AI in Construction: Real Value or Just Hype?

AI is having a moment. It’s the latest buzzword sweeping across industries, and construction is being pulled into the hype.

You only need to walk through an office to see it: ChatGPT is open on half the screens. A year ago, people would minimise the tab when they heard you coming. Now it’s being embraced as the future of productivity.

From generative design to automated document review and predictive planning, the construction industry is eager to show how AI can transform how we work. But as with any trend, it is worth asking a simple question:

Are we pursuing AI because it delivers real value, or simply because it’s fashionable?

AI ≠ Just ChatGPT

One common misconception is that AI begins and ends with tools like ChatGPT. These large language models can be incredibly helpful, summarising documents, writing reports and even answering technical questions. But this is only one small part of what AI actually is.

AI is a toolset, not just a chatbot.

It is a broader toolkit that includes prediction, classification, pattern recognition, and recommendation engines. Some models can analyse historic project data to forecast programme delays. Others can support quality inspections using site photos and vision models. Some even help identify trends across projects and generate suggestions based on lessons learned.

The more tailored the application, the more value it is likely to bring. And the more deeply integrated it is into real project workflows, the more impactful it becomes.

Don’t Let the Hype Fool You

The problem? Everyone wants to say their software uses AI. But often what’s marketed as AI is little more than automated rules or simple data filters. And even when genuine AI is used, it’s sometimes bolted on with no clear value.

Especially in high-stakes projects, overreliance on AI can lead to critical errors. The tech is good at confidence, even when it’s wrong. That makes it important to approach AI outputs with the same scrutiny you’d apply to any other information source.

The Real Opportunity: Big Data, Better Decisions

If AI has a true superpower in construction, it is scale.

Major infrastructure and nuclear projects generate huge volumes of data. Models, schedules, cost plans, reports, RFIs, change logs, and more all add up to something no human team can reasonably analyse in full. But hidden in that complexity are patterns that could inform better decisions, earlier interventions, and smoother project delivery.

This is where AI shines. It offers a way to process that data faster, surface insights earlier, and support more confident decisions.

This is not just a theoretical benefit. It is already happening in other industries. But to unlock that value in construction, we need to rethink how our data is structured and delivered. It must be machine-readable, not just human-friendly.

From Human-Friendly to AI-Readable

BIM managers have traditionally focused on producing models and documents that people could understand with their eyes. Think 2D drawings, PDF reports, visual mark-ups and graphically rich 3D models. But machines do not think like people. They need information that is structured, labelled, and consistently organised.

To truly benefit from AI, we need to make our data AI-readable. This means thinking in terms of structure, standardisation, and context.

Drawings are great for humans but almost useless for AI.

To unlock the value of machine learning, we need structured data, consistent naming, and clear relationships between components.

This shift in thinking will redefine how we build digital information in the coming years.

AI Should Inform, Not Decide

AI will not plan your project for you. But it should help you plan it better.

It can show you how a previous one performed, where delays occurred, and what factors had the greatest impact.

Imagine feeding in cost, productivity, and programme data from a recently completed project, alongside a set of key differences between that and your next one. The AI won’t give you a perfect answer, but it will highlight patterns, flag risks, and suggest areas to focus on. That gives planners and decision-makers a clearer, more informed starting point.

This is where AI adds the most value, not by replacing human judgment, but by delivering deeper insight faster.

AI should support human decisions, not replace them.

It gives experienced professionals better information at the moment they need it, helping them make decisions with greater confidence.

Final Thought

Not every problem needs AI. But some problems become much easier to solve with it.

The challenge is cutting through the hype to find the use cases that genuinely add value. That means leading with the need, not the technology. When AI is used with purpose, it’s not a replacement for good judgement. It’s a force multiplier for it.

That’s what construction should aim for. Insight over instinct. Decisions backed by data. And tools that make smart people even more effective.