The emergence of Industry 5.0, following the widespread adoption of Industry 4.0, marks a pivotal shift in digitalization and industrial operations. This article explores the implications of Industry 5.0 principles and enabling technologies within the Architecture, Engineering, Construction, Management, Operation, and Conservation (AECMO&C) industry, with a particular focus on the conservation of built cultural heritage environments. The results obtained from a systematic literature review and an online survey are summarized and discussed. Results reveal that artificial intelligence and digital twins are the most frequently studied enabling technologies in this context, while sustainability emerges as the dominant principle in the discourse surrounding this novel paradigm. Conversely, the principles of resilience and human-centrism remain underexplored, highlighting the need for further research to achieve a holistic implementation of Industry 5.0 in conservation practices. Furthermore, although awareness of Industry 5.0’s potential is growing, its adoption in heritage conservation remains limited due to knowledge gaps, inadequate training, and resource constraints. This underscores the need for comprehensive strategies to integrate Industry 5.0 principles and technologies into the conservation of built cultural heritage. Insights presented are intended to guide conservation practitioners seeking best practices, inform policymakers promoting technological adoption, and inspire researchers to address existing gaps and drive further innovation.

Despite its recent adoption, Industry 5.0 has attracted significant attention from researchers across various fields. However, the Architecture, Engineering, Construction, Management, Operation, and Conservation (AECMO&C) industry, particularly in the context of built cultural heritage conservation, has lagged in this regard. This study aims to gain a deeper understanding of conservation professionals’ perceptions regarding the adoption of Industry 5.0 principles and enabling technologies, as well as the perceived barriers and the skills needed to address them. A survey questionnaire was designed, tested, and implemented to collect relevant data. Analysis of the collected data reveals that, although there is a clear recognition of the significance of Industry 5.0 principles and enabling technologies, their application in built cultural heritage conservation remains limited. Future initiatives should prioritise bridging knowledge gaps, enhancing training programmes, and securing necessary resources to overcome these existing barriers.

Masonry buildings of historical centres are usually organized within aggregates, whose structural performance against seismic actions is challenging to predict and constitutes still an open issue. The SERA—AIMS (Seismic Testing of Adjacent Interacting Masonry Structures) project was developed to provide additional experimental data by testing a half-scale, two-unit stone masonry aggregate subjected to two horizontal components of dynamic excitation. In this context, this paper investigates the reliability of the modelling approach and the assumptions adopted to generate a three-dimensional continuum finite element model. The work involves two stages, namely a blind pre-diction and a post-diction phase, and proposes a series of simulation analyses including a strategy to shorten the actual records and save computation costs. The study was performed to investigate the extent of uncertainty in modelling for such masonry aggregates in relation to the experimental outcomes. Pre-diction results were proven to be not accurate in terms of predicted displacements and damage patterns. The upgrades introduced for the post-diction analyses, including the calibration of the elastic modulus and the introduction of a non-linear interface between the two units, allowed to improve the outcomes, with reasonable results in terms of predicted base shear force, displacements along Y-direction and damage pattern for the non-linear stage. The overall approach showed to be appropriate for the structural analysis of existing masonry aggregates, but the accurate modelling of this type of structure remains challenging due to the high level of uncertainties.