AWCI’s 2025 Industry Leaders Conference keynote speaker, Zach Giglio, explains why adopting artificial intelligence is about management, not software.
Wall and ceiling contractors have every reason to be skeptical of the buzz around artificial intelligence. New tools pop up regularly. They claim to improve site visits, design tasks, code compliance and more. Yet, the real challenge with AI isn’t about licensing more software. It’s about something much deeper and far more human: leading people through change.
“I would look at this not so much as a tech implementation, but more as a change management program,” says Zach Giglio, founder and CEO of GCM. “Understanding the people part of this process—that’s the first step.”
Giglio—the keynote speaker at AWCI’s 2025 Industry Leaders Conference, to be held November 11–13 in Louisville, Kentucky—specializes in helping construction companies integrate off-the-shelf AI models like ChatGPT and Claude into their daily workflows. But his approach doesn’t start with code. It starts with conversation—at the top.
“One of the bigger problems with AI adoption is not that leaders aren’t saying, ‘We need to adopt AI,’” Giglio says. “They’re saying, ‘We need to adopt AI,’ and then leave the room.”
Leaving it to the team to figure out how AI will be implemented is overwhelming and sets them up for a struggle, Giglio says. Instead, company leaders need to embed AI adoption into their own mindsets. They need to lead by example, becoming AI conversant, setting expectations and making adoption a team-wide journey, not just an IT department mandate. AI needs to be part of a construction company’s strategic mission.
AI Adoption—Analog Style
Artificial intelligence has been around since the 1950s. It began as a field of computer science and research. But from the beginning, its goal was to create software that could perform human-like tasks. Researchers soon developed a practical benchmark they called the Turing Test—named after Alan Turing, a British mathematician, computer scientist and early pioneer of AI. It was said that if humans couldn’t tell the difference between the machine’s output and a person’s then the software “passed” the Turing Test.
Today, the field of artificial intelligence is vast, encompassing robotics, machine learning, neural networks, natural language processing, big data and more. Many equate AI with large language models, such as Open AI’s GPT-4, largely because the media has focused so heavily on this branch of technology.
Discussions about AI often carry urgency, complexity and a sense of the unknown—making the path to adoption feel intimidating. But for wall and ceiling firms trying to get started, Giglio suggests keeping the game plan simple: Find simple tasks that AI can help complete more efficiently, he says. You don’t need to understand the inner workings of your smartphone’s digital camera to take a good photo, Giglio says, so you don’t need to be a mathematician to use AI. What matters, he says, is understanding the general idea of what AI models do.
And yet, Giglio admits, AI’s complexity often causes confusion on leadership teams and with participants in the field. So, he advises top management to focus on desired outcomes by auditing company workflows. Don’t think first about AI’s features, Giglio says. Think first about work tasks.
“Rather than thinking, ‘How can AI help me?’ I would think in a more analog way,” Giglio says. “If we had an intern working in this department, what are the first five to 10 things we would have them do?”
In answering that question, Giglio recommends filtering work tasks to those that are simple and what he says are “meaningful” to the company. This is important, Giglio says, because the goal of AI implementation isn’t to create new work—it’s to offload what’s routine.
For example, the project managers at one general contractor Giglio worked with would create handwritten notes during their jobsite walks. At the end of the day, they’d spend about two hours deciphering their notes, writing reports, updating schedules and emailing vendors with service requests.
“We helped them use voice dictation and ChatGPT to draft those notes immediately and cut the process down to a half hour,” Giglio says. “That’s meaningful. That’s 90 minutes a day they get back.”
The project managers immediately saw the value of doing what was already being done—but now faster with AI help. The lesson is to not jump into unfamiliar territory too quickly by seeking aspirational goals rather than practical ones.
“We find people saying, ‘Let’s start doing what we always wanted to do,’” Giglio says. “That’s a roadblock to long-term AI adoption.”
Not a Tech Project
Giglio brings a strong mix of academic training and real-world credibility to the conversation about AI. He is a certified AI strategist through The Wharton School of the University of Pennsylvania, bringing Ivy League insight to AI deployment. He’s also a TEDx speaker and serves on the faculty of the U.S. Chamber of Commerce’s Institute for Organization Management, where he teaches business leaders how to adopt transformative technologies.
The takeaway from Giglio’s work is to make AI a part of everyday operations. AI integration isn’t a technical project. It’s a management strategy.
“This is more change management than it is tech implementation,” he says. “You want to reduce as many barriers, and as much friction, as possible.”
Thus, Giglio encourages wall and ceiling company leaders to frame AI as a tool to save time and improve work, not replace jobs. He says that using AI should become as routine as sending email.
Here’s how to begin:
- Start with the early adopters. Let them use large language models—ChatGPT, Claude, Co-Pilot, Gemini—to model use cases for the firm. You want them to become internal AI champions, so to speak.
- Make AI adoption part of the leadership team’s weekly conversation. “Add two minutes to a meeting,” Giglio says. “Ask: Who used AI this week? What did you try? What’s not working?” This type of consistent follow-up, Giglio says, can turn passive curiosity about AI into real workflow implementations.
- Avoid outsourcing AI planning and implementation to tech departments. “Leadership needs to be involved,” Giglio says. “You have to sell the vision [of using AI models] or else you’ll lose the momentum.”
“You’re never going to get 100% of people on board at first,” he says. “You’ll have early adopters, skeptics and everyone in between. But if you show leadership, and embed the conversation into everyday work, it will become part of your culture.”
Use Cases for Contractors
Giglio sees promising AI use-cases for wall and ceiling firms. Here are a few areas where AI implementation can gain traction:
Estimating: Contractors can use large language models (Gemini, ChatGPT, Claude and Co-Pilot), to review scopes of work, assess bid packages, compare them to historical data and prepare initial responses. Giglio says AI can analyze 12 months of bids and identify variances and inconsistencies.
Preconstruction Decision-Making: AI can help answer the question of whether to even bid a job. AI can analyze a proposed job’s specs, location and material requirements and compare it to past wins and losses. “AI gives you a second set of eyes,” Giglio says.
Project Management and Scheduling: Once a job is won, AI models can help generate updates, summarize reports and flag patterns in scheduling and logistics.
Post-Project Wrap-Ups: Here, AI models can help summarize job cost reports, analyze labor productivity and create templates to standardize the lessons learned across projects.
Office Admin: From vendor emails to invoice summaries, Giglio says AI models can help reduce clerical tasks.
Hiring and Training: AI can be used to analyze resumes, assess job descriptions and prepare onboarding materials for new hires.
Internal Reporting and Forecasting: Here, Giglio recommends using Claude, an off-the-shelf AI model. He says Claude excels at preparing spreadsheets and generating project dashboards for management. “You can generate summaries that save time and help you focus on good decision-making,” Giglio says.
However, Giglio warns against chasing too many AI tools too soon. “One of the top barriers to adoption is that there are too many options,” he says. Instead, he advises companies to pick from a few powerful, well-supported AI models:
ChatGPT by OpenAI. Great for drafting content and everyday queries.
Claude by Anthropic, which is backed by a major investment by Amazon. Excellent for analyzing spreadsheets and reports.
Gemini by Google. Increasingly integrated with Google Workspace tools.
Co-Pilot by Microsoft. Integrated into Microsoft 365 tools. Great for drafting content and everyday queries.
“You’ll have a hard time exhausting what these models can do,” he says. “They’re powerful and well supported.”
Boosting Output Without Adding Staff
One way to reframe AI adoption is to see it as a staffing strategy. Effective AI implementation can essentially add the equivalent of 2.1 extra employees to your team without the overhead costs, the U.S. Chamber of Commerce says.
This benefit is especially useful in construction, where skilled office and project management staff are in short supply. Construction companies can use AI to free up time and improve output. In other words, project engineers, estimators and admins can do more of what matters when AI handles details of their work.
Citing the example mentioned earlier, project managers could essentially free up hundreds of hours a year by using AI models to process their jobsite walk-throughs. That’s freeing up time for higher-value tasks—improving margins, boosting morale, and strengthening your team’s capacity.
Giglio’s message to construction executives is clear: Don’t wait to get everything perfect. Start now.
“Eventually we need to say: ‘This is an expectation. This is part of our work,’” says Giglio. “No, your entire job will not be done by AI. But you can have some understanding of how to use it. You can become more proficient—now.” CD
Mark L. Johnson writes regularly about the wall and ceiling industry. You can reach him at linkedin.com/in/markjohnsoncommunications.
Zach Giglio co-founded GCM with Emma Giglio in 2019; GCM is an AI strategy and implementation agency focused on small to medium-sized businesses. The firm’s website, whoisgcm.com, says its mission is “to democratize AI knowledge.” Zach is Wharton‑certified in AI strategy, a faculty member of the U.S. Chamber’s Institute for Organization Management and a TEDx speaker. GCM’s stated goal is to embed off‑the‑shelf tools like ChatGPT and Claude into real workflows to deliver efficiency gains. Firms can “punch above their weight” by achieving “the equivalent of 2.1 extra employees” through smart AI use, the GCM website says.
