation; (3) digitally enabled business model innovation, which explained how AI-enabled business model innovation occurs; (4) smart design changes and sustainability, which reveals the working of AI in product service environments with different design changes and transformations based on sustainability; and (5) sectorial application, which highlights industry examples. Each cluster is comprehensively analyzed based on its contents, including central themes, models, theories, and methodologies, which help to identify the gaps and support suggestions for future research directions.

本研究旨在探讨人工智能 (AI) 在产品服务创新 (PSI) 中的作用。自 2018 年以来，关于 AI 支持 PSI、其他相关创新商业模式、产品服务系统和服务化的文献显着增长；因此，有必要系统地构建文献并补充迄今为止的研究内容。产品服务创新用于表示在处理创新成果（包括人工智能）的商业模式中实现创新的相关性。这项研究使用书目耦合分析了来自计算机科学、工程、社会科学、决策科学和管理领域的 159 篇文章。本综述描述了由五 (5) 个集群组成的文献结构，即 (1) 技术采用和转型障碍，描述了采用人工智能技术和随后转型过程中面临的障碍； （2）数据驱动的能力和创新，突出人工智能和创新支撑的数据能力； （3）数字化商业模式创新，解释了人工智能商业模式创新是如何发生的； （4）智能设计变更和可持续性，揭示了人工智能在基于可持续性的不同设计变更和转变的产品服务环境中的工作方式； （五）行业应用，突出行业实例。每个集群根据其内容进行全面分析，包括中心主题、模型、理论和方法论，这有助于找出差距并为未来的研究方向提供支持建议。