The Role of Artificial Intelligence in Mechanical Contracting

Melvin Newman, CEO of PataBid, is a mechanical estimator turned entrepreneur. Newman worked extensively in the field before founding a technology company serving the mechanical/electrical contracting industry.

Since ChatGPT burst onto the scene in late 2022, AI has gone from tech industry novelty to everyday business tool. Mechanical and plumbing contractors are no exception—AI is showing up in everything from project communication to marketing.

But not every task should be automated, and some carry real risks if you get it wrong.

Use AI to assist, not replace, your judgment. AI can draft, summarize, and suggest, but it doesn't know your clients, your suppliers, or the nuances of your local market.

Where AI does excel is in the tedious, time-consuming work that bogs down your preconstruction processes. Think automated takeoffs, extracting quantities from drawings, or organizing specification data. The sweet spot is using AI to handle the grunt work faster. This frees up your estimators to focus on what demands human judgment: pricing strategy, risk assessment, and building the relationships that win work.

The key to getting useful results from any AI tool is writing a good prompt. A prompt is simply the instruction you give the AI. Vague prompts get vague results. Specific prompts get specific, usable outputs.

The more detail you provide, the better your output. Instead of asking for "a scope letter," tell the AI the project type, square footage, scope inclusions, exclusions, and the tone you want. Think of it like briefing a new employee. The clearer your instructions, the less back and forth you'll need.

Your first AI prompt won't always give you exactly what you need. That's normal. Treat AI as a collaborative tool. Review the output, tell it what to fix or adjust, and refine from there. Most people give up after one mediocre result. The real value comes when you learn how to guide the AI toward what you actually want.

Use AI to assist, not replace, your judgment. AI can draft, summarize, and suggest, but it doesn't know your clients, your suppliers, or the nuances of your local market. Always review outputs before sending them out. The goal is to save time on the first draft, not to hand over decision-making.

Michael Kanaby, Managing Partner at Profitability Works Inc., has over 30 years’ experience in the construction industry and is the co-author of Building Excellence: Implementing Standard Processes for Construction Trade Contractors.

Here is the uncomfortable truth: most contractors are not ready to benefit from AI. The problem is not that contractors are resistant to technology; it is that most businesses lack the necessary data structures and processes for AI to work effectively.

AI is not a replacement for human expertise; it is an amplifier for it.

Let us examine a familiar process, change orders, and explore its progression across three stages of readiness: centralized data, process, and automation.

The first step is to centralize and standardize the data. Every change order should reside in a single platform, whether that is an ERP, a Project Management tool, or a Smartsheet on a SharePoint site. The inputs should have uniform fields, such as project number, client name, scope, price, status, date, and approvals, as examples. Once that consistency is in place, leadership can begin to trust the information.

Next, companies should establish a process to manage the identification, validation, and authorization of changes. Every project team and office should handle change orders in the same manner. This way, there is no confusion about which change orders are approved, what is pending, or what has been billed. Standardizing the process is not about adding red tape or slowing people down; it is about bringing clarity to the work, accountability to the numbers, and consistency that can enable the adoption of AI.

Once the data is clean and the process is consistent, automation can take over repetitive tasks. Imagine a system that captures every change order as soon as it is submitted, uses OCR (optical character recognition) to read attached documents, automatically routes it for approval, and updates project costs in real time. That is not science fiction; it is available now.

AI is not a replacement for human expertise; it is an amplifier for it. The construction contractors that succeed in the coming years will be those that are ready for modern technology and can integrate and operate in their customers’ technological environment.

AI then adds another layer of value. It can analyze hundreds of past projects to predict which types of changes are most likely, flag unusual cost patterns, or even recommend negotiation points with specific clients based on historical behavior. What was once reactive and tedious becomes proactive and strategic.

Chaitanya Naredla Krishna is Co-Founder & CEO of Track 3D, a “reality intelligence” platform turning complex site data into actionable insights.

Think of Reality Intelligence as a “capture–compare–act” loop that runs continuously. It starts with structured site capture—drones, 360° walks, mobile LiDAR—so conditions are timestamped and comparable over time.

Next, AI does the heavy lifting that humans shouldn’t have to: segmenting point clouds and images, recognizing building elements like duct runs, drywall, or structural members, and extracting geometric facts such as lengths, areas, volumes, and positions.

Construction will always be physical, local, and complex, but it doesn’t have to be opaque. 

Those measurements are then aligned to design and schedule to quantify progress, detect deviations, and recognize out-of-sequence work. The insights are accessible to various project stakeholders, they're organized and surfaced in a way that lets the right people act on them

First, progress becomes defensible, not anecdotal. When progress is measured with real data instead of guesswork, teams can prove exactly how much work is complete. This makes project tracking more accurate, protects schedules from slipping, and helps owners quickly verify what’s been done and paid for.

Second, deviations surface early. Geometric misalignments and tolerance breaches are identified before drywall is closed or rebar is poured, transforming quality control from after-the-fact reporting to proactive prevention.

Third, schedules reflect reality. As-built measures feed automated schedule updates, so the plan stops drifting on assumptions.

Fourth, resources are allocated with intent. With granular progress and look-ahead deltas, teams tune crew assignments and time deliveries just-in-time, trimming idle time and waste. 

Construction will always be physical, local, and complex, but it doesn’t have to be opaque. Reality Intelligence shortens the gap between plan and truth, turning photos and point clouds into verified progress, earlier conflict detection, and faster, better decisions.