As conversations around AI continue to fuel fears of job losses across the tech industry, many believe that more powerful AI tools will eventually mean fewer engineers are needed. But Nikesh Arora, the CEO of Palo Alto Networks, thinks that assumption misses the bigger picture.
Speaking during a recent episode of Hard Fork, Arora pushed back against the idea that higher AI-driven productivity automatically leads to smaller teams. Instead, he argues that increased productivity can just as easily expand what companies choose to build, rather than reduce headcount.
Here’s a breakdown of what he said about AI replacing engineers.
/1. AI Could Increase Demand for Engineers, Not Reduce It
With AI tools becoming more capable with each upgrade, many people assume these developments will result in fewer workers. However, Arora thinks it is a “fallacy” that AI productivity gains automatically mean companies need fewer people.
“No, I need more,” he said, adding that, “The fallacy is that organizations are going to get 30, 40, 50, 60% more productive from a development perspective and a testing perspective, so we need less people.”
This challenges one of the biggest fears in tech today — the idea that higher productivity will naturally lead to layoffs.
/2. Most Tech Companies Already Have More Work Than They Can Handle
According to Arora, the bigger issue is not a lack of work but a lack of people to execute ideas fast enough.
“Every technologist that you talk to has a feature request list which is longer than their arm,” he said, pointing to the fact that many organizations already operate with product roadmaps stretching six to twelve months ahead because development work takes time and resources.
“As we create more capacity, we're gonna try and fill the technological backlog,” he noted, suggesting that AI will first be used to unlock delayed projects and unfinished ideas rather than replace employees outright.
/3. AI-Driven Layoffs May Actually Be About Reorganizing Teams
Perhaps Concerns about AI replacing workers may be overstated, or at least more complicated than they first appear. As Nikesh Arora suggests, recent layoffs may have less to do with eliminating engineers and more to do with reshaping teams for the AI era.
He explained that some companies cutting headcount are not necessarily reducing technical talent, but reallocating resources to hire workers with newer AI-related skills. “Everybody who’s out there saying, ‘I’m reducing my headcount by seven percent or fifteen percent or twenty percent,’ I think they’re just creating capacity,” he said.
“That capacity allows me to hire more people and make room for people that I need who have the newer skill set,” he added.
/4. Companies Will Need Workers With “Newer Skill Sets.”
As opposed to how many people currently interpret recent developments in AI, from layoffs to company restructurings and buyouts, a major part of Arora’s argument focused on transformation rather than outright replacement. He believes the AI era will favor engineers who can adapt to changing technical demands, with companies increasingly making "room for people who have the newer skill set.”
This aligns with what companies like General Motors are doing, where they are placing greater value on AI talent alongside the specialized skill set.
/5. AI Is Part of a “Decade-Long Transformation”
The recent outlook on AI has largely been dominated by fears of job losses, automation, and uncertainty across the tech industry. But Arora views the rise of AI through a much wider lens — one that goes beyond short-term hiring concerns.
“We're dealing with a tsunami of a desire to transform. I think we're in a decade-long transformation of business ahead of us,” he explained
Considering the pace at which AI is already reshaping industries, that perspective echoes how many tech leaders now compare the technology to earlier shifts like the rise of the internet, smartphones, and cloud computing, innovations that eventually transformed not just the tools people used, but the kind of skills companies valued most.
David Adubiina
