What Builders Actually Do with AI: Insights from the IMW Backroom

Content, contracts, job sites, and spreadsheets—here’s how builders are actually using AI.

The latest IMW Backroom brought together a cross-disciplinary crew working deep inside their businesses:

• Morgan Molitor, co-founder of Construction2Style
• Will King, founder of High Cotton Homes
• Reece Barnes, strategist and sales pro, previously at Adaptive

What they shared: real-world examples of how AI is saving time, cutting costs, and speeding up decision-making—without a single masterclass, GPT build, or complicated setup.

What they’re navigating: the gap between AI hype and practical adoption in day-to-day business.

This wasn’t a look-ahead at where AI is going. It was a candid download of how they’re using it right now—and how fast it’s changing their work.

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1. AI is the new assistant—for content, planning, and client strategy.

Morgan broke down how she uses AI to scale up her content game and internal planning process.

From one transcript (a podcast, an interview, a client voice memo), she’s generating multiple blog ideas, full article structures, and even building content series mapped to her tone and blog formula. It’s not just automation—it’s acceleration.

She also uses AI for financial strategy: reviewing past revenue, identifying gaps, and reverse-engineering next year’s targets. In one team session, they restructured budget lines, assigned focus areas, and set weekly benchmarks for each department—with AI helping synthesize all the data.

Pro Tip: If you’ve done a content task or revenue review manually more than twice, teach AI your process. Then prompt it to do it for you.

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2. Builders are using AI on the job—right now.

Will’s take was refreshingly blunt: “I’m not building GPTs. I’m just using it like a foreman who’s tired of doing math.”

He uses AI to review contracts before sending them to lawyers, speeding up the Q&A phase and reducing his legal bills. But his biggest time-saver? Job-site math.

He walks through elevation plans, asks GPT to calculate wall heights, footer depths, or convert decimals to fractions on the fly. He even used it to verify a winter-ready concrete mix—GPT suggested a non-chloride accelerator over calcium, and his supplier backed it up.

Lesson Learned: AI isn’t replacing expertise—it’s a second set of eyes when pressure’s on.

Pro Tip: Use voice-to-text in the field. Speak your calculation out loud, have GPT run the numbers, and double-check your subs before the pour.

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3. Smart prompts > smart tools.

Reece kept it simple: start by replacing Google with GPT. Use it daily. Then ask it to grade your prompts and teach you how to get better.

He challenged the group to push past basic searches and think critically about how they’re prompting. His move? Ask GPT to critique its own answers. “Where is this logic flawed?” “What would you do if you had more data?” “Where might I be wrong?”—this opens up stronger, more nuanced responses.

He also shared a powerful use case for builders with ongoing service models: feed GPT every product spec from a completed build (HVAC, appliances, plumbing, etc.) and ask it to generate a home maintenance plan. Turn that into a recurring contract, and you’ve got a scalable new revenue stream.

Pro Tip: If your prompt sounds like a Google search, rework it. Give GPT context, constraints, and a role to play.

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4. Process, not magic.

Charlotte and Morgan emphasized the power of “Projects” in ChatGPT—containers where GPT can reference past files, tone guides, and previous conversations. When building a rebrand or content strategy, everything lives in one project. That means GPT is working with full context every time you prompt it.

They also use AI for communication—refining tone in emails, softening blunt feedback, and helping navigate tricky client conversations.

Pro Tip: Ask GPT to act as your editor, not your ghostwriter. Give it your core message, then ask it to match a tone or improve clarity without losing your voice.

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Bottom Line

No one in the room was building GPTs from scratch. No one was running prompts with 27 sub-steps. Everyone was using AI as a tool—to speed up thinking, scale insight, and buy back time.

The takeaway wasn’t “you should be using AI.”

It was: you already can.

Some of the sharpest applications didn’t look like tech at all—they looked like smarter thinking, faster feedback loops, and better boundaries with time and clients.

If that’s what AI can unlock right now, imagine where we’ll be in six months.