Getty Images; Tyler Le/BI
- Some software engineers said their reliance on AI has reduced everyday interactions with peers.
- With AI adoption in the field surging to 90%, workplace dynamics are shifting.
- At some companies, meetings are now spent on deeper discussions, rather than practical troubleshooting.
For Andrew Wang, a 33-year-old software engineer, AI has become a part of his daily routine — but it’s come at the cost of some of the casual conversations he used to have with colleagues.
Wang said the growing reliance on large language models has, at times, made teams feel more “siloed.” In the past, coworkers would regularly hash out ideas and design options in impromptu conversations, he said. Now, much of that back-and-forth happens with AI instead — leaving formal meetings for design or code reviews.
“It has fostered less of that interaction, face-to-face, to some degree,” Wang, a former Amazon software engineer who now works at an e-commerce AI startup called Fermat, told Business Insider.
Software engineering, known for its solitary nature, has been quick to embrace AI. Google Cloud released a report in September which found that AI adoption has surged to 90% among software professionals, a 14% increase from last year.
Anurag Dhingra, SVP of the Enterprise Connectivity and Collaboration Group at Cisco, told Business Insider that software engineering is on the “bleeding edge of what is possible with AI.” That means engineers are increasingly turning to agents for tasks that once relied on collaboration with coworkers, like writing or reviewing code together, he said.
“The more sophisticated these agents get, the more they start to feel like your coworkers and your teammates,” Dhingra said. “That is definitely changing this dynamic.”
Business Insider spoke with seven software engineers about how they see the technology transforming their jobs.
Less back-and-forth with peers and managers
While some engineers didn’t observe a notable change in their overall frequency of interacting with peers, every engineer Business Insider spoke to said they found themselves relying less on peers and managers for smaller questions.
“Now my first instinct is to first see if I can learn it, figure it out with AI,” said Geeta Shankar, a 25-year-old software engineer at Salesforce.
Sumanu Rawat, a 30-year-old software engineer at Walmart Global Tech said in his early days as a new grad, he would spend hours waiting for a 15-minute meeting with a mentor just to ask about undocumented processes or old code patterns.
“Now I can feed that context into Copilot and get answers immediately,” Rawat said.
While Wang and Rawat have been in the workplace for a few years, this shift could mean entry-level workers have fewer opportunities for small talk — and building meaningful connections.
Feneel Doshi, a 27-year-old software engineer at a New York-based tech startup, said he doesn’t view the adoption of AI tools as inherently isolating, but the transition has made him realize how much workplace culture “depends on deliberate connection and not just productivity tools.”
“That also means sometimes fewer spontaneous ‘hey, check this out’ moments with teammates,” Doshi said.
Collaboration isn’t dead
There are still ways that engineers can connect with peers and mentors — even if it requires more intention.
LinkedIn engineering VP for talent solutions, Prashanthi Padmanabhan, told Business Insider in the last couple of years, she’s noticed more entry-level engineers and interns getting coffee with leaders.
“They’re all probably worried about how the industry is evolving and how they should be thinking about it,” Padmanabhan said. “But I see that as a healthy trend, that they are thinking about all of this.”
Cisco’s Dhingra said the rising feeling of isolation is likely a “temporary phase,” and said it will lead to collaboration around bigger problems, like designing systems, building the right architecture, and improving user experience. Dhingra said engineers have to start thinking about system-level issues.
Some engineers told Business Insider that’s already happening. Rawat said using AI has shifted team discussions from solving practical questions like “how do we build this?” to bigger-picture questions like “what should we build?”
“In a way, the role boundaries are blurring,” Rawat said. “Software engineers are thinking more like product managers, focusing on strategy and direction in addition to just implementation details.”
Shankar said that since AI is accelerating the work, engineers can produce results at a faster pace, allowing her team to share findings more quickly. In the past, she said it might have taken her two days to complete a task that now takes her five hours.
Doshi noticed a similar trend and said it’s translated to more frequent review meetings, which has been an upside to the change in dynamics.
“The conversations we do have now go deeper,” Doshi said. “We’re debating tradeoffs, not the syntax.”
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