Artificiell intelligence in Business strategy

Sammanfattning

Industrial companies view Artificial Intelligence (AI) as the key to faster development and lower costs, but the path from pilot projects to scaled impact is often hindered by fragmented data, unstructured processes, and a lack of competence. This study maps Siemens Energy’s AI maturity within the company’s Product Lifecycle Management (PLM) to reduce the gap toward digitalization goals. An AI maturity model has been developed by adapting and combining established frameworks from the literature and applied through a survey directed at 23 key personnel as well as eight semi-structured interviews. The results show that the company’s AI maturity lies between level two and three on a five-point scale. Big Data security reaches level four, while Big Data quality, Smart data analytics, and Smart decision-making remain below level three. Two critical gaps were analyzed in greater depth: the handling of suppliers BOM data and requirements management. The study shows that unstructured supplier documents, the lack of shared conceptual structures, and fragmented information flows and systems are slowing down automation and data integration in the PLM process. A particular obstacle is the suppliers strong negotiation position, which complicates the imposition of requirements for structured and quality-assured data. To overcome these challenges, technical AI solutions are proposed based on a literature review. The proposals include optical character recognition and large language models, combined with a more strategic and data-driven approach to supplier requirements. The AI solutions aim to automate the extraction and validation of data, improving data quality, reducing manual work, and strengthening information traceability. The study results in an AI strategy with three focus areas: a shared information structure, strengthened AI and data competencies, and a gradual implementation of automated data flows. Together, these measures create the conditions for an unbroken digital thread and increased AI maturity in Siemens Energy’s PLM process.