Why data confidence is the foundation of AI-ready facilities management

Artificial intelligence (AI) is firmly on the facilities management (FM) agenda. From predictive maintenance and compliance reporting to energy optimisation and operational planning, organisations are exploring how AI can help teams work more efficiently and make better-informed decisions.

While AI dominates industry conversations, new research suggests many facilities teams may be overlooking a critical prerequisite to success: confidence in their data.

Our latest facilities management research report found that more than half of FM professionals are not confident their data is robust enough to support AI, automation or digital decision-making. Even more concerning, one in five respondents reported that they do not currently measure FM performance at all.

These findings highlight how important it is for facilities leaders to ensure the information that powers their AI is accurate and trustworthy.

The confidence gap behind digital transformation

Facilities teams generate vast amounts of operational data every day. Asset performance, maintenance histories, compliance records, occupancy information, energy consumption and contractor activities all contribute to a growing pool of information that should support better decision-making.

Yet turning data into actionable insight remains a challenge for many organisations.

According to our research, only 5% of respondents describe themselves as very confident that their FM data is robust enough to support AI or digital decision-making. Meanwhile, 52% either lack confidence in their data or remain unsure about its quality and readiness.

The issue is rarely a lack of information. Instead, data is often spread across multiple systems, departments, and service providers, making it difficult to build a complete picture of operational performance. When information exists in silos or is inconsistent in format and quality, confidence quickly erodes.

Why trusted data matters more than AI models

Much of the discussion around AI focuses on the sophistication of the technology itself. However, the value of AI depends far less on the model than on the quality of the information it analyses.

AI can identify patterns, surface risks, and generate recommendations at a scale that would be impossible for most teams to achieve manually. But if the underlying data is incomplete, inaccurate or disconnected, the resulting insights become far more difficult to trust.

This is particularly important in facilities management environments where operational decisions have real-world consequences. Whether maintaining compliance in a healthcare facility, managing building safety obligations in education environments or supporting critical infrastructure, decisionmakers need confidence that recommendations are grounded in reliable information.

Without strong data foundations, organisations risk amplifying existing data challenges rather than solving them. Across the sector, there is no shortage of enthusiasm for AI, and most facilities leaders understand the opportunities it presents. The difficulty lies in turning that ambition into operational reality. Too often, critical information remains spread across disconnected systems, siloed between teams, or held in formats that make it difficult to analyse consistently.

When data cannot be trusted, confidence in the insights generated from it inevitably suffers. That matters because AI is only as effective as the information that underpins it. Before organisations can fully realise the benefits of automation, predictive analytics and intelligent decision-making, they must first create a connected, reliable foundation of operational data that people trust and can act upon with confidence.

Creating a connected view of operations

The report identifies data readiness as one of the most significant barriers to AI adoption across the sector. It notes that information frequently exists across multiple platforms without a unified structure or clear governance framework.

Creating a connected view of operational performance is therefore becoming a priority for organisations seeking to improve both decision-making and AI readiness.

When asset, maintenance, compliance and operational data are brought together, facilities teams gain greater visibility into how buildings and services are performing. Rather than spending valuable time searching for information across disconnected systems, they can focus on identifying risks, resolving issues, and improving outcomes.

This is where a connected data strategy becomes critical. Platforms such as MRI Agora help organisations bring together data from multiple sources, creating a more complete operational picture, and establishing the trusted foundation needed for analytics, reporting and emerging AI capabilities.

Confidence before automation

As organisations explore greater levels of automation, confidence becomes even more important.

AI can accelerate analysis and help uncover opportunities that may otherwise go unnoticed, but human expertise remains essential. Facilities professionals must be able to understand, validate and act upon recommendations using their own operational knowledge and judgement.

This is particularly relevant for environments where safety, compliance, and governance are non-negotiable. While AI can support faster decision-making, organisations still require clear processes, oversight and accountability to ensure recommendations translate into appropriate action.

Rather than replacing facilities professionals, AI should enhance their ability to make informed decisions. The most successful organisations will be those that combine intelligent technologies with trusted data, strong governance, and human expertise.

Building the foundations for the future

The findings from MRI’s research point to a sector that clearly recognises the potential of AI and data-driven decision-making. More than 50% expect to adopt new facilities management technology within the next 12 to 18 months, while AI and data analytics have emerged as the sector’s most important training priority.

However, the research also makes clear that confidence in data remains an obstacle. Until organisations address data quality, governance and integration challenges, they will struggle to unlock the full value of AI and automation.

The next phase of facilities management will be shaped by the organisations that establish confidence in their operational data, connect information across teams and systems, and create a trusted foundation for smarter decision-making.

For facilities leaders, the message is clear: before organisations can trust AI, they must first believe in the data behind it.