Leveraging AI to Enhance Systems Engineering Practices in Large-Scale Infrastructure Projects

Paper i proceeding, 2025

The increasing complexity of large-scale infrastructure projects presents significant challenges and specifically challenges in Systems Engineering (SE) activities, particularly in managing vast volumes of data, evolving stakeholder requirements, and maintaining traceability across long project lifecycles. This study explores the potential of Artificial Intelligence (AI), particularly tools based on Natural Language Processing, to support SE practices in infrastructure contexts. Through a combination of survey data, two pilot studies, and five semi-structured interviews conducted within the Swedish national transport administration, the research investigates how AI can improve system information management, assist with Systems Engineering tasks, and what practical barriers limit broader adoption. Findings indicate that AI tools show promise in supporting text-heavy SE tasks such as document summarization, requirement tracking, and assumption analysis. However, low organizational awareness, trust concerns, lack of integration into workflows, and restricted access to internal data due to security concerns significantly limit their current impact. The study concludes by recommending targeted organizational strategies, operational support roles, and structured experimentation to unlock the full potential of AI in supporting SE in large-scale infrastructure projects.