By Kevin Eison, Director of Technology Strategy, Microsoft
Time keeps on slipping
I live and breathe AI every day at Microsoft, helping customers and partners figure out where it actually fits. AI is moving faster than any shift I have worked through. Faster than anyone has lived through. Households took about seventy-five years to adopt the telephone. The personal computer gave office workers close to a decade after it hit their desks in 1981. The web gave businesses five or six years after it went commercial in 1995.
AI is giving teams months. That is why I treat it as a cultural shift first.
It starts with your people.
Fear: the first great hurdle
There’s one question at the forefront of everybody’s mind right now: Is AI going to replace me?
That fear is the biggest obstacle you’ll face.
Of all the industries I work in, the physical ones have the most protection, and construction has more than most. There are already onsite robots that handle work that does not require heavy lifting. What they cannot do is drive a nail, run a nail gun, or make the call on how the day should run. That still takes a person. Even a two-legged robot that could carry material to the corner would still need someone directing the higher-level work.
Those robots are going to get better at moving material around a site (sheetrock and the like) so people are freed from the repetitive hauling. The role does not disappear. It moves up. On a crew that puts three people on one site today, the direction this is heading lets each of them run their own site as the foreman, with agents handling the software and robots moving material. The company takes on more work with the same team. You did not remove a headcount. You made that headcount more profitable.
New tools, new tasks, new growth
Almost any job has two layers. There is the repetitive layer, the busy work that keeps things moving. And there is the layer that takes thought and judgment. What AI does best right now is take away the mundane so you spend more of your time on the part only you can do.
Accounts payable is a clean example. Everyone has seen optical character recognition (usually referred to as OCR), where you scan a document and it lands on your screen to clean up. What is different now is that the scan gets checked against a template. The template confirms whether everything was captured and flags it on the spot, telling the clerk they missed a field and need to fill it in. That alone takes hours of data entry off an AP team’s day.
The bigger change is what happens next. The captured data flows straight into the job cost system, and that system flags when the job is trending the wrong way and shows where to adjust. Now the clerk gets data back fast enough to act on it. They can catch a problem while there is still time to fix it, relay it to the field, and make the change in real time. Their role becomes keeping the job efficient and profitable, and they can point to exactly where they saved time, where they caught a problem, and where they made the company money.
That is powerful.
The catch is that the company has to decide what its people do with the time AI gives back. The ones that get it right grow the work and grow their people at the same time.
What an AI cultural shift looks like onsite
When you walk onto a job site, AI scans the whole site from a regular camera and checks that the materials are where the plan says they should be. It feeds back to a database, confirms the site is ready, and clears the crew to come in. That did not exist two or three years ago.
The equipment does its own version of this. The bulldozer or the compactor tracks its own miles and fuel, and how efficiently it is moving, and all of it feeds back to the team. The operator sees how today should run compared to yesterday, based on the data coming off the machine. The operator's day gets easier without changing a thing, because everything around the operator is more efficient. The impact reaches the person in the hard hat who never works with the technology directly.
The future is not far
How every person works has changed in the last two years. And it will change again in the next two.
I can tell you the direction. AI keeps getting more woven into the day, no matter what you do or where you are. Today most of us are at the first phase, where you ask and it answers. Next come agents that get the work ready for you. The phase we are building toward is the one where you hand the agents a goal and a set of processes and they run with it. On a site that looks like materials staged before the crew arrives, once you have set the plan for the week. That is where this goes.
What I cannot tell you is where you will be standing when it gets there. It depends on how you implement it into your culture.
My advice is to start now. Pick one or two use cases. Put your business leaders and your technical leaders in the same room. Grow your people alongside the tools, because a company that wants to grow also wants its people to grow with it.
Our great-grandparents had over seventy years to make peace with the telephone. Your team has months. That is not a reason to wait for the technology to settle, because it will not settle. It is the reason to start now, while the climb is still short.
Hear more from Kevin Eison and leaders from NVIDIA, Snowflake and Trimble in the “Beyond the Hype” AI webinar recording.
About the author
Kevin Eison is Director of Technology Strategy at Microsoft, where he helps customers and partners in the AECO and geospatial industries put AI to practical, everyday use. His work focuses on treating AI as an enterprise discipline rather than a bolt-on, grounded in clear business outcomes, secure data governance and responsible AI practices built on platforms like Microsoft Azure. He partners closely with organizations like Trimble to bring those capabilities to both the job site and the back office.
