Alok Chanani is the co-founder and CEO of BuildOps, a software platform for commercial and industrial service contractors. The views expressed here are solely those of the author.

The most noteworthy phenomenon in the current AI field is not happening in Silicon Valley, but in a server room in Dallas. There, a second-year technician diagnosed a chiller fault in just a few minutes, a task that previously required experience that existed only in the mind of a 20-year veteran employee.

While the tech world is still debating whether AI will replace jobs, the skilled trades industry has already shown the world what AI is truly good at today—not replacement, but capability multiplication. This distinction is crucial.

AI's Blind Spot

I am deeply involved in the discussions around AI and clearly see two camps forming.

One camp is full of anxiety, worried that AI will hollow out entire functions and possibly even destroy entire companies.

The other camp focuses on using AI to do the same work faster and cheaper.

Both views miss the bigger picture. A third scenario is unfolding in reality, developing so rapidly that by the time most leaders realize it, the gap will be difficult to close. AI is not about shrinking existing scale, but expanding possibilities. The real question is not how to do the same work with fewer people, but what becomes possible when everyone on the team possesses capabilities that didn't exist a year ago.

If you haven't asked this question yet, you are building your strategy based on outdated assumptions about your team's capabilities.

How the Skilled Trades Apply AI

I co-founded BuildOps, a platform for commercial contractors—contractors who must be physically present at construction sites to ensure facilities operate properly. No amount of AI can install a chiller or pull wire through conduit; this work is inherently dependent on people.

Because of this, these workers found the best use of AI in construction earlier than other parts of the industry.

Since the core of their work is always physical labor, they never agonized over 'Will AI replace us?' Instead, long before AI became widespread, they were asking: 'How do we get this job done?' And answering that question is exactly what AI is good at today, giving them a clear advantage in finding the best ways to build.

This clarity, forced by the nature of the work, is exactly what all industries—not just construction—need right now. Once you stop worrying about what AI might take away and focus on what it can bring, you can make smarter decisions in any industry.

The 'Can-Do' Narrative in Construction

When you see the reality on the ground, the 'replacement' narrative falls apart.

Last fall, we surveyed hundreds of commercial contractors, and the results showed: 78% believe AI can improve how they work; 80% believe AI will be crucial for staying competitive in the next three years; 81% expressed confidence in adopting AI. These people are not preparing for layoffs; they are preparing to do more.

This pattern is emerging everywhere: small, focused teams are attempting and completing tasks that were impossible just 18 months ago. Not because they got bigger, but because the capabilities of each person on the team have been enhanced.

AI is changing the boundaries of what a small, focused team can realistically attempt. This is evident in every industry, but especially among teams on construction sites.

Beyond Cost Cutting

The easiest way to use AI is as a cost-cutting lever: have it generate summaries, use it to save a few minutes in workflows, and then celebrate that incremental gain.

The harder but more important approach is to view it as a capability leap.

If you enter this era with the question 'How many people can I cut?', you will only end up with a smaller company. You might hit your profit margin targets this quarter, but in the coming years, you'll wonder why market share is being taken by competitors you've never heard of.

If you enter with the question 'What can my employees now do that they couldn't before?', that leads to a completely different trajectory. This is how 40-person teams start operating with the force of 100.

But this only happens if you are willing to redesign the work itself. Job descriptions, team structures, and even who you hire first will change when you assume every employee has access to an ever-improving skill set.

Stop measuring AI by what it 'removes,' and start measuring it by what it 'unlocks.'

The skilled trades reached this conclusion earlier than most because they had no choice. When someone has to fasten a bolt on a job site, you can't dwell in replacement fantasies for long. You are forced to confront the more interesting question: How can this person do this job more effectively when I put these additional AI tools in their hands?

You should be asking the same question now. Because if you only count what AI might take away, you will miss the most important part: what your employees are suddenly able to do.