Will AI revolutionize how knowledge is shared; enhancing knowledge sharing in construction through AI; a case study of Peab

Abstract

Peabs’ existing knowledge lifecycle starts with the employees creating new knowledge during the project, and the knowledge is shared in post-project reviews at the end of the project, however, the documentation from the meeting consisted of only short sentences and keywords. The reports from the post-project reviews are stored in locked project platforms and are not shared with the rest of the organisation, and the knowledge lifecycle is broken. The critical information the interviewees would like to access in the organisation is solutions that can be applied to a project when they have encountered an issue related to an activity, material, or technical solution that the interviewees have not worked with before. This thesis advises on how to conduct an effective post-project review to gather as much knowledge as possible from the teams. The thesis also recommends building an organisational knowledge database that the whole organisation can access and close the knowledge lifecycle. When the knowledge life cycle is whole, the thesis investigates how the life cycle can be made more efficient with AI. Three AI tools are recommended for the lifecycle: a transcription tool to intercept more valuable information from the post-project reviews, a summarization tool to create descriptive documentation of the transcription, and a GPT tool to store, search, and distribute the collected knowledge. The thesis also discussed the social aspects of the post-project reviews and the knowledge that cannot be collected and shared in the knowledge lifecycle.