Beyond the Common Data Environment: unlocking supply chain collaboration with neuro-symbolic artificial intelligence

Across the built asset lifecycle, information governance and exchange processes are typically administered by humans. Bandwidth has been gained through standardisation of processes and tooling, notably by way of ISO 19650 and the Common Data Environment (CDE), but data volumes continue to increase. This constrains the sector’s ability to capitalise on information-intensive innovations such as robotics and agential artificial intelligence (AI). This paper presents a neuro-symbolic framework for AI augmentation of the CDE, capable of semi-autonomous information governance, retrieval and exchange. The framework employs AI-driven knowledge mining of built environment datasets to transform them into navigable, well-organised knowledge bases. Building on this foundation, the framework introduces ontology-based data access and model context protocol integration, enabling AI agents to navigate multi-platform technology ecosystems with human-like contextual reasoning. The framework offers immediate practical benefits, reducing information management costs and addressing skills shortages, while unlocking transformative capabilities for the future. By enabling the system to process complex, multi-faceted queries autonomously and return contextually appropriate responses to both human and machine requestors, the framework removes manual information processing constraints. The result is a vendor-agnostic, security-preserving framework that enhances existing data governance while dramatically expanding the sector's capacity for information-intensive innovation and inter-organisational collaboration.