Data sharing remains a central requirement for the digital transformation of the built environment. It supports better decision-making, improves project certainty, strengthens compliance, and enables organisations to work with consistent information across asset lifecycles. As artificial intelligence gains momentum across the sector, a core question continues to surface: is AI accelerating or complicating progress towards effective data sharing?
AI influence
AI systems are now influencing how information is created, structured and exchanged. Their integration into digital construction processes is reshaping debates around interoperability, data governance and responsibility. While the technology has the potential to support a more connected and reliable information ecosystem, it also introduces barriers that organisations must navigate with care.
Data quality
One of the strongest contributions AI offers is its capacity to process large volumes of fragmented project information. Many teams still operate with inconsistent naming conventions, incomplete metadata or legacy file formats. AI-powered data structuring tools can categorise, align and validate this information, reducing manual workload and enabling more accurate data exchanges. When linked with open standards such as IFC or ISO 19650 frameworks, AI has the potential to strengthen overall data quality and improve cross-platform interoperability.
Structure information
AI also supports earlier and more consistent adoption of structured information requirements. Through automated checks and rule-based reasoning, AI can highlight gaps in information delivery, support compliance with project information requirements, and improve confidence in shared data environments. This has clear value for organisations seeking to progress from isolated datasets to connected, traceable digital records.
AI challenges
However, the introduction of AI into the construction data landscape also raises challenges. Many AI tools operate as closed systems, making it difficult to understand how data is processed or transformed. This lack of transparency can undermine confidence in shared data outputs, particularly where decisions influence safety, cost or regulatory compliance. Organisations adopting AI for construction information management must therefore consider explainability and accountability as part of their digital strategy.
Fragmentation
There is also the risk that AI increases fragmentation if vendors develop proprietary formats or data structures. Without strong alignment to open standards, AI applications can create new information silos rather than removing existing ones. This highlights the need for ongoing sector-wide collaboration to ensure AI tools support, rather than bypass, shared data frameworks.
Data governance
A further challenge involves data governance. AI systems depend on high-quality, accessible and well-structured information. If organisations restrict data availability due to concerns about intellectual property, commercial sensitivity or cybersecurity, AI models cannot operate effectively. This makes the case for clear governance frameworks and robust information management practices across projects and portfolios.
AI impact
In practice, AI is neither a standalone solution nor an obstacle. Its impact depends on how it is implemented and whether organisations align the technology with established principles of consistent, transparent and secure data management. When used responsibly, AI can strengthen the foundations for digital construction data interoperability and support a more connected built environment. When adopted without shared standards or governance, it risks creating complexity and uncertainty.
AI is shaping the progress of data sharing in construction. The sector now has the opportunity to guide this development, ensuring the technology reinforces trust in shared information rather than replacing it. The organisations that succeed will be those that combine AI capability with open standards, transparent processes and a long-term commitment to data quality.
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