3 Systems to Scale Your Construction Company (in 2026)
Episode Description
In this episode, Adam Cooper and Jeff Robertson bring their decades of experience to lay out 3 of the top processes necessary for a construction firm to grow. We hope you enjoy this one!
Chapters:
0:00 – Scaling Preconstruction & Estimating
7:30 – Systems for Operational Performance
15:18 – The Strategic Role of the Back Office
20:33 – Comparing GC vs. Trade Contractor Scaling
31:43 – Specialization & Future Growth
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Episode Transcript:
Welcome everyone. Welcome to the Construction Hot Takes podcast. I’m Jeff Robertson, one of the partners here at Ascent Consulting. I’ve been on a couple of the other podcasts, and we’re doing something a little different today—this is a solo podcast, which is new for me, so bear with me.
I want to cover a topic today: artificial intelligence in construction. It’s a hot topic. We’ve got a lot of clients calling us asking how they can incorporate AI into their business, so I thought I would spend some time talking about that.
Specifically, I want to talk about it in general—what’s out there. There are a couple different ways to think about how AI is being incorporated into our software tools, some of which we may be familiar with and some we may not. I want to talk about the basic market a little bit, how those tools are being grouped into a few tiers, and then some practical ways to think about where AI fits in your business, along with some simple use cases.
So let’s get started.
AI as a concept is getting a lot of attention in the media, not just in construction. People are trying to figure out what it means for society. Is this Skynet? Is it HAL? What’s it going to do to us?
What some people may not realize is you’ve already been using AI, whether you know it or not. If you use Waze or Google Maps, or if you’ve ever gotten a fraud alert from your bank, those systems are using AI algorithms in the background. So it’s already happening.
Construction has traditionally been a conservative industry—if it ain’t broke, don’t fix it. But in the last 10 to 15 years, there’s been a massive investment in construction technology. We’ve resisted it pretty well, but we’ve hit a tipping point where it’s becoming inevitable.
And that’s for good reason—it can make us more efficient. But I’ve never been one to recommend technology just because it’s cool. It should always be evaluated based on how it improves your business and what the return on investment is.
If you don’t think about how it fits into your business and how it will actually be adopted, it can become a wasted investment. That’s why we spend a lot of time with clients figuring out where it actually makes sense.
I also think we’re often asking the wrong question. Instead of asking “What is AI?” or “Where do I plug it in?”, the better question is: where are the friction points in my business, and how could AI help solve them?
Now let’s talk about the marketplace.
There are easily 300+ AI-related tools out there right now—probably more. That’s what makes it overwhelming. Clients tell us all the time they don’t know where to start.
But this moment actually reminds me of the late 90s and early 2000s when the internet was emerging. It was the Wild West. Nobody knew how to use it or monetize it. Eventually, the market consolidated—Google emerged as a dominant player, and things became clearer.
We’re in a similar place now with AI. There’s a lot of investment, a lot of ideas, and eventually there will be consolidation. That shouldn’t scare you—it should actually be exciting.
So how is AI showing up?
There are basically three categories.
First, AI-enhanced tools. These are legacy systems like Procore or Sage that are adding AI features on top of what already exists. For example, Procore’s Helix is an AI layer built into their platform.
Second, AI-native tools. These are built from the ground up with AI as the core. Tools like ChatGPT or construction-specific platforms like Document Crunch fall into this category.
Third, integration or orchestration layers. These sit on top of multiple systems and connect them, allowing you to pull data together in one place. Tools like Brick, HH2, or even Power BI can function this way.
Now let’s talk about adoption across different contractor sizes.
Large contractors—hundreds of millions or billions in revenue—are already well into AI. They’ve formed committees, developed governance policies, and are actively running pilot programs.
Mid-market contractors—say $50M to $250M—are experimenting. They may have individuals using AI tools for meeting summaries, RFIs, or contract reviews, but it’s not fully standardized across the company yet.
Smaller contractors, in my opinion, have the biggest opportunity. AI can act as a force multiplier. It can function like an additional employee, helping them compete in ways they couldn’t before.
One important note: adoption at the field level is still very low. Most of the activity is happening in the back office or operational side of the business.
Now let’s talk about barriers to adoption.
The biggest barriers are not the technology—they’re your internal systems.
Data cleanliness: Do you trust your data? ERP maturity: How sophisticated are your systems and processes? Change management: How well does your organization adapt to new ways of working? Trust: Do you trust the output of the system?
AI is not a magic solution. It won’t fix poor financial controls, inconsistent job costing, or fragmented workflows. If your foundation is broken, layering AI on top will only create more frustration.
There’s an old saying—garbage in, garbage out. That still applies.
So how should you approach this?
I like to use a baseball analogy. Home runs are exciting, but they’re high risk. I prefer a more consistent approach—getting on base, moving runners, playing the long game.
That’s how you should think about AI. Start small. Find areas where you can incrementally improve your business.
Now let’s talk about practical use cases.
From a risk and compliance standpoint:
Subcontractor insurance expiration alerts
Certified payroll anomaly detection
OSHA trend analysis
From a financial controls standpoint:
Underbilling alerts
WIP analysis support
Vendor price volatility tracking
From a project management standpoint:
Daily report keyword scanning
Automated superintendent prompts for daily logs
Preconstruction bid leveling
Scope gap detection
Go/no-go decision models
From an executive level:
Cash flow forecasting
Backlog risk analysis
All of these are things you can do today. This isn’t science fiction.
The common theme is margin protection and risk mitigation.
In closing, we’re in the early stages of AI adoption in construction. There’s a lot of diversity in the market, just like there is in our industry.
Don’t let it overwhelm you. You don’t need to fully understand how it works to start using it. Just start somewhere—start small.
But remember: if your data is unreliable or your processes are unstable, AI will be difficult to implement effectively.
It’s not a cure-all. It won’t fix a bad foundation.
That’s ultimately why Ascent Consulting exists—we help construction companies build better processes, implement systems, and scale effectively. AI is just another tool in that toolbox.
So if you’re looking for help, we’re here.
Thanks for tuning in. I hope you got something out of this. Please like and subscribe, and we’ll see you next time.
