Across construction boardrooms and project hubs throughout the UK, a long-simmering conversation is gaining urgency. After years of growing pressure, one question is becoming unavoidable: who actually controls the data that underpins and runs our projects?
New research from Revizto examining the technology priorities of 600 CIOs across the US, UK, Europe, Australia and the Middle East reveals the scale of the concern: 96% of construction CIOs report anxiety about data ownership and control across their tech stacks. In the UK, that figure rises to 99% – the highest of any market surveyed.
And 18% of UK respondents describe themselves as “extremely concerned” compared with 14% globally. This is not background noise. It is an alarm.
The industry has spent the better part of a decade accumulating tools – BIM platforms, coordination software, cloud environments, field applications – in pursuit of a more connected, more efficient way of building.
In many respects, those investments have delivered. Our customers have saved as much as $15m on a single project through early coordination issue resolution and regularly report rework cost reductions of between 2% and 5%.
But they have also created a new category of risk: data governance gaps. When project-critical information lives across multiple vendor environments, each with its own licensing terms and data policies, the question of what happens when a contract ends, a relationship sours or a vendor experiences a data breach is no longer theoretical. It is a genuine governance problem.
The stakes here are high, and not only in the abstract. Our Bridging the Gap report found that 92% of the AEC teams surveyed experience cost overruns of 6% or more on their projects. That figure represents billions of pounds in lost value across project cycles. When margins are already thin and timelines are long, the notion that a firm cannot readily access, migrate or interrogate its own project data is a financial and operational liability.
Data and the AI readiness gap
What makes this moment particularly complex is that it has collided with the arrival of artificial intelligence as a genuine capability, not just a promise. The pressure to deploy AI across construction workflows is intense and, in many organisations, driven from above and below the CIO’s desk.
Yet the research exposes a significant AI readiness gap. In the UK, 31% of CIOs cite regulatory uncertainty as the single biggest barrier to gaining value from AI – again, the highest of any market surveyed.
Every UK CIO surveyed still faces at least one barrier to gaining value from AI, compared with 10% of CIOs globally who report no barriers remaining. There is real AI fatigue setting in before it has even begun to take hold.
The dynamic this creates is one the industry must take seriously. AI cannot produce reliable outcomes when built on fragmented, poorly governed or unreliable data. Deploying powerful automation on broken workflows does not accelerate delivery – it accelerates failure, and it does so at scale.
As AI capabilities mature, the underlying data may no longer need to be fully cleaned, labelled or centralised. But understanding where that data sits and who can access it will remain critical. The CIOs who succeed in this era won’t be the ones moving fastest on AI adoption but the ones who get the foundations right first.
This is not an argument for conservatism. Construction has real coordination problems and technology plays a vital role in solving them. But the right sequencing matters enormously.
Before any organisation can extract meaningful value from AI-driven coordination, model analysis or predictive risk tools, it needs to be confident in the quality, accessibility and ownership of the underlying data those tools will act upon.
That means making deliberate decisions now about which platforms hold your project data, under what terms and with what portability rights. Vendor lock-in, in an environment where the tools themselves are changing rapidly, is a strategic risk that deserves boardroom-level attention.
There is also a consolidation story emerging from the data. 45% of UK CIOs plan to consolidate their tech stack over the next 12 to 18 months. This is above the global average of 39% and sharply at odds with the narrative that more tools equal more capability.
The UK market is in a mode of deliberate simplification and that is a healthy instinct. The firms that have accumulated the most fragmented environments – or what I like to call “tool sprawl” – often have the least visibility into what their project data is actually telling them, while spending the most time, money and resources managing an increasingly complex tech stack.
The question worth asking – and the one CIOs and their boards should be pressing hard in 2026 – is not “what AI should we buy?”. It is “do we have the right governance, data infrastructure and vendor relationships in place to deploy any advanced AI capability responsibly?”.
Getting that answer right will matter far more to long-term project outcomes than any individual tool decision. In an industry where billions are lost annually to project coordination failures and budget overruns, the next decade’s winners won’t be those adding more layers to fragmented systems. They’ll be the organisations adopting scalable digital tools, working with vendors that prioritise AI practicality over hype, all while maintaining full control of their data in the process.
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