AI In Construction, Two Years On

In March 2023, I asked whether one of the world’s oldest industries could learn new tricks. Construction had long lagged behind in digital transformation. Artificial intelligence, then making its mainstream debut via tools like ChatGPT, was viewed with a mix of curiosity and caution by the sector. The hesitation was understandable. Fragmented workflows, legacy systems, and analogue processes made innovation feel distant, even risky.

Two years on, the debate has moved on. It’s no longer about whether AI has a place in construction, but how to apply it in ways that deliver real value.

While the sector still trails behind industries like finance and manufacturing in overall adoption, AI is already solving some of construction’s most persistent challenges – from cost inflation and labour shortages to stagnant productivity and escalating sustainability pressures. With Big Tech earmarking over $300 billion for AI investment this year, and UK adoption creeping beyond 12%, the old dog is not only learning new tricks – it’s beginning to use them.

From Theory to Action

In 2023, most firms were in the exploratory phase. Today, AI is being applied across the project lifecycle, with measurable results.

Safety remains one of the clearest use cases. In 2023/24, 138 workers were killed in work-related accidents in Great Britain, with construction accounting for 51 of those deaths, or in percentage terms, 37% of the total. The majority resulted from falls from height, being struck by moving vehicles, or contact with moving objects, which together made up around 70% of fatalities. According to the Health and Safety Executive, 95% of those killed were men, and more than a third were aged 60 or older, highlighting the sector’s persistent exposure to physical risk, particularly among an ageing workforce.

AI-enabled safety systems are now being deployed to monitor site conditions in real time using video feeds, environmental sensors, and equipment tracking. These tools can detect and flag hazards before they escalate, enabling a shift from reactive compliance to proactive prevention.

On the operational side, AI is transforming procurement and project controls. US-based startup Field Materials, for example, uses AI to streamline invoice and quote processing. With $10.5 million in Series A funding, it now handles over $360 million in purchases across 27 states. Contractors using the platform report time savings of over 90%, freeing teams to focus on strategic sourcing rather than admin.

AI is also unlocking new approaches to sustainability, a top priority for over 85% of business leaders. As construction firms confront mounting pressure to decarbonise, digital tools are proving essential. AI-powered predictive modelling and real-time analytics are helping teams reduce rework, minimise material waste, and optimise the use of energy and equipment. By offering a holistic, data-driven view of the full project lifecycle – including carbon scope management and material traceability – AI empowers firms to make environmentally responsible decisions that are also cost-effective. From automating emissions tracking to enhancing biodiversity assessments through ecological data analysis, AI is turning sustainability from an aspiration into a measurable, operational discipline. In a sector responsible for over 37% of global emissions, these small step changes represent major progress toward net-zero construction.

The Data Dilemma

Despite this momentum, many firms remain stalled by one key issue: data. AI systems rely on structured, consistent, and accessible inputs. Too often, project information remains buried in PDFs, spreadsheets, or even paper documents.

Here, incremental solutions are proving effective. Emerging platforms are now helping standardise commercial and financial data, enabling firms to shift from retrospective reporting to predictive forecasting, without the need to overhaul entire tech stacks.

The Rise of Multimodal and Agentic AI

Beyond structured data, the next step is enabling AI to interpret the visual and physical realities of construction projects. Early AI focused on text, but the technology is now multimodal – analysing images, video, 3D scans, digital twins, photogrammetry, and LiDAR data.

Reality capture tools, such as drone-based scanning and laser imaging, are enabling real-time comparisons between as-designed and as-built models, reducing rework and improving coordination. When integrated with BIM, they offer a dynamic view of project conditions, updated continuously and remotely.

These systems are increasingly powered by agentic AI – autonomous tools that can interpret data and act on it. Built on architectures like hierarchical reinforcement learning, they improve through iteration and reflection, supporting complex automation across procurement, risk management, and logistics.

Gen Z’s Role in the Transition

Attracting the next generation of talent means redefining what a career in construction looks like. According to Deloitte’s 2025 Gen Z and Millennial Survey, these cohorts prioritise learning, well-being, and purpose, often above climbing the corporate ladder. They’re not disinterested in work; they’re focused on meaningful progress and roles that reflect their values. Gen Z’s fluency in digital tools and comfort with AI make them natural adopters of the technologies now transforming the industry.

Tapping into that potential is no longer optional. By 2035, the EU construction sector is expected to face a shortfall of 4.2 million workers, driven by retirements and attrition. Without deliberate succession planning and skills transfer, decades of on-site expertise risk being lost. The firms that succeed will be those that treat Gen Z not just as digital natives, but as future leaders – embedding them early into project teams, investing in cross-generational learning, and creating environments where technology and experience reinforce one another.

Looking Ahead

AI won’t transform construction overnight, and it doesn’t need to. The most effective adopters are moving steadily, prioritising clean data, aligning internal systems, and deploying technologies where the use case is proven. The global AI-in-construction market is expected to exceed $20 billion by 2034, but its real value lies less in scale than in outcomes: more informed decisions, better project visibility, and greater resilience across delivery models.

The aim shouldn’t be to replace human expertise, but to strengthen it. When used well, AI supports teams with the tools to work more safely, efficiently, and sustainably. As adoption grows, the firms that will lead are those combining digital tools with practical insight, treating AI not as a cure-all solution, but as part of a broader strategy to improve performance, manage complexity, and build for the long run.