A former Google executive warned that artificial intelligence will plunge society into more than a decade of severe disruption and hardship as it eliminates many white-collar jobs — and the “hell” will begin as early as 2027.
Mo Gawdat, who left Google X as its chief business officer in 2018 and has become a popular author and public speaker, painted a grim picture of widespread job losses, economic inequality and social chaos from the AI revolution.
“The next 15 years will be hell before we get to heaven,” Gawdat told British entrepreneur Steven Bartlett on his “Diary of a CEO” podcast on Monday.
Gawdat, 58, pointed to his own startup, Emma.love, which builds emotional and relationship-focused artificial intelligence. It is run by three people.
“That startup would have been 350 developers in the past,” he told Bartlett in the interview, first reported by Business Insider.
“As a matter of fact, podcaster is going to be replaced.”
Gawdat specifically warned that “the end of white-collar work” will begin by the late 2020s, representing a fundamental shift in how society operates.
Unlike previous technological revolutions that primarily affected manual labor, he argues this wave of automation will target educated professionals and middle-class workers who form the backbone of modern economies.
The Egyptian-born tech whiz, who was a millionaire by age 29, believes this massive displacement will create dangerous levels of economic inequality.
Without proper government oversight, AI technology will channel unprecedented wealth and influence to those who own or control these systems, while leaving millions of workers struggling to find their place in the new economy, according to Gawdat.
Beyond economic concerns, Gawdat anticipates serious social consequences from this rapid transformation.
Gawdat said AI will trigger significant “social unrest” as people grapple with losing their livelihoods and sense of purpose — resulting in rising rates of mental health problems, increased loneliness and deepening social divisions.
“Unless you’re in the top 0.1%, you’re a peasant,” Gawdat said. “There is no middle class.”
Despite his gloomy predictions, Gawdat said that the period of “hell” will be followed by a “utopian” era that would begin after 2040, when workers will be free from doing repetitive and mundane tasks.
Instead of being “focused on consumerism and greed,” humanity could instead be guided by “love, community, and spiritual development,” according to Gawdat.
Gawdat said that it is incumbent on governments, individuals and businesses to take proactive measures such as the adoption of universal basic income to help people navigate the transition.
“We are headed into a short-term dystopia, but we can still decide what comes after that,” Gawdat told the podcast, emphasizing that the future remains malleable based on choices society makes today.
He argued that outcomes will depend heavily on decisions regarding regulation, equitable access to technology, and what he calls the “moral programming” of AI algorithms.
“Our last hurrah as a species could be how we adapt, re-imagine, and humanize this new world,” Gawdat said.
Gawdat’s predictions about mass AI-driven disruption are increasingly backed by mainstream economic data and analysis.
Anthropic CEO Dario Amodei has warned of a “white-collar bloodbath,” predicting that up to half of all entry-level office jobs could vanish within five years.
The World Economic Forum says 40% of global employers expect to reduce staff due to AI, and Harvard researchers estimate that 35% of white-collar tasks are now automatable.
Meanwhile, Challenger, Gray & Christmas reports that over 27,000 job cuts since 2023 have been directly attributed to AI, with tens of thousands more expected.
Goldman Sachs and McKinsey project a multi-trillion-dollar boost to global GDP from AI, but the IMF cautions that these gains may worsen inequality without targeted policy responses.
Analysts from MIT and PwC echo Gawdat’s fears of wage collapse, wealth concentration, and social unrest — unless governments act swiftly to manage the transition.
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