Over the last year, I’ve noticed that operations work inside tech companies doesn’t look the way it used to.
Teams still ship quickly. In some cases, they move faster than before. But fewer people are involved in the middle of things. A lot of things that used to require elaborate coordination now just … run. Not flawlessly, but well enough that no one steps in unless something breaks.
What’s interesting is that no one ever announces this shift. There’s no slide deck explaining a new model. It shows up in small ways instead. Teams quietly get smaller. Meetings fall off calendars and don’t come back. Work that used to belong to a specific role ends up living inside a tool. After a while, no one remembers when that happened.
How Is Automation Changing Tech Operations?
AI and automation are transforming tech operations by absorbing coordination tasks and handoffs once managed by people. Rather than just handling simple tasks, software now routes work and flags inconsistencies, shifting the operational focus from running processes to high-judgment system design and deciding where human intervention is necessary.
Automation Shows Up Quietly
When anyone discusses layoffs, they’re often framed as due to automation or AI efficiency. That explanation sounds generic, and it’s easy to tune it out. But it becomes harder to ignore when the same companies making cuts are still growing and investing elsewhere. At that point, the explanation stops feeling like temporary belt-tightening and starts to look like a more fundamental shift in how companies think about operations work
This kind of change isn’t new. Technology has always reshaped roles. What feels different now is how fast it’s happening and how much coordination work is being pushed into automated systems rather than people.
AI tools aren’t just handling tasks. They’re replacing entire chains of handoffs. When software can route work, check inputs, flag inconsistencies and escalate decisions to the right owner automatically, there’s less need for someone to manage that flow day to day. That doesn’t mean the old role was unnecessary. It means the system absorbed it.
Operations have always been exposed to this kind of shift. A lot of the job is about dealing with friction, tools that don’t integrate well, teams that move at different speeds and data that’s hard to access. As those gaps close, the work changes shape.
I’ve seen this happen in very ordinary ways. A weekly ops sync gets skipped once, then twice; eventually, no one bothers to reschedule it. A report still technically exists, but everyone looks at the dashboard instead. Nobody decides to stop doing the work. It just stops mattering.
What replaces that work isn’t the removal of operations altogether. It’s concentration. Fewer people own a larger share of the system. The expectation shifts from running processes to deciding how those processes should work in the first place.
Software now handles a lot of the tasks that used to define operations roles: tracking handoffs, updating documents and preparing recurring updates, among others. What’s left is higher-judgment work: deciding what should be automated, how systems interact and where human intervention is still necessary when something doesn’t fit neatly.
How Operations Roles Are Changing
There’s also a practical reality here. Once an automated process is clearly faster and more reliable than a manual one, it’s hard to justify keeping the manual version around. Low-code tools have made this even more visible since people outside of operations can now build workflows on their own. The result is fewer roles focused purely on coordination. Not because coordination isn’t valuable, but because its value is easier to encode.
None of this happens all at once inside an organization. It unfolds gradually: fewer roles get posted, fewer people are included by default and processes stop needing dedicated owners because they no longer require hands-on management.
For people working in operations, this shift shows up in very practical ways. Roles are scoped differently than they were a few years ago. Certain skills are rewarded more visibly, while others stop appearing in job descriptions altogether. What used to be considered core operational work is increasingly bundled into tools or platforms rather than assigned to a person.
The open question now isn’t whether automation will continue to reshape operations roles. That’s already happening. The question is which parts of the work still require a human in the loop once coordination itself is no longer the bottleneck.
In practice, the work that tends to hold up is less about managing process and more about shaping it. That includes deciding how a workflow should behave when inputs are incomplete, when priorities conflict, or when edge cases don’t fit neatly into predefined logic. It also includes making calls about where automation actually improves outcomes and where it creates new failure modes.
Those decisions are harder to standardize. They depend on context, trade-offs and an understanding of how systems behave over time. As coordination becomes cheaper and easier to automate, that kind of judgment becomes part of operations work that’s hardest to replace.
From Execution to Judgment
That doesn’t mean everyone needs to become deeply technical. But it does mean prioritizing an understanding of how systems work end to end, and developing the ability to evaluate whether automation is actually improving outcomes or just speeding up broken processes. Operations roles that add value in this environment tend to be less about execution and more about deciding what execution should look like.
Technology has always moved faster than people would like. What’s different now is how quietly that change is happening.
