When Digs announced its new strategic partnership with Matt Risinger and The Build Show Network last week, the headline was easy to read as another AI-in-construction story. A platform company and a respected industry educator collaborate on a promise to help builders make sense of new technology. All that is certainly accurate. But what I see is another example of AI starting to move from curiosity to workflow infrastructure.
Digs describes itself as an AI-powered construction collaboration platform built around documentation, collaboration, visualization, search, takeoffs, homeowner communication, and warranty management. Through the partnership, Risinger and The Build Show Network will help builders understand where AI can deliver practical results in areas like estimating, pre-construction planning, project collaboration, homeowner handoff, and warranty support.
That kinds of lists should sound familiar to integrators, who asked for AI tools that help them accomplish as much in our recent AI workflow survey. The work isn’t just installing technology. It’s capturing decisions, translating technical details, keeping everyone aligned, and leaving behind a system the client can actually understand after the trucks are gone.
With a platform like Digs, we’re seeing a version of AI that’s framed around project memory.
For builders, the idea is that valuable information is often trapped across plans, PDFs, emails, messages, and disconnected systems. For integrators, the same problem shows up in proposals, drawings, equipment lists, programming notes, passwords, network maps, service histories—you name it. The information exists, but it is often scattered across people, platforms, or folders.
Connected Design’s recent AI coverage has pointed in the same direction. In that AI workflow survey, 79 percent of respondents said they are either actively using AI in daily workflows or experimenting with it. The leading use cases were practical: proposals and client communications, product research, marketing, documentation, and support. Those results spilled over to our AI Roundtable where panelists kept returning to the same point. AI becomes more useful when it is aimed at real bottlenecks rather than treated as a novelty.
For an integration firm, that means the first question should not be “Which AI tool should we use?” Rather, you should be asking “Where does our team lose the most time because information is hard to find, hard to format, or hard to hand off?”
The builder example offers a useful framework.
Start with documentation. Digs is emphasizing AI-powered search across plans, specifications, contracts, etc. Integrators can apply that same logic to their own project records. Imagine being able to ask, “Which access points were installed in the Smith residence?” or “What shade fabric did the designer approve for the primary bedroom?” or “What did we promise in the final proposal?” and get an answer tied back to source material. That type of workflow doesn’t replace your judgment or expertise in the matter. All it does is reduce the time spent hunting for context.
Next, look at takeoffs and scoping. Builders are using AI to speed up measurements and quantities. Integrators have a parallel opportunity in early design and proposal development. AI can help summarize plans, extract room counts, organize product categories, draft scope language, and flag missing information before a proposal goes out. The value is not in letting AI design the system alone. The value is giving the professional a cleaner starting point and more time to think through the experience.
Collaboration is another clear lesson. DigsCanvas, the company’s plan collaboration environment, is built around communication directly on plans and tracking decisions before construction begins. Integrators live in that same coordination space with architects, designers, builders, and countless other trades. AI-assisted project tools could help turn scattered comments into action items, organize design decisions by room, summarize meeting notes and preserve the “why” behind system choices.
The integrator’s work often becomes invisible when it succeeds. The homeowner sees a clean keypad, a quiet rack, a simple scene or a system that just works. But invisible should not mean undocumented. AI can help firms create a better digital handoff: product records, manuals, warranties, service expectations, network information, maintenance schedules, and plain-language explanations of what was installed.
Digs is also putting warranty and aftercare into the AI conversation. Service is where margins, client trust, and team capacity collide. If AI can help a service team quickly understand the history of a home, identify likely causes, prepare the technician, and explain the resolution to the client, it becomes a business tool, not just an administrative helper.
To be clear, the goal here is not just blind automation. Alex Capecelatro, CEO of Josh.ai, warned of that during the AI roundtable, saying AI outputs need to be checked. Client data must be protected. Firms need to understand the companies behind the tools they adopt and the way those tools handle sensitive project information. AI tools can provide better context, faster retrieval, cleaner communication, and more consistent follow-through. But the human instinct element certainly needs to play a part.
All that said, builders are beginning to use AI to make the homebuilding process more connected, more searchable, and more useful after the project ends. Integrators can do the same. The firms that benefit first will likely be the ones that stop treating AI as a side experiment and start applying it to the everyday friction points that shape profitability, client experience, and team sanity.
