In an exclusive interview with CanadianSME Small Business Magazine, Andrew Hansen, Co-Founder of Site, and Josiah Shelley, Co-Founder of ForwardPath AI and SiteAI, break down what AI adoption actually looks like inside Canada’s construction, manufacturing, and engineering sectors.This conversation cuts through the noise surrounding artificial intelligence and focuses on execution.
Andrew Hansen is a Partner at SiteAI, and utilizes his unique perspective from working on-site in the natural resources and construction sectors to inform an understanding of the industrial market and how to drive results. He is also the founder and CEO of Site, a specialized consulting services group that solves business problems, builds brands, and drives growth for the construction, manufacturing and resource sectors.
Josiah Shelley is a Partner at SiteAI, and is driven by a desire to be very practical and empower businesses through effective AI solutions. He is also the CEO of ForwardPath AI, an AI consulting firm that builds custom AI solutions for the industrial sector.
Interview By Maheen Bari
For Andrew Hansen: You’ve spent years inside Canada’s industrial sector—on construction sites, in manufacturing, and across engineering teams—what does AI adoption really look like on the ground today, and how does that differ from the glossy narratives most leaders are hearing about AI?
From what we see working across Canada’s industrial sector, AI adoption is much more practical than the headlines suggest. Most construction, manufacturing, and engineering teams aren’t experimenting with models, they’re usually occupied trying to solve everyday problems: how to find information faster, draft proposals, or search through technical documentation.
The reality is that many companies have already purchased AI tools, but haven’t figured out how best to embed them into daily workflows. Leadership often hears that AI will transform everything overnight, while teams on the ground are still figuring out where it actually helps and where it doesn’t. What that creates is fragmented adoption: a few employees experiment with the tools, others ignore them entirely, and the organization doesn’t see much operational change.
The companies making real progress treat AI the same way they treat any other type of operational technology. They test it inside real workflows and from there they train their teams, and deploy solutions that solve specific problems.
AI becomes valuable when it’s tied directly to how work already happens on job sites, in plants, and inside engineering teams.
For Josiah Shelley: You’ve said AI has a “trust problem” in industrial settings, especially when companies roll out tools like Copilot without training or workflow changes—what do you mean by that, and what does it take to close the gap between what leadership thinks is happening and how people are actually working?
What we’re really talking about is the gap between leadership expectations and how work actually happens on a daily basis. A lot of organizations roll out tools like Copilot and assume adoption will follow automatically. Realistically if people haven’t been trained and if workflows haven’t changed – and if no one has explained what good AI usage looks like – the technology never becomes part of the job.
We’ve walked into organizations that invested heavily in AI licensing, but employees were still using consumer tools on personal devices because the licensed system wasn’t integrated into how they do their work. That disconnect is where the trust problem shows up. Workers don’t trust tools that feel disconnected from their workflows, and leadership often doesn’t have visibility into what’s actually happening on the ground.
Closing that gap requires more than technology. It means training teams, embedding AI inside the systems they already use, and demonstrating practical value in real work, not just talking about the potential.
For Andrew Hansen: From your State of AI research and client work, what is the most common mistake you see organizations make when they start their AI journey—and what’s the key difference between a company that builds true AI capability and one that just buys AI tools?
We’re seeing organizations buy AI tools before they’ve decided what capability they want to build. Companies hear about AI, allocate budget for licenses, and assume transformation will follow automatically. In practice, that rarely happens.
Across the industrial sector there’s a widening gap between companies that are building real AI capability and those that are simply adding tools to their software stack. The difference doesn’t come down to access, because everyone has access to the same platforms. The difference is how organizations approach adoption.
Companies that succeed focus on training their teams, identifying specific operational use cases, and deploying solutions that fit existing workflows. They treat AI as a capability-building exercise. On the flip side of that coin, the companies that are struggling tend to focus primarily on the technology itself. They launch pilots or buy licenses, but if these aren’t accompanied by sufficient training or clear workflows, the tools rarely translate into operational improvement.
In industrial environments – just like most other environments – AI adoption works best when it’s tied directly to solving real business problems.
For Josiah Shelley: SiteAI was formed by combining Site’s sector expertise with ForwardPath AI’s technical delivery, with solutions built on Microsoft’s platform and integrated into tools like Teams and SharePoint—what does this partnership let you offer that a generic AI consultant or big-name firm typically can’t?
The biggest difference is that SiteAI was built specifically for the industrial sector. It combines Site’s experience working directly with construction, manufacturing, and resource companies with ForwardPath AI’s expertise designing and deploying custom AI systems.
Most organizations are forced to choose between two kinds of partners. You have large consulting firms that understand technology but don’t always understand the realities of industrial operations. Then you have industry consultants who know the sector but don’t have the capability to actually build and deploy AI systems. Our model actually brings those two things together.
One of the benefits of developing our solutions on Microsoft’s platform, and integrating directly with tools like Teams and SharePoint, is that we can bring AI into the systems that companies already use every day. That means the tools aren’t sitting off to the side, they’re embedded directly into the flow of work.
For industrial organizations, that’s what turns AI from a concept into something that actually changes how work gets done.
For both: For a Canadian construction or manufacturing company that wants real results in the next 90 days, where should they start—what concrete steps should they take first to identify a high‑impact use case, build trust with their teams, and get a working AI tool into their secure environment instead of another pilot that goes nowhere?
For companies that want meaningful results in the next 90 days, the starting point isn’t buying more technology—it’s identifying a single operational problem where AI can create immediate value.
In industrial environments, that might be something like automating proposal development, improving search across technical documents, or building a conversational assistant that helps teams navigate internal knowledge. These are practical use cases where AI can remove friction quickly.
Once the use case is clear, the next step is working directly with the teams who will use the tool. That means mapping their workflows, identifying where AI can support them, and providing training so people understand how the system fits into their work.
The goal isn’t another pilot, it’s deploying a working solution inside the company’s secure environment and integrating it into tools employees already use. When staff see AI solving a real problem in their daily work, adoption follows quickly—and that momentum continues to simplify each future deployment.
Disclaimer: The views and opinions expressed in this interview are those of the interviewee and do not necessarily reflect the official policy or position of CanadianSME Small Business Magazine. Our platform is dedicated to fostering dialogue and sharing insights that inspire and empower small and medium-sized businesses across Canada.
