Artificial intelligence has plenty of runway in construction, industrial and logistics as more companies seek to invest in the technology over the next two years.
That’s according to a survey released June 30 by Ferguson Partners, a global talent management and strategic advisory services firm for the real assets industry. In the second and latest edition of its AI and Automation Pulse Survey, Ferguson Partners finds that technology spending and allocation to AI and automation varies, but 88 percent of the survey participants anticipate increasing investment over the next 12 to 24 months.
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In late March, Ferguson Partners distributed the survey questionnaire to gather relevant market data on AI and automation usage. Two dozen firms of varying size, strategy and location participated in this edition of the survey. For the survey, Ferguson Partners categorized AI and automation together, while recognizing their distinctions. Automation follows defined rules to execute tasks with minimal human input. AI, while capable of driving automation, differs by learning, adapting and making data-driven decisions. Examples include machine learning, natural language processing, predictive analytics and — the big one — generative AI.
The survey cites a clear directional shift, as AI and automation are no longer niche experiments, but are becoming core to how real estate organizations operate, allocate capital, and differentiate in a competitive environment.
“Real estate has reached an AI tipping point,” Mike Cordingley, managing director at Ferguson Partners, said in a statement. “What was once a forward-looking possibility is now viewed as a necessary lever for efficiency, insight and scale. The data shows leaders are investing accordingly and pushing toward smarter, more strategic applications.”
The industrial automation market is projected to hit $395 billion by 2029, growing 10 percent annually, according to Matt Labinski, director of business development at Macrovey, a Chicago-based company that uses proprietary robotic and AI technology for logistical, industrial and manufacturing processes. That includes warehouses and, interestingly enough, the U.S. Air Force, Macrovey said in an email.
“We’re positioned right at the center of this growth with our software-first approach,” said Labinski. “Unlike competitors, our system works with any robot on the market.”
From robots in Amazon warehouses to proptech startups, AI is powering a new way of viewing and operating the industrial-construction-logistics complex of modernization issues.
“We typically use drones, but also a number of different aerial options like satellite and manned aircraft as well,” said Austin Rabine, co-founder and CEO of Site Technologies, a Chicago-based company that uses data capture methods to analyze conditions for industrial facility maintenance and construction. The drone-collected imagery is then run through the company’s AI-driven software to detect defects and optimize maintenance and capital spending.
Site Technologies uses Ph.D.-level engineers and other experts specific to the trades that it analyzes to influence, or prompt, the AI to automatically detect defects in pavements, roofs, landscaping and facades, Rabine explained.
“We stitch that together into what’s called an ortho mosaic. It’s basically a high-definition, kind of Google Earth view. Then we build two- to five-year plans on how they should spend their money across large portfolios of properties,” he said.
The company, which employs 70 people, including 15 such facility experts, has scaled data capture to analyze up to 2,000 facilities in a month. There is significant interest in Site Technologies’ objective, data-driven approach, which enhances rather than replaces expert roles, said Rabine.
Working with clients like global logistics giant Prologis, Rabine has seen a growing interest in AI-driven facility maintenance and construction — but still finds a low percentage of the industrial sector using the technology.
“We work with customers who have hundreds of millions of dollars in budget in just pavements, and they’ve historically been using their multiple consultants to go out to these sites, and they’ve never really had a clear snapshot of all of the conditions of their properties,” he said. “So this is really allowing them to make data-driven decisions, rather than going off their gut feel.”
The logistics sector is primed for AI-aided innovation, said Yosh Rozen, CEO of PartRunner, a trucking logistics company based in Mexico City and operating throughout Mexico. PartRunner uses AI to enhance operations, including pricing algorithms, customer support and fleet onboarding. AI bots are used for handling low-level functions as well for internal training and onboarding. This increases efficiency, Rozen said.
Founded in Boston in 2018, PartRunner is a marketplace connecting fleet operators with larger companies, said Rozen. The company expanded into Mexico in 2022 and fully relocated in 2024 to take advantage of what he saw as an opportunity to grow faster in that country by connecting with companies big and small.
“Mexico started growing at a much faster rate than the U.S. was and we decided to downsize the U.S. team,” Rozen said. “We actually did an asset sale in August of 2024, and I moved in September of 2024 to Mexico.”
Unlike some other proptech companies, PartRunner does not use proprietary AI in its work, Rozen said. “Essentially, we use AI bots to support different aspects of the business. I’m not saying that we use AI bots on everything that I’ll mention right now, but this is how we envision how we’ll use AI specifically: everything from pricing insights to helping our pricing algorithms. Bots will support functions like general questions, but also very high-level monitoring of the routes and live tracking.”
Additionally, AI bots are used, or will be within the next six months or so, for onboarding trucking fleets, advancing from the use of call centers and emailed documents to a more efficient automated process, said Rozen.
A longtime proponent of AI in construction, Tom Scarangello, managing principal and senior adviser at Manhattan-based engineering consultancy Thornton Tomasetti, sees a rapid and undeniable move to AI in the architecture, engineering and construction (AEC) industries.
“I think what’s interesting is that there are certain trends that are happening in AEC, construction tech, and in proptech in general,” said Scarangello. “Kind of across the board, I think it’s being driven by the incredibly rapid growth of not just AI — because AI has been around for a while — but what we’re starting to see with large language models [LLMs] and agentic AI. We first started looking into, and have been tracking this, for over a decade, but I would say it’s really accelerated in the last five years or so.”
(Agentic AI describes AI systems that are designed to autonomously make decisions and act, with the ability to pursue complex goals with limited human supervision. It brings together the flexible characteristics of LLMs with the accuracy of traditional programming.)
Scarangello is a founding member of AEC Angels, a Thornton Tomasetti initiative to identify, mentor, and invest in startups to drive innovation in the AEC industry. As such he has had a close-up view of the shift from cloud-based service as a software (SaaS) solutions to AI-enhanced hardware, noting that AI could potentially replicate and improve existing platforms.
“In the past, if you were a cloud-based SaaS company, you were kind of a darling of the industry, because it was all about if you were a product-based, more of a hardware company,” Scarangello said. “A lot of the money and the focus was going for the programs and platforms that were starting to speed up a lot of the different processes that were out there. And the products that were required, a lot more of them were much more capital intensive.
“But I think what we’re seeing now with AI and the coming wave of agentic AI is that there’s a lot of concern about how many of these [SaaS] platforms are going to be overtaken. There’s a lot of things you can do now with agentic AI and some of the large language models — including the programming that is behind some of these platforms — that could be making them a threat, and, if not free, competitive or at least readily available.”
Scarangello also stressed the importance of being curious and nimble in the rapidly evolving tech landscape.
“In time, someone else is going to build a better mousetrap using these tools that are ubiquitous now, that didn’t exist four or five years ago,” he said. “So, while I think there’s still success stories out there with SaaS-based platforms and cloud solutions, I think a lot of the attention we’re getting is toward people who are solving problems that require products and hardware in which, truthfully, AI is a really good partner, because you can maybe optimize that product faster using AI — a product to help people better manage the operations of the product. That’s a transition that’s happening in real time with the acceleration of agentic AI and large language models in general.”
Proptech investors also see the inevitability and opportunities that AI presents in AEC and industrial.
“Every startup is incorporating AI into its offerings: software, hardware, marketplaces, fintech, and more,” Raja Ghawi, a partner at Era Ventures, a venture capital firm that invests in innovation in industrial and logistics, said in an email. “Some common use cases include AI-powered contract review, data extraction and presentation through a chat interface, call center automation, and robotics. We’re seeing investor interest across the board.”
Era is particularly interested in the role of new advances in making robots cheaper and more productive, said Ghawi. “The recent advancement in LLM technology will help automate some intellectual labor. However, physical labor is the bulk of labor in industrial construction and logistics, where robots are primed to drive sizable productivity gains in these industries.”
Philip Russo can be reached at prusso@commercialobserver.com.
