‘Godfather of AI’ Warns AI Is Coming for More Jobs in 2026

What Happened

Geoffrey Hinton, the Nobel Prize-winning computer scientist whose work laid the foundation for modern artificial intelligence, told CNN during a recent interview that AI will replace a substantial number of jobs in 2026 as the technology continues its rapid advancement.

Hinton, who left Google in 2023 to speak more freely about AI risks, says the technology’s capabilities are roughly doubling every seven months.

According to Hinton, tasks that currently require a month of human labor in fields like software engineering will soon be completed by AI in a fraction of the time. This acceleration means AI systems are gaining ground faster than he initially anticipated, particularly in reasoning abilities and, most troubling, the capacity to deceive humans in pursuit of programmed goals.

The employment data support his concerns. Nearly 78,000 tech job losses in the first half of 2025 were directly attributed to AI. Job openings have dropped 30% since ChatGPT launched in late 2022, as major companies make dramatic cuts: Chegg eliminated 22% of its workforce after students switched to free AI tools, while Intel announced 21,000 layoffs as it pivots to AI chip production.

Why It Matters 

Rather than targeting manufacturing or routine clerical work, generative AI threatens cognitive tasks performed by knowledge workers, jobs that have traditionally been considered secure and well-compensated.

Companies pouring trillions into AI infrastructure are now seeing rapid worker replacement as the most direct route to profitability. Hinton’s warning is stark and immediate: AI will soon unleash massive unemployment while channeling unprecedented profits to a select few, sharply accelerating inequality.

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Current automation risk assessments reveal widespread exposure across sectors. Data entry and administrative support roles face near-complete automation. Retail cashiers are experiencing significant job losses as self-checkout systems expand.

The legal profession isn't immune either, as paralegals face substantial automation risk over the next few years. Financial services operations are increasingly being handled by AI systems, particularly in basic transactional work.

In its Future Jobs Report 2025, the World Economic Forum projects 92 million job losses by 2030, along with 170 million new positions, for a net gain of 78 million jobs. However, 77% of AI-related jobs require master’s degrees, which is an educational barrier that means displaced workers in traditional roles face significant obstacles to transitioning into emerging positions.

While Hinton acknowledges AI’s potential benefits in medicine, education, and climate research, he argues society is drastically underinvesting in safety measures and governance. He’s particularly critical of the tech industry lobbying against regulation, calling it crazy, given the risks involved.

How It Affects You

Adapting now is imperative for anyone in the workforce, as individuals must develop skills AI cannot easily replicate. This includes creativity, emotional intelligence, strategic thinking, and interpersonal negotiation skills, which are increasingly vital for survival. Those who act swiftly to manage and direct AI systems will be best positioned, while hesitation risks obsolescence.

Beyond personal employment, Hinton predicts AI will concentrate wealth among a small elite and reduce opportunities for most workers unless there is policy or corporate intervention.

Some economists dispute Hinton’s timeline, arguing that past technological revolutions played out over decades, not months. Yet the broader labor market has not shown all-out disruption in the 33 months since ChatGPT’s release. Still, urgent warning signs are clear: employment growth in marketing consulting, graphic design, administrative work, and call centers has rapidly slipped below historic norms.

The critical difference now is scope and speed. While previous automation altered tasks and allowed for gradual adaptation, today’s AI can wipe out entire job categories quickly, compressing adaptation timelines and threatening to overwhelm traditional retraining systems almost overnight.

The central question is not if, but how AI-driven change unfolds, and if it will drive widely shared prosperity or deepen inequality by replacing millions of knowledge workers. With policy choices now shaping outcomes, Hinton’s warnings indicate an urgent need to address the unprecedented pace and reach of AI’s threat to traditional employment.