Outlook for 2025: How AI and the Digital Thread are Shaping the Future of PLM
The integration of artificial intelligence (AI) into product lifecycle management (PLM) marks a turning point. While PLM systems have primarily served to connect and manage structured data, they are now gaining proactive and collaborative capabilities through AI. The digital thread, essential for connecting data and processes, is now the cornerstone of modern product development and manufacturing.
“PLM and AI are forming a symbiotic partnership, with each technology enhancing the other. PLM provides the data, creating a foundation for AI to analyze and interpret,” says Leon Lauritsen, Aras’ General Manager, Europe. “Realizing AI’s full potential in an industrial setting requires the integration of diverse stages across the product lifecycle.”
The digital thread keeps critical product information seamlessly connected, enabling advanced analysis, learning, and real-time decision-making. This transformation impacts every stage of production—from manufacturing and design to recycling. Lauritsen notes, “With the help of innovative AI technologies, we’re witnessing the rise of a new generation of adaptive, self-learning, and proactive PLM solutions, empowering companies to operate more flexibly and efficiently.”
The Digital Thread Becomes an Active Advisor
The digital thread continuously gathers and analyzes data from design, manufacturing, operations, and maintenance, seamlessly integrating insights into new product generations. The result: faster development, reduced costs, enhanced quality, and better alignment with customer needs.
A constant flow of data keeps the PLM platform adaptive and intelligent, encompassing production analysis, supplier status checks, and customer feedback. These valuable insights feed into the development of manufacturing processes as well as precise sales forecasting. The software generates intelligent optimization suggestions from the analyzed data, supporting the strategic positioning of new products in the market.
“The digital thread enables AI to continuously track customer needs and adjust product development accordingly. This capability drives hyper-personalization, allowing products to adapt in real-time to individual requirements,” added Lauritsen.
Teaching AI to Understand the Business
An example of the extensive range of AI-supported application systems is its use at marine specialist Thyssenkrupp Marine Systems (TKMS). Software-supported analysis of internal processes aims to create a digital image of the entire company. Dr. Kira Giesecke, Head of Value Chain Strategy at TKMS, explains, “With the capabilities we now have with Aras Innovator, we connect information, enabling us, among other things, to teach AI how our company operates.”