ver the past two decades, our understanding of product devel-opment has changed fundamentally. Disciplines that were onceclearly distinct from one another, such as mechanical engineer-ing, electrical engineering and software development, have nowbecome increasingly intertwined. Products are no longer isolatedobjects, but rather nodes in a network of systems, data and pro-cesses. In this environment, it is no longer enough to manage indi-vidual data sets – they must flow, remain consistent and be avail-able to the right people at the right time. The AI-based lifecyclemanagement system of Digital Threads (Digital Thread for short)has therefore established itself as the backbone of modern sys-tem engineering. Early approaches to product data management(PDM) focused on the central storage of CAD data and the man-agement of versions and approvals. However, with the advent ofcomplex mechatronic systems, networked vehicles and modularplants, it became clear that this approach was not sufficient. Com-panies began to realise that it was not enough to simply store ge-ometries; they needed a system that mapped the entire lifecycleof a product – from the initial requirement through developmentand production to operation and decommissioning. Today, DigitalThreads’ AI-based lifecycle management system acts as a digitalnervous system that connects disciplines such as mechanics, elec-tronics, software and simulation. While system engineering pro-vides methodical approaches for structuring requirements and ar-chitectures, Digital Thread ensures that the associated data is find-able, traceable and up to date. This object-oriented approach cre-ates transparency and enables end-to-end traceability, which is akey requirement of modern systems engineering. Another featureof modern digital thread approaches is the seamless integration ofmodels and product data. Changes in one discipline – for example,in design – can automatically detect and forward all affected areassuch as requirements, tests and functions. This promotes the con-tinuous flow of information and prevents unnoticed consequencesof changes elsewhere in the system. The close link between AI-based lifecycle management systems for digital threads and systemengineering goes beyond technical necessities and promotes cul-tural change in companies.