by Carlo Cattero
About 7 percent of global workforce is employed in building sector. The total value of spending in branch is 10 trillion dollars per annum (McKinsey, 2017).
Many other sector have used AI and other innovative technologies to increase their productivity; in contrast building sector has increased little or nothing in comparison.
Global building sector has grown by only 1% per year over the past few decades. Even worse if we compare this with a growth rate of 3.6 percent in the industrial production sector and 2.8 percent of the entire world economy. Productivity, or total economic production per worker, has remained substantially unchanged in construction. In comparison, it has grown by 1500 percent in retail, manufacturing and agriculture since 1945. One of principal reasons of this phenomenon is due to the fact that construction represent one of the most under-digitized industries in the world, as well as very slow in the adoption of new technologies (McKinsey, 2017).
In general, the adoption of a new technology can be discouraging for teamwork, but the Machine Learning and AI are helping to make workplaces more efficient with significant saving in the process. AI solutions that have proved disruptive in other sectors, however, are slowly starting to emerge in the construction sector as well.
But what are Machine Learning and Artificial Intelligence?
Artificial Intelligence is an aggregative term to describe when a machine duplicates some human cognitive functions, such as a problem solving, pattern recognition or learning. Machine Learning is a subset of AI which uses statistical techniques to give IT systems the ability to “learn” from data, without being explicitly programmed. A machine improves in understanding and providing insights when it is fed with more data.
McKinsey, a multinational strategic consultant, predicts that the spread of AI in construction sector will be modest in the near future (McKinsey, 2018), however, a change is on the horizon. The subjects involved in the sector, in fact, can no longer afford to see the AI as relevant only if it refers to other sectors. Engineering and construction will have to get in line with AI’s methods and applications and this is the only way to deal with the increasingly frequent competitors entering the market and to remain competitive.
Machine Learning and Artificial Intelligence in a new paradigm of smart construction
Potential application of machine learning and AI in building are extended: the request for information, the snag lists and the orders of variations – just to list a few – are standard and often repetitive operations in the sector and could be the first to benefit of the use of these innovative schemes. The use of machine learning systems, in fact, can be compared to having an intelligent assistant able to dispose of this enormous amount of data very quickly and in case warns the project managers of the critical aspects on which their attention is required. Several applications already use the AI in this way and the benefits range from the trivial filtering of spam emails to advanced monitoring of security and construction processes.
The future of AI in construction
Robotics, AI and Internet of Things can reduce construction costs by up to 20 percent. Designers can wear virtual reality glasses and send mini robots into buildings under construction. Robots use cameras to keep track of work progress. Artificial intelligence is used to plan passages of electric and hydraulic systems in modern buildings (Building Information Modeling BIM). Construction companies already today use AI to develop safety, planning and control systems on construction sites, where AI collects and evaluates real-time interactions of workers, equipements and materials on site and alerts teams in case of problems safety, construction errors or scarce productivity.
Despite the previsions of enormous job losses, it is very unlikely that AI will replace the human labor force, on the contrary, it will alter the business models in the construction sector, reduce costly errors, site accidents and make more efficient construction operations. Great leaders of construction world should be the first to trace the way – and, in part, they are already doing it especially in Asia, Australia and partly in Europe, while incredibly the USA is far behind in this area (McKinsey, 2017) – and prioritize investments based on areas where AI can have the greatest impact on productivity in the sector. Those who will move first in this area (early adopters) will define the direction and will be able to take advantage of it both in the short and in the long term. It has been calculated, in fact, that the production gap of the entire system compared to other sectors is worth 1.6 trillion dollars, which corresponds to half of the world’s infrastructural needs and to a 2 percent increase in the planet’s GDP.
In conclusion, developing the construction sector according to logics similar to those of industrial production, from which it has been held detached for too long, investing in R&D and identifying new construction logic for standard buildings in order to increase productivity, represents a challenge to which the sector must can no longer afford to escape.