Where AI adds value on live construction programmes.

Artificial intelligence is attracting significant attention across the construction industry. Some of that attention is warranted. Much of it, however, risks oversimplifying the realities of live projects.

The most useful applications of AI today are not about prediction for its own sake, or replacing professional expertise. They are about supporting better engineering decisions in environments defined by uncertainty, complexity and constant change.

From our experience on live programmes, AI delivers the greatest value when it is practical, evidence-led and grounded in how projects actually behave.

Seeing pressure build earlier

Traditional programme controls are often backward-looking. By the time delay becomes visible in reports, options to mitigate are already narrowing.

AI changes this by analysing how programmes perform over time, not just how they are planned to perform. Patterns such as repeated slippage, float erosion and persistent underperformance can be identified earlier, providing a clearer picture of where pressure is building across the programme.

This earlier visibility does not remove risk but it does give teams more time, better evidence and a stronger basis for decision-making.

Shifting effort away from low-value tasks

Despite advances in digital delivery, project teams still spend a disproportionate amount of time maintaining data, updating spreadsheets and producing routine reports.

AI can help automate much of this work, reducing the administrative burden and improving consistency in reporting. More importantly, it allows planners and engineers to redirect their effort towards analysis, judgement and collaboration, where their expertise has the greatest impact.

Turning lessons learned into live insight

The industry is good at documenting lessons learned. It is less effective at applying them in real time.

AI offers a way to close that gap by learning from historic programme behaviour, using evidence from previous projects to highlight where similar scopes of work have tended to drift, compress or fail to recover.

This approach moves learning from a retrospective exercise into something that can actively inform planning, risk discussions and mitigation strategies on live projects.

Augmenting judgement, not automating decisions

AI does not remove uncertainty from complex projects, nor should it attempt to. Construction outcomes are shaped by human judgement, context and trade-offs that cannot be fully automated.

The most effective use of AI is as a decision-support tool, one that enhances professional judgement by improving visibility, strengthening evidence and reducing noise.

At Strata, our position is clear: AI works best when it supports engineering judgement, not when it tries to replace it. As the industry continues to adopt new technologies, the focus must remain on practical application and real value on live projects.

That is where AI moves from promise to impact.

If you’d like to learn more about how we’re applying AI to support better engineering decisions on live projects, please get in touch: info@stratadigital.io