Most contracting firms have at least one person who has figured out how to use AI well. Maybe it’s an estimator who cut his takeoff prep time in half. A project manager who uses it to draft RFIs and correspondence. A BD person who stopped staring at blank screens when it’s time to write a proposal. These people exist in firms across the industry, and they are getting real value out of the tools they’ve learned.
The problem is that what they know usually stays with them.
It doesn’t spread to the rest of the team. It doesn’t get built into a workflow. It doesn’t become part of how the company operates. One person figures something out, maybe mentions it in passing, and then goes back to their desk. Meanwhile, three offices down, someone else is doing the same task the slow way they’ve always done it.
This is what you might call the enthusiasm gap, and it is one of the more expensive quiet problems in the industry right now.
It is not a technology problem. The tools exist. Most firms already have access to them. The gap is structural. It lives in the space between individual initiative and company-wide capability, and closing it requires more than forwarding a ChatGPT link to your team in a group text.
The gap shows up in a few predictable ways. Firms where one or two people are running ahead with AI while the rest of the organization waits. Firms where there has been a demonstration or a lunch and learn, some genuine excitement in the room, and then nothing changed the following Monday. Firms where leadership is interested in AI but hasn’t defined what that actually means for the way work gets done. Firms that have bought a tool and called it an AI strategy.
None of this is a failure of intelligence or ambition. It reflects something more straightforward: organizations are complicated, people are busy, and turning individual behavior into institutional practice takes deliberate effort. That effort doesn’t happen on its own.
What makes this worth taking seriously right now is the competitive dimension. The gap is not uniform across the industry. Some firms are moving past the experimentation phase. They are building repeatable workflows around AI, training their people with intention, and starting to show up differently in business development, operations, and project execution. For those firms, AI is no longer a curiosity. It is becoming a capability.
For firms still stuck in the phase where one person knows something and nobody else does, the gap will widen. Not dramatically, not overnight, but consistently. Over time, the firms that made AI institutional will carry real advantages in speed, output quality, capacity, and how they present themselves to owners and GCs.
The good news is that closing the gap does not require a massive investment or a years-long transformation initiative. It requires leadership that takes the problem seriously and a structured approach to building AI literacy across the team. That means defining where AI fits in your actual workflows, not in the abstract. It means giving people the context and the training to use tools with confidence. It means creating enough shared language around AI that the person who figures something out can actually transfer that knowledge to the people next to them.
The firms that move from enthusiasm to capability will not all be the largest firms or the best-funded ones. They will be the ones where leadership decided that individual momentum was worth building into something the whole organization could use.
That decision is available to any firm willing to make it.