Construction and maintenance of the transport infrastructure presents many hazards to workers. In the United Kingdom (UK), safety issues are recognized by government agencies (e.g., Health and Safety Commission, Highways Agency), academia, and industry alike. Increasing skill short-ages and an aging working population present problems on collating, organizing, and redistributing safety knowledge before existing workers retire or change jobs. Any influx of international workers also brings problems of language, effective communication, and training into the mix. The knowledge and experience of these workers needs to be tapped and used in the measurement of risks and their subsequent management. In response to these issues, the artificial intelligence methodology, case-based reasoning, has been incorporated into an information technology tool to improve hazard identification and management during a worker's daily tasks of identifying hazards and determining appropriate mitigations. The tool prompts users to classify a given work task and then, using a stored library of cases, suggests possible mitigation strategies. The user can accept or reject suggested mitigations. Results are fed back into the system, which becomes more refined for the next work task and next user. The tool is being developed in collaboration with Carillion Transport, a large UK infrastructure development and management contractor. It is in the development stages, but the ultimate aim will be deployment of the tool to those working in the field of construction and maintenance in infrastructure. A working example of the tool is given, followed by a presentation of its strengths and opportunity for improvement.