AI is eliminating routine work—but the real change is who takes responsibility when automation ends.
By Carter Barczak
It appeared in Cityview Magazine, Vol. 42, Issue 2 (March/April 2026)
Most conversations about creative intelligence and job loss begin the same way. They focus on what is disappearing. Analysts, planners, customer support jobs, entry-level technical jobs – the job is always full on the screen and follows a repetitive pattern. And that concern is not lost. I saw it happening in real time. I’ve seen jobs quietly removed after processes have been automated, jobs folded into systems, and teams told “the process is working really well now.” That fact is not stable. But it is not enough either.
What makes people get overlooked is what’s going on at the same time. While AI is cutting jobs at the top, it’s creating a new set of opportunities at the bottom – and not just at the corporate level, but at the individual level. The biggest change is not that jobs are going away. It’s that people are now able to automate parts of their work and use that version to get the work done that matters.
That is the real inflection point.
The winners in the next phase will not be people who avoid AI or complain about it. They are the ones who will use it to eliminate low-value work from their day, position themselves closer to making decisions, and be difficult to replace in the process.
By the time most people realize that their work is being automated, it’s often too late. But what gets lost in the noise is that the same job-elimination tools are quietly turning individual workers into redundant ones. I experienced this change firsthand while learning tools like Power Automate. It became clear how much work there is because “that’s how it’s always been done.” Once it’s automated, those jobs don’t disappear – they just stop needing constant human attention.
For the first time, one person can automate parts of his work that previously justified all positions. Jobs that used to require junior researchers, coordinators, or support staff can now run quietly in the background. It doesn’t just change the reading options. It changes who becomes important within the organization.
If part of your job is repetitive, manual, or rule-based, AI will give you a choice. You can wait for the task to be automated from your bottom, or you can manage it yourself and restore the time in important tasks. That transition – from execution to ownership – is where new jobs are created.
This distinction is important because AI is very good at eliminating the middleman. Not up and not down, but the layers are built around the assumption of execution. Reporting tasks, static analysis, manual ordering, and heavy work are the easiest to control because they produce fixed results without real ownership. When software makes that faster and cheaper, organizations will respond in the same way they always have: pressure.
What AI still struggles with is accountability. Nothing will come out. It doesn’t take risks. It doesn’t do the courts if the assumptions are conflicting. And as automation increases, so does the importance of people.
The change becomes easier to understand if you look outside the screen.
I see it play out every day in my own work around large-scale data-center development – the physical backbone of the AI economy. These buildings are not invisible. A single data center campus can span over 100 hectares, draw more electricity than a city the size of Knoxville, and represent billions of dollars in combined projects and infrastructure.
Automation doesn’t eliminate work – It redistributes it.
In advanced construction, data centers can include thousands of workers on the floor at once – electricians, mechanic tradesmen, concrete workers, steel workers, dispatch teams, security managers, and project planners all working together under tight schedules and unforgiving constraints.
Once the infrastructure is in place, human involvement does not end. Infrastructure engineers, operations teams, maintenance specialists, and network personnel remain connected for life. These environments are highly automated, but not autonomous. Software can help predict demand, optimize plans, and track equipment. It cannot decide how much risk is acceptable. It cannot navigate sales delays, permitting problems, weather disruptions, or equipment failures without human intervention. And if something goes wrong, he cannot own the consequences. That’s the part of the automatic conversation that most people miss.
Automation doesn’t eliminate work – it redistributes it. It reduces the amount of clean execution required and increases the value of collaboration, control, and ownership.
This pattern shows any work that deals with the physical world – energy, buildings, health, creativity, materials. The closer this work is to uncontrollable results, the more difficult it is to automate completely.
That’s why most of the career advice around AI is falling apart. Learning materials are helpful, but they are not enough. The real opportunity comes from understanding where automation makes sense – and where human control still matters.
This is where people have more power than they realize. AI gives you the ability to eliminate low-value parts of your work yourself before someone else does it for you. Not by waiting for approval or making a big announcement, but by quietly doing repetitive work that doesn’t require judgment and using that time to focus on the work at hand.
The shifts aren’t flashy, but they connect. Over time, the people who do them become hard to replace because their value is not tied to the amount of work they produce. It depends on the situation, control, and ownership.
AI will take away jobs. That part of the story is true. But it will also reveal something deeper: many jobs were there to do work that wasn’t really his.
Because AI doesn’t replace humans doing the work. It replaces people who never had it.
#Automation #Jobs #story
