Artificial intelligence: The future of construction


Artificial intelligence: The future of construction

According to McKinsey, AI is the next frontier for construction technology. Without a doubt, the construction industry has still a long way to go before we can claim with confidence that artificial intelligence solutions have been properly implemented in the sector.

The good news is that construction is an industry with tremendous potential. The total worth of the sector is estimated at $10 trillion per year, while the productivity gap due to the lack of digitalisation in the industry is calculated to $1.6 trillion.

An Introduction to the research

There is no doubt that AI applications can boost efficiency on site and raise the bar for the industry in terms of productivity, risk reduction and overall construction performance. Of course, this won’t be an easy journey for the industry given the mistrust on contractual relations and the biggest enemy of all which is the resistance to change.

Nonetheless, artificial intelligence can function as the fuel for a meaningful change in how stakeholders in construction design, collaborate and operate.

The Need for Artificial Intelligence in Construction

Now that we have a better understanding of the research focus, it is time to examine why artificial intelligence is deemed to be necessary for the construction industry.

Shrinking workforce

Skilled labor shortage is one of the most crucial problems for the construction industry on a global scale. This element is extremely important when we refer to labour-intensive industries, such as construction.

AI could offer solid solutions to this problem through the automation of labour and time-intensive tasks such as programme creation, cost estimation, resource management, health and safety management and many more.

Low-profit margins

Low-profit margins have always had been a serious source of pain for construction compared to the other industries.

In short, the most noteworthy factors which have led to this problematic situation could be summarised to the next five:

  • Competitive tendering
  • High bidding cost to return ratio
  • Increased costs due to sterling decline
  • Low productivity
  • Poor risk management

The implementation of artificial intelligence technologies to the construction process could eliminate many of these factors and adding much more accuracy on the way people in construction work and build.

Risk management

We have already mentioned risk management as one of the factors that lead to low-profit margins. Nevertheless, it’s not the only type of risk management that AI could potentially provide significant help with.

Risk management as an aspect of construction management is also something that needs special attention. There are simply so many parameters that should be taken into serious consideration in a construction project and an effective risk management system could make a real difference there.

More analytically, artificial intelligence could function as the objective source of truth for the industry which would eliminate any optimism bias and provide valuable data which can show the way for future projects.


Last but not least, the issue of sustainability. The Global Status Report 2017 (Abergel, T. Dean, B. & Dula, J., p.14) reveals that the construction industry was responsible for 11{b70d0765ca39f2596dbc297ea355d977781cb3f8756e7593c30ded776020f4ad} percent of global C02 emissions in 2015, and combined with the 26{b70d0765ca39f2596dbc297ea355d977781cb3f8756e7593c30ded776020f4ad} of emissions generated by the buildings themselves, leads to the built environment contributing to 37{b70d0765ca39f2596dbc297ea355d977781cb3f8756e7593c30ded776020f4ad} of global emissions.

artificial intelligence - sustainability

Fig. 1: CO2 emissions by sector

That is a strong wake-up call for the construction sector. A substantial paradigm shift on the way all stakeholders in construction work is required. With the help of AI, smart buildings which are resource and energy efficient both in terms of construction and use later on could become the norm.

Such an approach could be beneficial both for the construction industry and the people who work or live in the buildings.

The Challenges Facing AI Implementation in Construction

Despite the various problems that construction is currently facing, the successful implementation of AI technologies is not expected to be easy. There is a number of obstacles that the industry will have to overcome:


Mistrust on contractual relationships and power of habit are two of the most crucial parameters that should be taken into consideration when it comes to AI implementation in construction.

It is expected that digital technologies will come across heavy scepticism until it is proven that they can provide value. Of course, this scepticism isn’t only the result of resistance to something new.

The fact that there haven’t been so many AI success stories in construction yet plays also a substantial role in that direction.

To make matters worse, it seems that at the moment there is a big disconnection between the board room and the construction site when it comes to implementing these new technologies.

On the one hand, the implementation of artificial intelligence in construction will come from the top down but on the other hand, it is vital that people who are going to use this technology on site have a good understanding of its benefits. Only then, the full-scale implementation will be a success.

Ageing workforce

The age of the workforce is one more challenge that can hinder the implementation of AI in construction. The construction industry faces serious problems to recruit young workers.

This can be a strong indication that construction has a lot of work to do when it comes to its profile. The good news is that the rise of digital technologies can help the sector redefining itself and turn to a promising destination for an ambitious and tech-savvy workforce.


Without a doubt, upfront costs can also be a challenge for the spreading of artificial intelligence technology in the construction industry. This obstacle can be even higher if we take into account the fact that this type of technology is still at very early stages and hasn’t entirely proven its value yet.

In the long term, though, things will get better as this type of technology will be tested on a larger scale and there will be more tangible results of its use in the industry.

The training of the project team on these technologies can also play a role in raising the cost of AI implementation. It’s not all bad though. As pointed out by McKinsey and Company, the investment in R&D has started to increase significantly in the course of the last years which help decisively in reducing the digital adoption cost in construction.

Data collaboration

Construction is producing a vast amount of data which either goes to waste or isn’t used properly. To great extent, that is the result of working in a highly fragmented supply chain and by extension industry.

Many stakeholders in construction continue to work in silos which makes things much tougher when it comes to extracting valuable project knowledge from the available data. That being said, minimising delays, keeping the budget under control and improving the quality of the countless processes becomes much more challenging when there is no data you can use.


As technology progresses, it becomes more and more difficult for legislators to keep up and make sure that the right legal framework is in place. Especially if we take into account the different rules and regulations that might apply to different countries things can get even more confusing.

In many cases, this legal gap may lead to costly project disputes, a lot of confusion and unnecessary project delays and budget overruns.

Confidence in using technology

One of the first and highly encouraging findings had to do with the confidence of construction professionals in using technology.

Fig. 2: Respondents confidence in using technology

As you can see from the diagram above, nearly 66{b70d0765ca39f2596dbc297ea355d977781cb3f8756e7593c30ded776020f4ad} of the participants declared that their confidence level in using technology is 5/5, while 26.8{b70d0765ca39f2596dbc297ea355d977781cb3f8756e7593c30ded776020f4ad} chose 4/5 and 7.3{b70d0765ca39f2596dbc297ea355d977781cb3f8756e7593c30ded776020f4ad} replied with 3/5. This result shows that there are many in the industry who are capable of handling the arrival of digital technologies and have potentially a positive attitude toward them.

This might also, of course, be related to their age given the fact that 68.3{b70d0765ca39f2596dbc297ea355d977781cb3f8756e7593c30ded776020f4ad} of them were between 25 and 49 years old. That is a strong indication for where the industry might be heading within the next two decades.

Time spent on repetitive tasks

Another factor which in the long run may act as a catalyst for change in construction is the need for automation. One way to measure this is by calculating the time spent by construction professionals on non-technical and/or repetitive tasks.

Fig. 3: Number of hours respondents spend doing repetitive tasks

Based on the findings of the survey, we can see that on average a person will dedicate 2.16 hours per day on repetitive tasks which on a yearly basis accounts for 564 hours.

“If we use Viechnicki and Eggers (2017) upper estimate of how much time AI can save us (30{b70d0765ca39f2596dbc297ea355d977781cb3f8756e7593c30ded776020f4ad}), we can calculate that AI could potentially reduce each worker’s yearly time spent on repetitive tasks by 188 hours.

Resistance to change: A challenge for AI or not?

Another interesting and very contradicting finding came up during the examination of the company’s culture. The vast majority of the survey participants replied that 82.9{b70d0765ca39f2596dbc297ea355d977781cb3f8756e7593c30ded776020f4ad} of the people working in the organisation are open to change and new methods of working.

Fig. 4: Respondents opinions of the culture in their organisation

What’s interesting, though, is that later at the same research they identify resistance to change as one of the biggest problems for the sector. This is an emphatic indication that the industry is highly disconnected from the people working in it.

Fig. 5: Bar graph highlighting the challenges that AI will face in construction

The impact of AI in construction

Could artificial intelligence be a disruptive force for construction? That is a question which received mixed responses as you can see below:

Fig. 6: Pie chart representing respondents opinion of if AI will disrupt the construction industry

What is more interesting, though, is examining the various areas within construction where the survey participants believe that AI can make a difference.

AI in construction

Fig. 7: Bar graph showing areas respondents thought that AI could benefit construction

Administrative tasks and general efficiency seem to be the areas which will be benefited the most according to the respondents. That’s not a big surprise if we consider that the first solid step of AI in construction is expected to be in eliminating repetitive tasks that drain a lot of time and energy.

Risk reduction, cost, and quality are coming after repetitive and administrative tasks as the areas where artificial intelligence could have a very positive impact on the construction industry.

The time frame for the advent of AI in construction

How soon will AI be meaningfully implemented in the construction industry? That’s really hard to tell but it’s very interesting to see what people from the industry think on the topic.

As shown by the following numbers, the construction industry seems to be sceptical when it comes to when the sector will be ready to fully leverage AI technologies.

Fig. 8: Pie chart representing a time frame when respondents believe AI will become meaningfully implemented in construction

More specifically, 29.3{b70d0765ca39f2596dbc297ea355d977781cb3f8756e7593c30ded776020f4ad} of the respondents believe that AI won’t be successfully implemented in construction for 15+ years, while 22{b70d0765ca39f2596dbc297ea355d977781cb3f8756e7593c30ded776020f4ad} considers a period of 10-15 years as a realistic time frame for it.

These results can be worrying because they suggest that the industry isn’t well informed about the potential of AI in construction. There are already some promising examples of meaningful AI implementation in the industry (eg. Smartvidio, Volvo Density Direct, and ALICE) which haven’t attracted yet the attention they deserve.

The lack of discussion with regards to AI implementation in construction can be also verified by the following pie chart which depicts how many of the respondents are aware of any artificial intelligence systems being implemented within their organisation.

Fig. 9: Pie chart indicating if respondents were aware of any AI systems their organisation is using

Only 22{b70d0765ca39f2596dbc297ea355d977781cb3f8756e7593c30ded776020f4ad} of them gave a positive response to this question which suggests that they either aren’t well-informed or that their organisation isn’t actively working on AI at the time being. Regardless of what may be the right answer that’s a statistic that the construction industry needs to take into account moving forward.

Final thoughts

All in all, this greatly informative research by Conor Gantly highlights that the construction industry is ready for a meaningful digital change. AI has the power to bring that change into construction but there are many obstacles that need to be overcome first before we can claim with confidence that the industry has managed to fully leverage AI.

It is expected to be a long and challenging journey for the entire sector but with the right plan and an open mind toward new technologies the digitalisation of construction can be closer than many might think.