AI for Sustainability in the Construction Industry

In a recent webinar episode, Distinguished Professor Fang Chen explored the opportunities for Artificial Intelligence (AI) to improve productivity and sustainability in the construction industry.

UTS academics in UTS Data Lounge with numeric data on screen

AI has the power to transform the productivity of a business, optimising assets, minimising risk and reducing costs. It can identify patterns and variances in historic or real-time data and make decisions or recommendations to engineering or construction teams.

Adoption of this technology in the construction industry has been slow to move beyond pilot programs. However there are shifts starting to take place as companies understand how the combination of AI and human skills can improve productivity and sustainability.

Global AI expert Distinguished Professor Chen recently explored applications of AI in the construction industry in a recent webinar episode, hosted by the UTS Boral Centre for Sustainable Building.

Prevent project cost overruns

Construction projects often have significant costs attached, especially for large-scale, multi-year projects. AI can develop the budget and predict cost overruns based on factors such as project size, contract type, delay/cost factors and the competence of management.

Improved design

The future of CAD is Generative Design – AI-driven design that uses machine algorithms to explore all the variations of a solution and generate design alternatives to create the optimal solution. The input could include objectives and parameters entered such as material, size, manufacturing method and costs.

Project planning

AI can make the project management process predictable. It can correct itself over time for project planning if work is not being delivered or meeting deadlines. Data can also be used for contingency planning and forecast for off-schedule projects.

Improved productivity of repetitive tasks

AI-based self-driving construction machinery can perform low-level repetitive tasks more efficiently such as pouring concrete, bricklaying, welding, demolition and painting. These autonomous robots can help to reduce labour costs or redeploy the skilled workforce to improve productivity.

Site safety

AI systems can watch what is happening on-site 24/7 through cameras, IoT devices and sensors. AI can automatically identify safety issues and report back to a central system in real-time to inform the site manager. For example, the technology can incorporate facial and object identification to highlight workers not wearing appropriate safety helmets.

AI for Labour or Equipment Shortages

AI can improve planning for the distribution of labour and machinery across sites. Sensors added to construction equipment or machinery can monitor use, geo-location and engine condition. This information can flag what teams or machinery can be redeployed to another site or require preventative maintenance.


Building managers can use AI for key building operations including energy management, comfort control and predictive maintenance. AI can monitor problems and offer solutions to prevent these issues, ultimately increasing cost savings and productivity.

Structural Health Monitoring

AI can develop predictive maintenance schedules using remote sensing and AI systems. Taking environmental and operational conditions into account the technology can identify or predict abnormal structure behaviour. This can increase productivity and extend asset life of machinery and buildings.