Image courtesy of Earthcam, Inc.
Construction has already adopted artificial intelligence for use cases such as noticing safety violations or equipment placement in reality captures.
Kaplanoglu
The construction industry is facing challenges due to rapid growth, labor shortages, a retiring workforce, productivity declines, increased complexity, and safety performance challenges. Many people are seeking solutions to these issues through artificial intelligence.
You may say that we have seen this before: the workforce will adapt, and AI is all hype anyway. This time, it’s different, and you need to look beyond the hype.
Speed of Technology Advancement
Let’s take a look at how fast technology is improving. In the design services sector, the use of image generators is gaining traction for early-stage design. It takes weeks for a new and improved image-generation model to become available. Three weeks after Google’s revolutionary Nano banana model, ByteDance Seedream 4.0 released a superior model. The AI models are context-aware; you can request a change to an image and see it update in real time within minutes. The vast amount of research, funding, and breakthroughs is accelerating the pace of advancement.
Availability and Scaled Adoption
We are experiencing change differently because anyone can access AI online. In the past, it took decades to implement technologies. This time, AI’s adoption is much faster than that of any other technology due to its widespread availability. ChatGPT has more queries per day than Google Search reached in its first decade. OpenAI reported that it had over 700 million weekly active users and more than 3 billion messages sent daily as of August 2025.
Efficiency Gains
It hasn’t been easy to measure the impact on the construction workforce. Last summer, we started hearing that companies were not replacing employees who left or retired. Now we have the proof that in 2025, there were 30% fewer college graduate hires across all industries. While the overall unemployment rate was 4.3%, the rate for recent college graduates was 6.5%, the highest in over a decade. Some industries are already changing fast. Data show that more than a quarter of all computer programming jobs have disappeared in the past two years, and employment is projected to decline by 10% in that business over the next decade.
Naysayers will point to an MIT study that found that 95% of AI implementations fail. The study focused solely on generative AI, the kind that necessarily creates new code or other content, and it had a relatively small sample size. I agree with one of the study’s conclusions, which showed that change management was a key issue. The results align with my own observations: successful AI deployments either use AI-embedded products or don’t do it alone and partner with others. In my opinion, buy AND partner are both the right choices.
Some studies also show that people often don’t say they use AI, as they believe it diminishes the value of their work, even when they really are using it. At the personal level, people report significant productivity gains, but we struggle to measure generative AI’s impact on business outcomes. I believe that, in isolation, generative AI is useful, but it really becomes powerful when it’s working with AI agents designed to perform specific workflow tasks. We will see more studies measuring the positive impact of use cases that leverage generative AI and AI agents working together.
AI encompasses a range of technologies, including machine learning, deep learning, computer vision, general AI, multimodal AI, and AI agents. For public education, generative AI’s abilities and impact are generalized for AI adoption, as it’s the most visible and accessible.
Like any technology, generative AI can be successfully deployed when it’s well managed. IKEA implemented a call center bot without laying off employees. They reskilled 70% of them to become design advisors, and the rest continue to provide call center support. By reskilling call center agents, they realized additional billions in revenue from upselling their products while providing design services. The bot use case can be applied in our industry by providing information and guidance for our workforce’s day-to-day operations. It’s also useful to have employees remaining in customer service call centers for every problem a call center bot cannot solely solve.
I am confident that the efficiency gains will become more measurable as the technology and adoption continue to evolve, and we reskill our workforce.
Now that you have a perspective on the current state of AI, let’s take a look at the potential impact of AI on the construction business in the next decade.
Jobs (Not Steve)
I believe construction jobs will become more attractive as jobs in other industries become automated.
Due to the physical nature of the work and its complexity, I predict that the automation of our industry will be delayed compared to other industries, and more people seeking employment will transition into our industry.
Workload Management
AI infrastructure companies are announcing investments totaling hundreds of billions of dollars weekly. We can’t keep up with announcements. Some believe we are experiencing a bubble and work will decline in 3-5 years. I think the opposite: the work will continue to grow as the AI infrastructure we are building today will need to be upgraded as technology advances. We will also be building new infrastructure, such as roads, schools, and hospitals, to enable gains from the technology advances.
Staying Capable
We will also see shifts in how work is being performed. The ability to do more with fewer people for engineering, design, and construction will help smaller businesses to compete with larger firms. Companies will have fewer people with specialized skills.
Construction labor is a case in point. There has been significant improvement in robotics in the last 12 months. Construction has been listed at the bottom of the AI impact list due to its physical nature and complexity. Still, I see a clearer path for higher levels of robotic adoption in the industry. For construction tasks that require physical abilities, advancements in robotics will help us augment the labor force (not replace it) and bridge the gaps. Adoption of automation on large, remote projects is already pushing productivity forward. This change is likely to occur a decade from now in today’s world.
Making Business Sense
Eventually, construction business models will change. We will start measuring value, rather than racing to the bottom. We will charge based on the end value of the services, not by the hour.
I believe these changes will happen in the next decade. The good news is that other industries will transform rapidly, giving the construction industry more time to react and adapt. We will also have two different speeds. Due to digital workflows, architecture and engineering will be transformed faster than site construction, which requires physical workflows.
We have to keep our eyes on the ball.
Burcin Kaplanoglu is a construction technologist and AI expert. He is active in industry organizations and on LinkedIn where he provides educational content related to technology, innovation, robotics, AI and industry use cases.