What are the chances AI will take your construction job?

Workers in the construction industry with specialist skills or a high degree of responsibility are some of the least likely to see their jobs replaced by artificial intelligence and most likely to benefit from the technology, a new study has found.

A report published by international lender of last resort, the International Monetary Fund (IMF) found that while AI is likely to impact nearly 40% of all jobs around the world, those in the construction sector were on the whole more likely to find the technology complementary to their work than to be displaced by it.

The IMF analysis found that about 60% of jobs in advanced economies such as the USA are exposed to AI and half of those jobs may be negatively affected. But the technology will also help to improve productivity for skilled workers with high degrees of responsibility such as construction managers and civil engineers.

AI generated image of a robot working on a construction site. Source: Adobe Stock

Using the ISO-devised International Standard Classification of Occupations, the research ranked jobs for both their exposure to being automated using AI and for how complementary the technology could be for completing tasks.

The report found that although white collar occupations in the construction industry such as civil engineers and construction managers, which mostly fall into the ISO categories of professionals, managers, and technicians, were highly exposed to the impact of AI, they could also benefit the most from the technology, improving human efficiency.

On the other hand, blue collar construction jobs such as construction labourers, which mostly fall into the category of craft workers were far less exposed to the possibility of disruption by AI and yet stood to benefit from complementary technology even more.

IMF managing director, Kristalina Georgieva warned that the technology could deepen inequalities around the world, increasing wages among those who were able to harness the abilities of AI from those impacted by lower labour demand, lower wages and reduced hiring. She also said that those in advanced economies stood to benefit most from the technology while those in the developing world, and younger workers may find it easier to exploit opportunities than older ones.

“We are on the brink of a technological revolution that could jumpstart productivity, boost global growth and raise incomes around the world,” she said. “Yet it could also replace jobs and deepen inequality.”

The research echoes that of technologists, Mubashar Iqbal and Dimitar Raykov, who set up website WillRobotsTakeMyJob.com ranking the exposure of hundreds of specific jobs to AI disruption, following a model established by academics Benedikt Frey and Michael A. Osborne from the University of Oxford.

According to Iqbal and Raykov’s site, which lists 702 detailed occupations and attaches a score to each of them based on the model’s predicted risk level for AI disruption as well as polling data from website visitors and prediction from the US-based Bureau of Labor Statistics about growth projections.

Why is construction less exposed to AI disruption than other industries?

It found that no major roles within the construction industry scored less than three out of ten, making them less exposed to disruption than nearly 200 other jobs and professions.

The reasons for this among blue collar jobs are pretty clear. While Chat GPT and others can churn through data or generate written reports faster than a human, machines are currently far less capable of manipulating objects in 3D on sites in a state of continuous change.

Although autonomous construction equipment is regularly used in large scale mining operations, so far, the prospects of it being used on mainstream construction sites seem many years away.

Nonetheless, the research makes surprising reading with some white and blue collar jobs within the industry far more exposed to disruption than others. 

According to WillRobotsTakeMyJob.com, some of the construction industry jobs most exposed included welders, electricians’ helpers, insulation workers and crane operators.

Meanwhile those in construction least likely to be replaced by technology included construction managers, civil engineers and electricians.

Are white or blue collar construction jobs most exposed to AI disruption?

A study by McKinsey published in July 2023 predicted that demand for construction workers would increase 12% between 2022 and 2030 despite the increased use of AI technology over the period, while demand for office support workers would fall by 18% over the same period and customer service and sales jobs would decrease 13%.

For white collar workers in construction, the future looks ever more optimistic. Although researchers in general are divided over to what extent AI will disrupt skilled office jobs, even those predicting major upheaval expect the effects mostly to be felt in fields such as media, marketing, IT and law.

“The impact of gen AI alone could automate almost 10% of tasks in the US economy,” says McKinsey senior partner, Kweilin Ellingrud. “That affects all spectrums of jobs. It is much more concentrated on lower-wage jobs, which are those earning less than US$38,000. In fact, if you’re in one of those jobs, you are 14 times more likely to lose your job or need to transition to another occupation than those with wages in the higher range, above US$58,000 for example.”

Construction jobs ranking from WillRobotsTakeMyJob.com:

Source: WillRobotsTakeMyJob.com

*Risk levels are calculated based on the abilities, knowledge, skills and activities required in order to do each job provided by US government sponsored online database O*Net. The higher it is, the more at risk each occupation is to automation. Researchers calculate each score by inputting the different attributes of each occupation into a machine learning system which trains a model which can then be used to provide a score. Scores are then verified by comparing them to the site’s user votes. 

**Voted risk levels are compiled from feedback from more than 100,000 votes from the website’s users to date.

***Job scores are calculated using a combination of the website’s calculated risk levels, its voted risk levels and some additional information from the Bureau of Labor Statistics.