Asset owners are increasingly turning to AI to improve building performance, compliance and safety, yet many are finding that technology alone is not enough. This article will explore how fragmented building information undermines AI’s potential and the foundational steps asset owners must take before AI can succeed
Artificial intelligence has quickly become a priority for asset owners looking to improve building efficiency, transparency and safety. This reflects a broader shift toward digital asset management and building information management, accelerated by regulatory changes such as the Building Safety Act. Organisations now need unified, well-structured data to make faster decisions, manage risk and operate portfolios with confidence. Yet despite AI’s promise, one systemic challenge continues to limit progress: building information remains scattered and is often incomplete.
Many organisations have digitised documents, but the information still sits across shared drives, legacy platforms, email archives, contractor CDEs and scattered servers (or even USBs). This fragmentation slows even the most capable teams. Studies show facility employees spend 1–2 hours each day searching for building information (ARC Facilities), and that 80% of employees lose around 30 minutes per day retrieving data in inefficient environments (Asset Infinity). For asset owners, these delays escalate into slower decisions, higher operational risk and unnecessary cost.
Strong data foundations
AI cannot resolve these issues when the underlying data is incomplete, inconsistent or difficult to locate. If information is unlabelled or outdated, AI cannot determine which document is authoritative. Multiple versions of an inspection report without metadata make it impossible for a model to identify the right one. When naming conventions vary widely, systems cannot draw accurate links between assets, zones or components. Fragmented information leads to fragmented intelligence – and for AI, that means inaccurate or even hallucinatory outputs.
That’s why improving data foundations is becoming a priority for asset owners. A consolidated environment reduces reliance on individual knowledge, eliminates manual searching and supports faster operational responses. When documents are consistently named, logically grouped and stored in one secure place, teams gain clarity that digitisation alone cannot achieve. As buildings grow more complex and regulations evolve, this clarity becomes essential.
Strong information practices also enable Golden Thread grade transparency and traceability across the building lifecycle. Knowing where documents originate, how they have changed and who has accessed them is vital for confident decision-making and compliance. A unified platform allows asset owners to track this in one place rather than relying on a patchwork of systems with limited visibility. The aim is not just to organise information, but to create a dependable record that supports audits and evidences compliance, such as safety cases and long-term planning.
Once this foundation is in place, AI can deliver meaningful value. Structured information allows AI to retrieve documents quickly, interpret asset relationships and highlight gaps requiring attention. Instead of manually searching for certificates or installation details, teams can obtain what they need through simple queries, freeing time for higher-value work.
The next generation of AI tools goes far beyond simple search
These systems understand the language, structure, and relationships within building information, allowing them to read O&M manuals, interpret drawings, recognise asset hierarchies, and identify documents supporting critical safety or operational questions. Operating within secure, closed environments, they respect role-based access, maintain audit trails and ensure every response links to a verified document. Users can ask natural-language questions – such as “What is the warranty on the lift in Building A?” or “Show me all fire-safety certificates expiring this quarter” – and receive accurate answers with authoritative sources attached.
The impact is significant. Tasks that once required sifting through thousands of files, hunting across multiple systems, or relying on individual memory become instant and reliable. Asset owners and facilities teams benefit from faster decisions, reduced compliance risk and clearer visibility across the lifecycle.
Achieving this standard begins long before building operation. When contractors capture, validate and organise documentation consistently throughout a project – using clear templates, naming conventions and defined folder structures on a single platform – asset owners receive information ready for immediate use. For existing buildings, consolidating dispersed documents into one central environment and identifying gaps ensures incomplete data can be backfilled and legacy information improved. Asset owners also play a key role: by specifying contractors to use a dedicated handover provider like Zutec and adding existing building data into the same environment, they create a single, secure repository that is easier to manage across the lifecycle and gives AI a reliable foundation to act upon.
The future of purpose-built systems
The future of AI in building operations will be shaped not by general storage platforms like SharePoint or Dropbox using generic AI assistants, but by systems purpose-built to understand built assets and operate within structured environments. Those who invest in the right foundations today will be best positioned to unlock the intelligence and operational benefits AI can offer.
To understand more about preparing your building data for AI, you can read Zutec’s paper ‘Find What Matters: The Data Foundations for AI-Driven Building Information.
The post Why AI won’t fix fragmented building data – and what asset owners must do first appeared first on Planning, Building & Construction Today.
