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Notorious for slow technology adoption and inefficiency, homebuilders are not at the forefront of artificial intelligence.
That also means there is a ripe opportunity for AI to drive smarter decision-making and workforce efficiency, which will also drive innovation and help future-proof organizations.
“People think it’s a very technical concept, part of it is art and part of it is science, but actually it’s all about practice,” says Jeff Willert, director of data science at Schneider Electric’s SE consulting solutions. “It’s about finding the right data, the right knowledge base and the right subject matter expertise and putting that into the equation so that tools provide the right guidance.”
Willert says he has been building his expertise with his team, where they competed internally in a shark tank-like challenge for ideas and are now implementing solutions that have turned month-long processes into a few days.
He recognizes the value of collaboration between humans and machines, where humans do not always have to be displaced. AI can speed up processes, but it must be able to rely on the more than twenty years of expertise that the organization has built up.
AI for home builders
The residential construction sector is made up of many small and medium-sized businesses that can take a similar approach to large organizations.
“Businesses of all sizes can start experimenting with AI tools like ChatGPT, Gemini or Microsoft Copilot,” said Willert. “In some ways, small businesses may even have an advantage over larger enterprises. Large organizations often experience slower adoption due to strict IT policies and lengthy procurement processes. Small businesses can typically move more quickly and adapt to new technologies without too many bureaucratic hurdles.”
Many small businesses will not have in-house expertise, which is valuable because applying AI properly requires a deep understanding of the business. More and more consultants are beginning to offer strategic services to help analyze opportunities and develop solutions.
For someone specifically in housing, Willert suggests a starting point: identify which non-physical tasks are the most expensive or time-consuming. For example, can data-driven decision making improve project timelines and increase customer satisfaction? Are there opportunities to optimize deliveries and reduce costs? Can automating record keeping, budgeting, purchasing or other back-office functions save labor costs?
“For one [building product] Whether it’s a retailer or a manufacturer, I would take a similar approach,” Willert added. “The focus would be on identifying where time or money is being lost due to slow, tedious or outdated processes. Manufacturers could benefit from advanced measurements and predictive maintenance. By monitoring equipment for energy consumption, temperature and vibration it is possible to detect when maintenance is required before a failure occurs, which can save significant costs and downtime.”
Michael Anschel is director at OA Design+Construction and has been in the industry for decades and is now developing and sharing its own expertise in AI. He agrees that AI can enable smaller companies to be more competitive in a larger landscape.
A challenge for those involved in building and remodeling homes is marketing and promotion. Anschel says agentic AI can build a website for a new or existing housing company in less than 15 minutes. This new playing field can automate many office functions.
“AI can understand projects better than a builder,” says Anschel. “Imagine having drawings, specifications, project management software and planning all in an AI tool that can take off very accurately, from the number of fasteners to the number of drywall sheets and all the other pieces on a complex scale.”
AI can identify if something is out of order and suggest an alternative order. It can provide estimates if linked to a database, and it helps fill in the blanks. It can also provide accurate, real-time information about a project.
“The advantage for a builder is that they can query the system and the LLM can produce the response without calling a designer or production manager,” he added. “Tasks that only take time, that can be automated and that can relieve the burden on the construction team.”
Shae Wilson is director of brand and marketing at the construction management platform Constructionxact and says it uses AI-powered features that learn from thousands of estimates over 15 years.
“The builders and professionals who use our platform save up to 80% of the time they would normally spend on some of these processes and can spend longer on site,” she says. “These types of efficiencies are exactly what we need to catalyze more home construction. It’s an exciting time for builders to turn to technology partners and get more out of the processes they’ve had in place for years.”
Now there are also agent tools that can negotiate on behalf of a professional.
“A super exciting part is that AI agents will negotiate and collaborate with each other,” Anschel said. “A builder looking to source materials doesn’t want to have to call hundreds of lumber yards or distributors. He can tell an agent AI what he’s looking for, and it will scour the agent’s web or internet and negotiate with other agent AIs for the best deal on what he has set up – price, timeline, product, availability, quality, quality. Depending on the authority you give him, he can complete the entire transaction for you, or he can bring it back for you to approve.”
There is also the option to perform heavier tasks, such as change orders. AI can monitor a project as it happens. When it notices a change in schedule, it can generate a change order and manage the process.
“Think of every task we hate – that’s where the tools reduce friction and make us more profitable,” Anschel said.
Replacing the local feeling of home builders
AI must be implemented effectively and not haphazardly replace people or processes.
MIT recently published a study, State of AI in Business 2025that reports a waste of billions of dollars invested in AI pilots that fail to deliver results, but not because of the tool, but because of a phenomenon called the GenAI Divide. The study looked at 300 implementations, most of which failed due to exposed workflows, lack of contextual learning, and poor alignment with daily operations.
Willert did those experiments at SE and has now named AI agents that appear in organizational charts.
“The agents were running at 50% accuracy at launch, 90% after a month and now 99.9%,” says his colleague Steve Wilhite, executive vice president at SE Advisory. “The value creation is amazing. As a leader, I didn’t want to leave the decision-making to an agent with 56% accuracy. But with 99.9% accuracy, I know the agent is taking care of it.”
Much of the construction industry is mired in fear of losing the personal connection that drives their business.
“The business world today is both global and local,” says Willert. “Deploying AI is not about replacing the expertise of a local company, but about making that expertise more accessible. The effectiveness of AI depends on the people building it and the context provided to the system. While I am not a construction expert, I think it is important to ask whether an AI tool at a major retailer understands the user’s local context. Local building codes and material preferences can significantly influence its recommendations.”
He adds that AI should perform routine tasks, while experts should refine things and add value where it matters most.
Homebuilders’ need for sustainability
While AI is a welcome solution to create efficiency, it drives up energy consumption and energy costs.
Organizations should consider where it adds value, but first understand the trade-offs.
Google published a technical paper that measured the environmental impact of its Gemini tool and its activities. It was estimated that the average Gemini Apps text prompt consumes energy equivalent to watching TV for less than nine seconds. In addition, the systems are run more efficiently and even more than 33 times per year, while providing higher quality input.
“Frugal AI is our term at SE – AI where AI makes sense,” said Willert. “We place fully autonomous AI agents at the top because they absorb the most carbon. Moreover, we recognize that this technology allows us to solve problems that were previously insoluble or would take months. And in doing so, we could even accelerate decarbonization.”
He uses estimates of what a call to an LLM entails versus the number of calls a job might take, compared to someone doing it manually with a computer running. He finds that having an LLM do certain tasks can be more carbon efficient, and that it can also become more efficient over time.
“What we do today will be more efficient tomorrow,” he added.
While these considerations are important internally, they will also be important for the network requirements for the homes the builders build. Homes will need to be able to create and store their own energy to be more independent from the electricity grid, which will be more committed to data center activities.
In the future
By 2027 we will have super intelligence, or a fully self-aware, true artificial intelligence that can function independently.
“The race to superintelligence is accelerating and whoever gets there first wins the AI race,” Anschel said. “If OpenAI gets there first, no other model will be able to catch up and it will be able to grow faster than any other model. The only way to prevent that is to physically damage that intelligence.”
While the wait for super intelligence continues, home builders and those who serve them can embrace AI to future-proof their businesses and be ready to reach the next level when the time comes.
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