Artificial intelligence (“AI”) isn’t a Silicon Valley experiment anymore. It’s showing up on construction sites and changing how projects get planned, priced, and built. Drones check progress. Software estimates materials. Predictive tools flag potential safety risks, before anyone steps foot on a jobsite. The technology is powerful, but as the saying goes, “with great power comes great responsibility.” On a jobsite, that responsibility means knowing who’s liable when something goes wrong and how to protect the data your AI tools collect.

Let’s start with liability. Picture your AI estimator misjudging the amount of concrete you need, leaving you with a massive surplus. Or a drone’s analytics mistakenly flagging a “safety issue,” that causes the crew to stop work for a full day. These aren’t far-fetched examples; they’re already happening. When the algorithm gets it wrong, who pays for the mistake? The answer is almost always in your contract. Most vendors draft their agreements to protect themselves, not you. Software liability caps are often limited to the price of the software, which won’t come close to covering a real loss. Before you purchase the software, read the fine print carefully and negotiate for meaningful protection, if at all possible. Push for indemnity clauses that make the vendor accountable if their technology fails. A few paragraphs in the contract can decide whether a glitch becomes an inconvenience or a financial disaster.

Still, no contract changes one fundamental rule: AI is a tool, not a decision-maker. The law expects a human to stay in control. Following an algorithm without independent review isn’t being “innovative,” it’s being careless. A project manager who accepts a cost analysis without checking the inputs takes the same risk as a builder ignoring a specification sheet. The software can make you faster, but it doesn’t replace judgment. Keep a licensed professional to review designs. Document your oversight. Stay in the loop.

And never forget one of the oldest rules in technology: garbage in, garbage out. AI is only as reliable as the data behind it. If that data is outdated, incomplete, or biased, the results will be, too. That’s how you end up with flawed estimates or unrealistic schedules. Don’t treat an AI dashboard as gospel. Ask where the data came from, how current it is, and whether it fits the dynamics of your jobsite, instead of someone else’s.

The other half of the equation in AI is privacy. AI systems collect enormous amounts of data—site footage, blueprints, GPS tracking, and even biometric scans from workers. That information can make operations smarter and safer, but it also creates risk if it falls into the wrong hands. A single breach could expose client plans, trade secrets, or personal information. That’s not just embarrassing; it’s potentially a lawsuit. You need to know where your data is stored, who manages it, and what the backup plan is, if something goes wrong. Every contract should include robust cybersecurity standards and clear breach notification procedures. And if a vendor’s system gets hacked, they should share responsibility for the damage caused, instead of simply shifting responsibility to you.

Transparency with your team also matters. If you’re using AI to track employees—through cameras, wearables, or scanners—you need to be honest about it. Tell people what’s being collected, why, and how it will be used. In several states, written consent isn’t just polite: it’s the law. Even where it isn’t required, openness builds trust. Workers are more likely to embrace technology when they know it’s there to improve safety and efficiency, not to monitor them.

And don’t forget about privacy outside your own site. Drones and smart cameras don’t automatically stop at property lines. If your equipment captures neighboring homes or people who aren’t part of your crew, you could face privacy claims. Know your flight paths, control your footage, and think about what’s in your frame before you start recording.

AI can make the industry faster, safer, and more efficient. But it’s not autopilot. The companies that win with this technology will be the ones that combine innovation with accountability. They’ll read their contracts closely, keep qualified professionals in charge, and treat data with the same care they treat structural steel. The tools are getting smarter by the day, but it’s still up to humans to set the rules. Smart tools need smart leadership—and the builders who understand that balance will set the standard for everyone else.

 

David R. Meunier is an associate attorney with Dunn DeSantis Walt & Kendrick. David’s practice focuses on complex commercial litigation, bankruptcy, and real estate disputes.

Dunn DeSantis Walt & Kendrick provides a broad spectrum of legal services to businesses of all sizes, from small, local start-ups and non-profits to large, national companies. DDWK’s real estate development and construction practice includes representing all segments of the development and construction industries on both private and public projects. 

You can find additional information and resources related to helping business owners and their businesses on the DDWK website.