Silicon Valley cannot seem to agree on what AI will do to jobs. While some executives warn that AI will wipe out white-collar jobs, others argue that it is making workers more productive and creating demand for new roles. As layoffs continue to mount across the tech industry, the debate is shifting less from whether AI will reshape work and more toward how much disruption is actually happening today.
According to layoff tracker TrueUp, more than 142,000 tech workers were affected by layoffs in the first five months of 2026, up 33% from the same period a year earlier, with projected job cuts expected to cross 360,000 by the end of the year.
Despite those figures, OpenAI CEO Sam Altman recently reversed his stance on AI-driven job losses, saying he had overestimated the pace of disruption.
“I’m delighted to be wrong about this. I thought there would have been more impact on entry-level white-collar jobs being eliminated by now than has actually happened,” Altman said, speaking at the Commonwealth Bank of Australia's Accelerate AI Conference in May.
Similarly, NVIDIA CEO Jensen Huang pushed back against the idea that AI will reduce software engineering jobs, arguing that the technology is dramatically increasing developer productivity and, in turn, demand for engineers.
Speaking at NVIDIA GTC Taipei, Huang pointed to GitHub data showing a sharp rise in software development activity. According to Huang, the platform recorded around 500 million code commits in 2025, with that figure nearly tripling in the first few months of 2026.
“The number of software engineers is actually increasing. People talk about AI reducing jobs. Complete nonsense,” Huang said. “It’s causing more software engineers to be hired.”
He said AI is helping software engineers become far more productive and argued that a workforce with annual salaries of about $3 trillion can now generate nearly three times as much output, effectively boosting productivity to the equivalent of $9 trillion.
“The output is so incredible, people want to hire more software engineers,” he said.
Echoing a more measured view of AI’s impact on employment, Professor Balaraman Ravindran of IIT Madras said that fears of widespread job losses are understandable but often exaggerated.
“I think the fear is not unjustified, but overblown,” Ravindran tells AIM in an exclusive interview. “It’s not like AI is going to take away all jobs and make people jobless. People are simply going to become more efficient at what they do.”
According to Ravindran, AI will amplify the capabilities of workers with strong technical expertise or deep domain knowledge, allowing them to achieve outcomes that were previously difficult or impossible. He expects a future in which AI functions as a workplace companion rather than a replacement for humans.
Ravindran notes that human expertise remains essential, particularly in areas such as software development, where AI-generated outputs still require verification and oversight.
“Even today, if you ask AI to write a piece of software, you still need to understand software design, testing and engineering principles to verify that the AI has done the job correctly,” he says.
Recently, Mustafa Suleyman, chief executive of Microsoft AI, predicted that AI would automate virtually all white-collar jobs within 18 months.
Anthropic CEO Dario Amodei has also repeatedly warned that AI could eliminate up to half of all entry-level white-collar jobs and push unemployment to between 10% and 20% over the next one to five years.
The view, however, drew scepticism from industry experts.
“AI is certainly capable of handling drafts, pattern recognition, and data processing at scale, but it still lacks the judgment, accountability, and relationship-building that define meaningful professional work,” said Srinivas Padmanabhuni, co-founder and CTO of AiEnsured.
What the Numbers Actually Show
In April, AI was the leading reason cited for job cuts for the second consecutive month, accounting for 26% of all announced layoffs, according to global outplacement and executive coaching firm Challenger, Gray & Christmas. However, the link between those cuts and AI directly replacing workers is not always clear.
Several companies appear to be reallocating spending toward AI infrastructure and related investments, suggesting that some layoffs may reflect broader budget shifts rather than straightforward automation. In other words, companies may be cutting jobs to free up resources for AI initiatives, rather than replacing workers with AI systems outright.
“Many CEOs turn to layoffs to demonstrate quick AI returns; however, this disposition is misplaced,” Helen Poitevin, Distinguished VP Analyst at Gartner, previously told AIM. “Workforce reductions may create budget room, but they do not create returns.”
According to him, the distinction is important. While layoffs may free up capital for AI investments, they do not automatically translate into business value or measurable returns.
The IPO Shadow
These comments from Altman and Huang come at a time when OpenAI and Anthropic are expected to pursue high-profile IPOs. As AI companies seek support from investors and customers, some observers argue there is a growing incentive to stress productivity gains, economic growth and new job creation alongside concerns about disruption.
“You can’t go to the public market selling societal collapse,” Bob Hutchins, an AI strategy advisor, told Business Insider.
However, tech leaders agree that AI will change the way people work. Short-term disruptions are likely, particularly for routine and entry-level roles, but many believe the productivity gains from AI could drive economic growth and create new opportunities over time.
The outcome will depend on how businesses, governments and workers respond.
Many existing jobs may not disappear entirely, but the nature of those roles is likely to change as workers increasingly collaborate with AI tools.
For instance, Cognizant recently announced the creation of two new job categories — Frontier Certified Engineer and Frontier Business Operator — as part of its strategy to help organisations translate AI investments into business outcomes.
“The question every enterprise is asking is why AI results aren’t showing up yet. The answer is talent and process,” said Thirumala Arohi, Senior Vice President and Head of Learning and Development at Cognizant.
Arohi said AI has exposed 93% of jobs to automation, but much of the associated labour value remains unrealised because organisations lack the workforce structures needed to deploy the technology effectively.
Ironically, the future of work may depend less on what AI can do and more on what humans choose to do with it.
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