AI Support in Project Management : Exploring Automation Potential within Vattenfall’s Technical Workflows and Processes

Projects consisting of maintaining nuclear power plants often involve tasks that are documentation-intensive, and must satisfy strict requirements in safety, confidentiality, and traceability. These tasks, that are associated with knowledge work, can be highly time consuming. This thesis investigates how large language models (LLMs) can be implemented to assist in project management workflows from both technical and social perspectives. This was done through a qualitative study of a process within Forsmark nuclear power plant. The results indicated that interview participants saw value in AI-support for tasks such as assistance and drafting in writing reports, evaluating and summarizing documents, coding, translating, and educating. However, there were also fears of implementing AI, as it might cause over-reliance on the technology and can hallucinate. Based on identified requirements an on-premise solution is proposed, centered on RAG with different modes depending on use case. Deployment of such a system is recommended to be incremental to allow for early testing, starting with a semantic search only mode first, as that was identified to potentially be of value. The study concludes that an LLM-integration is possible if designed around the identified requirements, and implemented as socio-technical system, with clear guidelines for use and training for employees.