Considerable amounts of data are collected on the UK’s stock of bridges. Much of these data are collected to inform the planning and scope of maintenance activities. This paper reports on the results of a series of semi-structured interviews with 17 individuals involved in UK bridge asset management and data collection activities to explore how such data are used in practice. A wide spectrum of organisations and industrial sectors is represented in this dataset. Hierarchical Process Modelling was used to characterise, the UK’s bridge management system and define the processes and sub-processes involved in the management of bridges. Key quotations are used from the interviews to reveal the state of data collection and use in UK bridge infrastructure from the perspective of those directly involved. The study concludes that there is significant variation within the industry of the use of visual inspection data and that formal Structural Health Monitoring (SHM) remains relatively rare. Furthermore, there is a need to develop a new unifying paradigm that will frame the efficient and effective application of emerging artificial intelligence and data science enabled (i.e. ‘smart’) condition monitoring techniques to bridge management.