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Saudi Arabia’s Construction Boom Has a Data Challenge

Construction Market Growth in KSA Has Led to Larger Volumes of Delivery Data.

Saudi Arabia’s construction sector was valued at over $70 billion in 2024 and is growing steadily, with forecasts pointing to nearly $100 billion by 2030, as Vision 2030 pushes forward huge infrastructure and development plans. But behind that momentum, there’s a quieter issue that keeps surfacing on projects: how to turn data into actionable intelligence that drives decision-making.

On paper, there’s no shortage of information. Major projects track everything, from schedule, cost, risk, procurement, quality, and progress. The problem is that it all lives in different places. Teams use different systems, define metrics in different ways and report on different timelines. So instead of getting a clear picture, leadership often ends up piecing things together manually. There’s a lot of data, but not much clarity.

This challenge is more acute in Saudi Arabia than in more established markets. Elsewhere, systems and ways of working evolved gradually. Here, everything is happening at once. Projects are scaling, organizations are expanding, governance is still taking shape and digital capabilities are being built in parallel. That combination makes it difficult to get ahead of problems before they compound.

This is where a Project Management Information System (PMIS) can help, but only if it is implemented properly. It consolidates disparate data streams, standardises definitions, and establishes a single source of truth. When done right, it gives site teams what they need day-to-day; it helps programme teams compare performance across projects; and gives leadership a clear view of where things are heading.

AI is starting to play a role here as well. It can spot patterns early, highlight anomalies and even suggest where to intervene before issues escalate. But it’s not a fix on its own. If the underlying data is inconsistent or poorly structured, AI will amplify the problem rather than solve it.

Systems only deliver value when they’re tied to clear ownership, consistent processes and decisions that actually rely on the data. That means agreeing on definitions, holding teams accountable for inputs and using the system as part of how the project is run, not just how it's reported.

Ultimately, the issue is not about collecting more data, it’s about making better use of what’s already there. For many projects, that discipline will increasingly separate the projects that succeed from those that do not.

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