Artificial Intelligence is advancing rapidly, reshaping the world of work in ways never seen before. Roman Yampolskiy, a computer science professor at the University of Louisville and a leading AI safety expert, has warned of a possible future where AI causes mass unemployment affecting 99% of workers worldwide by 2030. He spoke about this alarming prediction on the popular podcast “The Diary of a CEO,” highlighting how soon machines might replace nearly every human job.

Rapid rise of AI and impending job losses

According to Professor Yampolskiy, artificial general intelligence (AGI), which refers to machines capable of human-like intelligence and decision-making, could arrive as soon as 2027. Once AGI is developed, he said, automation will no longer be confined to computer-based tasks but will also extend rapidly to physical labour through humanoid robots, predicted to be just five years behind AGI. In his words, “First, anything on a computer will be automated. And next, humanoid robots are maybe five years behind. So, in five years, all physical labour can also be automated.” This means that nearly every type of work—from office jobs to manual labour—could disappear within a very short period.

He explained that this process would lead to unprecedented unemployment levels far surpassing anything experienced before. “We’re looking at a world where we have levels of unemployment we’ve never seen before. Not talking about 10 per cent unemployment, which is scary, but 99 per cent,” Yampolskiy warned. He stressed that little resistance to this change would come from workers or professionals themselves, as many still underestimate the speed and extent of AI’s takeover. Even professions once considered safe, such as drivers, professors, podcasters, and skilled craftsmen, could be replicated by AI systems trained on massive datasets.

AI’s Impact Across all Sectors

The professor’s warning echoes concerns of other prominent figures in artificial intelligence. Geoffrey Hinton, often called the “Godfather of AI,” recently asserted that AI will replace everyone in white-collar jobs and doubted that new jobs will emerge to offset those lost. Similarly, Anthropic CEO Dario Amodei projected that half of all entry-level white-collar jobs could vanish within five years, leading to unemployment rates rising significantly.

For India, with its large and diverse labour market, the implications are serious. Many sectors such as IT services, call centres, transportation, and manufacturing, already show signs of automation and AI integration. While AI-driven chatbots and automation save businesses billions annually, millions of workers performing routine or even skilled tasks face growing risk of displacement. The possibility of humanoid robots taking over physical jobs like delivery, factory work, and repair within the next decade adds further challenges for India’s workforce.

Studies further show that while some new AI-related jobs like prompt engineers, AI ethics officers, and human-AI collaboration specialists will emerge, the vast majority of these require advanced skills and higher education, creating a skills gap. This leaves millions vulnerable, especially in developing countries, where reskilling infrastructure is still limited.

Urgent Need for Policy and Societal Shifts

Professor Yampolskiy highlights that the looming crisis is not just economic but existential for humanity. With AI providing “trillions of dollars” of free cognitive and physical labour, businesses might find it illogical to pay human workers, drastically shrinking job opportunities. He warned that societies currently lack sufficient plans or “Plan B” to cope with such a massive displacement of labour.

To counter this, experts suggest rethinking the fundamentals of work and income. Concepts like universal basic income (UBI) are gaining attention as potential buffers for populations that may remain unemployed despite ongoing technological progress. Education systems need urgent reform to focus on creativity, emotional intelligence, ethical reasoning, and lifelong learning rather than just job preparation, aiming to equip people to collaborate with AI effectively.

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