To remain agile and competitive, organizations must design globally while executing manufacturing, sales and services locally. Achieving this balance demands more than just robust systems – it requires intelligent, integrated platforms that can manage the entire lifecycle of a product—from concept to retirement, with agility and precision.

Product Lifecycle Management (PLM) and Application Lifecycle Management (ALM) platforms are central to this transformation. As industries face increasing complexity, these systems must evolve to become smarter and more responsive, supporting the modern industrial world with constant change, demanding faster innovation and greater efficiency.

Integrating AI with PLM and ALM is no longer optional, it’s essential. AI enhances collaboration, improves product data quality and boosts user efficiency by addressing the following challenges.

• Repetitive activities are time consuming impacting user efficiency / productivity

  Manually managing large volume of data during the product development process in the form of product structure, entities and their relationship is a tedious task. This leads to not only a significant time consumption in performing various activities like product data creation, modification, release, etc., but also impacts the quality of data.

• Quality of data impact decision making

  Getting access to the right and required data during different stages of product development process is an imperative, but compiling these details manually adversely affects accuracy.

• Lack of better collaboration causes duplication of efforts

  Data silos and disconnected platforms delay decision-making and duplicate efforts, making it difficult to access timely, relevant insights. AI-powered platforms unify workflows, enabling engineers to access timely, relevant insights and collaborate more effectively.