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Home repairs do not come cheap or easy—especially in today’s era of high inflation and contractor shortages. Perhaps then it’s no surprise that homeowners are turning to AI to help them out.
A new Guardian Service survey of more than 1,000 respondents found that homeowners who followed AI’s guidance on tools like ChatGPT and Bard reported an average 47% reduction in repair or maintenance costs and 29% felt less stressed about managing home repairs.
However, there is a downside to using AI for home repairs, namely wrong or incomplete advice. While the DIY movement is still alive and well with the help of AI tools, homeowners should be wary that saving a buck might cost them in the long run.
More homeowners are turning to AI to fix things themselves
More than 2 in 5 homeowners have already used AI for assistance with home repairs or maintenance, according to the Guardian Service survey, and nearly 1 in 4 homeowners stated they would delay hiring a contractor if AI said their issue wasn’t pressing.
The most significant savings were seen in appliance repairs (51%), plumbing (49%), and general handyman work (46%)—aka, repairs that a skillful homeowner could tackle themselves with some simple instruction.
Perhaps unsurprisingly, Gen Z led the way in percentage of homeowners turning to AI for maintenance advice, with 50% asking for home repair guidance from AI. This was compared with 32% of baby boomers, 40% of Gen X, and 47% of millennials.
What was surprising was that homeowners didn’t always double-check the advice AI gave them. In fact, 22% of homeowners went ahead and followed AI’s recommendations without reaching out to a human or contractor for reassurance—and that’s where the trouble can start.
The pros and cons of AI-powered home repairs
AI can provide basic information about common home repairs and may be able to save you some cash if you complete a repair yourself. It can also help you vet service providers and make smart decisions about home insurance.
But the truth is that no AI can adequately substitute for hiring a professional, especially when the repair itself requires knowing a specialty skill.
“You risk spending time and money on repairs that can lead to no success and potentially wreak havoc on your water heater, furnace, air conditioner, fridge, or other important systems in your home,” says Gregg Cantor, president and CEO at Murray Lampert Design, Build, Remodel in San Diego.
AI-powered home repairs can also pose serious safety risks, especially if gas, electrical, or structural work is involved. Thankfully, far fewer homeowners are turning to AI for these kinds of repairs. For example, only 13% of homeowners acknowledged using AI to help with electrical work.
So, while there’s nothing wrong with using AI as a research tool, understand that it’s not a replacement for professionals.
Homeowners still trust real people over algorithms
Even among frequent AI users, trust is still a hurdle. While over 40% have turned to AI for home repairs, a full 79% trust a contractor more. “The gap is driven by concerns around accuracy—68% worry that AI could give misleading advice,” says Sam M. Huisache, Austin, TX,-based researcher and analyst at Guardian Service.
Home repairs often include elements that homeowners themselves don’t even realize, which is why the eyes of a pro can be invaluable. For example, sometimes roof damage isn’t just a few missing shingles.
“Sure, AI might be able to tell you general advice about how to install new shingles, but it’s not going to know if you have water damage or mold growth, so you might end up with a major problem you won’t know about for a while until it gets much worse and much more costly to repair,” says Andre Kazimierski, co-owner and president at HomeHero Roofing in Downers Grove, IL.
While the study doesn’t report on contractor feedback directly, 1 in 4 homeowners say they’ve used AI to verify or challenge a professional’s recommendation—strongly suggesting that contractors are encountering AI-informed clients more often.
“A tenth of homeowners reported that AI gave them conflicting information compared to a technician. That kind of mixed messaging introduces doubt and highlights AI’s current limitations in nuanced, hands-on tasks,” says Huisache.