AI in construction - redefining what's possible

For years, construction productivity has stalled, but Al is now enhancing the skills and judgment of those who build. True adoption, however, must come from within - reshaping mindsets, processes and workflows from inside the industry, driven by its own professionals.

- Daniel Dannhofer | Owner AI Exchange | RIB Software | daniel.dannhofer@rib-software.​com|

The construction industry is at a pivotal crossroads. Demand for infrastructure is soaring, and projects have become increasingly complicated, but productivity has stagnated. Fragmented data, skills shortages and resistance to digital change have long stifled progress, leaving construction lagging behind other fields that have embraced innovation more readily. However, with the advent of AI and automation, the way we design, manage and deliver construction projects is undergoing a fundamental shift.

Tangible gains from AI adoption

AI is no longer a futuristic promise and is already driving tangible improvements. Studies suggest that AI can increase efficiency by up to 20%, reduce costs by 15%, and shorten project timelines by 30%.[1] These gains come at a crucial time, as the industry faces a potential global shortfall of $40 trillion in output by 2040.[2] Such figures highlight why AI solutions that complement human expertise, rather than replace it, are rapidly gaining traction.

Yet this expertise must be twofold - the most impactful use cases come from professionals who combine deep domain knowledge of construction with an understanding of Generative AI's capabilities. Without this blend, AI risks being underutilised or misapplied.

Building a digital foundation

Unlike many sectors that have fully digitised, construction still relies heavily on manual, often paper-based systems. As is the case with key processes that depend on scattered spreadsheets, emails and handwritten notes, AI tools need a solid digital foundation comprising well-structured and connected data to deliver meaningful insights.

Where these digital workflows are established, the benefits are already clear.

Predictive AI is being deployed to forecast material price trends, optimise resource allocation and improve scheduling precision.