How AI is Rewriting the Rules of Documentation

documentation

You might still remember the yellow binder days鈥攚hen documenting a claim meant seven layers of carbon copies and a handshake at the bar. Mitch Byrom also remembers those days. He joked that, back then, 鈥渃ontractors knew how to do construction and restoration, and adjusters knew how to assess damage.鈥

But as Byrom, founder of Restoration-OS and a longtime IICRC instructor, explained, today鈥檚 water damage claims are a very different story鈥攁nd artificial intelligence (AI) is right in the middle of it.

AI is no longer some looming trend or gimmick鈥攊t鈥檚 here to stay, embedded in your smartphone, calculating your estimates, drafting your sketch, reviewing scopes, and shaving days off your billing cycle.

So what does that mean for you, the person actually wading through water, documenting drying logs, and arguing line items?

With decades of restoration experience and multiple software, businesses, and executive relationships, paired with his knowledge of claims, Byrom shared his expertise on the subject with the restoration community.

From floppy disks to LiDAR scans

You didn鈥檛 ask for this shift. 鈥淲e were forced to use Xactimate,鈥 Byrom reminded. 鈥淣ot because people didn鈥檛 like your handwritten notes, but because the carriers wanted a standardized price list.鈥

Xactimate, among other products available in the marketplace, is one of the software systems that insurance adjusters, contractors, and restoration professionals use to create detailed property damage estimates. It uses advanced algorithms and a comprehensive database of repair and replacement costs. The process is highly automated, reducing the potential for errors and ensuring a high degree of accuracy. Its use was the first major shift to technology in the industry.

The earliest version was built off a group of contractors inputting their pricing on floppy disks. That evolved into national pricing averages, labor efficiency tracking, formula research, and the rise of unit pricing.

But what about AI? 鈥淎I is different,鈥 Byrom said. 鈥淎I is when the system learns. When it starts making decisions based on data, it鈥檚 not just your calculator鈥攊t鈥檚 your assistant, estimator, and auditor. And it鈥檚 learning fast.鈥

Take measurement, for instance. 鈥淚f you get a bad measurement on ceiling height, you miss out on cubic footage for dehumidification, on antimicrobial, on cleaning labor, on paint. You even lose your scaffold charge,鈥 Byrom explained. 鈥淎ll because you measured 10 feet instead of 12 feet.鈥

Now, your iPhone can do it better. If you have a 12 Pro or above, you already carry a LiDAR (light detection and ranging) scanner in your pocket.

鈥淵our phone doesn鈥檛 forget a measurement,鈥 he said. 鈥淚t doesn鈥檛 misread the tape. And it鈥檚 fast.鈥

Meet the new technician: AI

Byrom doesn鈥檛 just teach this stuff鈥攈e uses it. His 21-year-old son, Kyler, was recently conducting an inspection at a Hardee鈥檚 in flood-soaked Western Kentucky. Kyler鈥檚 no Applied Structural Drying (ASD) expert, just a normal, barely-passed Water Restoration Technician (WRT). But with Restoration-OS in hand, a LiDAR-equipped phone, and AI-powered sketch tools, he can generate a complete carrier compliant water sketch, scope, and moisture map documentation set on his own.

鈥淚t鈥檚 not because he鈥檚 the world鈥檚 best tech,鈥 Byrom admitted. 鈥淚t鈥檚 because he had the right tool.鈥

That鈥檚 the new reality: High-skill outputs from low-skill labor鈥攚hen paired with the right tech. You don鈥檛 need a black belt in restoration to deliver a perfect sketch and inspection anymore. AI is doing the heavy lifting.

Speed, accuracy, and the estimate gap

At some point in your business, you鈥檝e likely been told that claims need to be processed faster; that carriers expect a three-day turnaround on estimates. And if you鈥檙e like most contractors, you鈥檙e actually averaging nine.

鈥淭hey say we need to speed up,鈥 Byrom said. 鈥淏ut really, what they mean is this: We will be mandated to speed us up, if we don鈥檛 start doing it fast enough.鈥

Carriers and private equity groups are already investing heavily in AI for estimate generation and review technology. Byrom named tools like Yembo and Hosta A.I., which scan rooms, calculate costs, and even initiate homeowner payouts鈥攁ll before you get on site. Some of these are coming out of academic leaders like the Massachusetts Institute of Technology.

鈥淭hat check鈥檚 going straight into their account,鈥 he said. 鈥淎nd then what? The homeowner calls around, looks for someone cheaper, and now you鈥檙e stuck supplementing.鈥 Does that sound familiar? The auto body industry has seen how this changes up the business process since they have already seen this shift in auto claims.

How the bots really think

If you think AI is always accurate, think again. 鈥淕arbage in, garbage out,鈥 Byrom said. 鈥淎I is only as smart as the data it gets.鈥

So, double-check everything, especially if you鈥檙e relying on tech to build your sketch or pick your line items.

鈥淚s it fiberglass reinforced plastic or drywall?鈥 Byrom asked. 鈥淚s it Category 3 or Category 2? Was it after hours? Weighted extraction? The AI won鈥檛 know unless you tell it.鈥

Even when an AI system recommends line items, you鈥檙e still the quality control. 鈥淵ou鈥檙e not the estimator anymore,鈥 Byrom explained. 鈥淵ou鈥檙e the auditor.鈥

Context is king

Byrom shared a story about working with RICOH, the global tech company behind some of the best 360-degree cameras on the market.

He convinced them to integrate their imaging into his app, and now they鈥檙e exploring ways to teach AI how to recognize furniture by its cubic volume, weight, and even SKU (stock-keeping unit) numbers.

鈥淚magine scanning a room and instantly knowing how many vaults you鈥檒l need or getting a suggested contents list and estimate built automatically,鈥 he said. 鈥淭hat鈥檚 where this is going.鈥

Still, AI won鈥檛 know if the sofa鈥檚 medium-density fiberboard (MDF) is swollen from water damage. It won鈥檛 catch the nuance of customer distress. It won鈥檛 interpret context as well as you can.

鈥淎I won鈥檛 get you paid faster,鈥 Byrom clarified, 鈥渂ut it can help you submit faster. And submission speed is directly tied to payment speed.鈥

Who鈥檚 training whom?

Byrom provided one final takeaway: The best AI won鈥檛 come from big tech or software vendors鈥攊t鈥檒l come from you.

鈥淭he algorithm only gets smarter when you feed it,鈥 he explained. 鈥淚f you build your own workflows, train your own models, and set up your own logic, it works for you鈥攏ot against you.鈥

His app, Restoration-OS, is designed with that in mind: choose the materials, conditions, and damage levels, and the app automatically fills recommended equipment and scope line items. You鈥檙e not just guessing鈥攜ou鈥檙e guiding.

And when you鈥檙e guiding, you鈥檙e still in charge.

The future is fast鈥攁nd human

Yes, AI is here. It鈥檚 scanning rooms. It鈥檚 building estimates. It鈥檚 replacing pencil sketches with phone scans and turning technicians into data collectors. But as Byrom reminded us, 鈥淎I doesn鈥檛 replace judgment. It replaces repetition.鈥

The real challenge isn鈥檛 learning how to use it. It鈥檚 knowing when not to.

So next time someone says you鈥檙e behind the curve, remember what Byrom said: 鈥淵ou don鈥檛 have to be afraid of AI. You just have to be better than it.鈥

Watch the full interview below:

Jeff Cross

Jeff Cross is the 天美传媒 media director, with publications that include Cleaning & Maintenance Management, 天美传媒 Today, and Cleanfax magazines. He is the previous owner of a successful cleaning and restoration firm. He also works as a trainer and consultant for business owners, managers, and front-line technicians. He can be reached at [email protected].

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