Efficient and safe maintenance through AI
| Reference number | |
| Coordinator | Stiftelsen Blue Institute |
| Funding from Vinnova | SEK 1 000 000 |
| Project duration | August 2024 - June 2025 |
| Status | Ongoing |
| Venture | Regulation and cutting-edge technology |
| Call | Regulations and ground-breaking technology |
Important results from the project
The project was carried out as planned with workshops, interviews and mappings. The goal of testing policy labs as a method and creating learning on AI in maintenance was achieved, but concrete changes to TDOKs were not proposed due to complex change management processes and fragmented ownership. Instead, the project contributed with increased understanding, new networks among actors and insights into barriers and opportunities for future AI use in infrastructure.
Expected long term effects
The project is expected to contribute to increased knowledge and readiness to use AI in infrastructure maintenance. In the long term, this may lead to more efficient resource use, reduced costs and improved safety. At the same time, the need for ownership and effective processes for managing and adapting technical regulations is highlighted, which is a prerequisite for realizing the potential.
Approach and implementation
The project was carried out as planned with four workshops, prepared through mappings, interviews and international benchmarking. Activities provided valuable input, though concrete policy proposals were harder to achieve. The timetable was followed and collaboration worked well. A key lesson was that complexities and shared responsibilities around TDOKs limited real change within the project’s time and resource constraints.