AI-Driven Process Automation in Product Lifecycle Management: A Transformative Approach

Abstract

The integration of Artificial Intelligence into Product Lifecycle Management represents a transformative paradigm shift in manufacturing and product development. This comprehensive article examines how AI technologies fundamentally reshape PLM systems from passive information repositories into dynamic, intelligent platforms that actively participate in decision-making processes throughout the product lifecycle. The evolution of PLM systems is traced across four generations, from basic document management origins to sophisticated AI-enhanced ecosystems that deliver unprecedented levels of efficiency, innovation capacity, and collaborative capability. Technical applications of AI within modern PLM frameworks are detailed, including process automation through machine learning, advanced analytics for decision support, and digital twin technology. The critical role of enterprise data integration and governance in enabling effective AI deployment is explored, highlighting how semantic modeling, entity resolution algorithms, and intelligent data governance mechanisms create unified information environments that transcend traditional organizational boundaries. Despite compelling benefits, significant implementation challenges persist, including data quality issues, integration complexity, organizational resistance, and resource constraints. Looking forward, emerging technologies including quantum computing, extended reality integration, and increasingly autonomous PLM systems promise to revolutionize product development practices further. This examination provides manufacturing enterprises with comprehensive insights into how AI-driven process automation in PLM can deliver substantial competitive advantages through accelerated innovation cycles, enhanced product quality, optimized resource allocation, and improved sustainability outcomes.