‘AI is a tsunami for jobs’: Experts warn of mass white-collar cuts as calls grow for AI windfall tax

Alap Shah, co-author of the viral Citrini Research report that triggered an “AI scare trade” selloff on Tuesday, has urged governments to consider taxing artificial intelligence to cushion the economic fallout from large-scale job displacement. In a Bloomberg TV interview on Monday, Shah, CIO at Lotus Technology Management, warned that rapid advances in artificial intelligence could significantly disrupt labour markets and consumption-driven economies such as the US. “The smarter AI gets, the more jobs it can replace,” Shah said.

His remarks come after a weekend research note from Citrini outlined disruptive AI scenarios, sparking a selloff in delivery, payments and software stocks.

Similar thoughts were echoed by IMF chief Kristalina Georgieva. Georgieva told Business Today that AI is “like a tsunami hitting the labor market,” with “40% of jobs globally, 60% in advanced economies” set to be impacted. She urged policymakers to “manage the risks, especially the risks of displacement of workers” and strengthen safety nets for those affected.

Why an AI tax?

Shah argued that policymakers should consider taxing incremental or windfall gains generated by AI adoption, particularly as productivity gains increasingly replace human labour. Governments “should consider policies such as taxing incremental or windfall gains from AI,” Shah said, adding that a related hit to consumer spending would imperil the broader economy.

His core concern is macroeconomic: rising unemployment weakens household consumption, which in turn drags on growth in advanced economies where demand drives GDP.

The proposal does not advocate taxing AI as a technology. Instead, it frames taxation as a stabilisation tool — recycling extraordinary automation-driven corporate gains back into the economy to offset displaced incomes.

Job displacement scenario

The Citrini report sketches a forward-looking scenario in which rapid advances in machine intelligence dramatically boost productivity while simultaneously displacing large swathes of white-collar labour. Shah outlined a near-term risk case where as much as 5% of white-collar workers could be cut within 18 months. The concern is not just job losses, but a reinforcing negative loop: firms trim headcount to protect margins, redeploy savings into AI systems, enable further automation, and in the process weaken aggregate consumer demand. That erosion in spending power could feed back into corporate revenues, particularly in sectors built on intermediation such as finance, insurance and software.

Market impact and sectoral divide

The so-called “AI scare trade” followed Citrini’s warning of structural disruption, with delivery platforms, payments companies and select software names singled out as vulnerable — triggering a broad selloff. Technology stocks have already been volatile amid growing concerns that AI could rewire business models across industries.

Shah said a pronounced sectoral split. Likely beneficiaries include chipmakers, data centers and foundation model labs — the infrastructure backbone of the AI buildout. In contrast, insurers, banks, consumer discretionary platforms and other intermediation-heavy businesses face elevated risk as automation compresses fee pools and weakens demand.

“We generally have a set of shorts out against businesses that we think are going to be disrupted by AI,” Shah said. “On the other side of that, we own a lot of semiconductors that we think are going to benefit.”

AI is like a tsunami

IMF Managing Director Kristalina Georgieva delivered a stark warning about the scale and speed of AI-led transformation.

Speaking to Business Today in New Delhi, she said: “AI is already here and the speed with which it is affecting the way we work, we live, we interact with each other is so high, highest in the history of technological transformation.”

Her assessment of labour-market impact was blunt: “AI is like a tsunami hitting the labor market.”

The IMF estimates that “40% of jobs globally, 60% in advanced economies, [are] to be impacted by AI in the next years, either enhanced, made more productive, or replaced.”

Georgieva noted that while overall employment effects may be positive in some regions, gains are skewed: “The total impact on employment, surprisingly, in areas we study, is positive. But it is positive because of the increase of low-paying jobs.”

She warned of middle-income job compression: “The jobs in the middle that are neither enhanced nor created as low-service. Jobs they get in relative terms squeezed.”

She also flagged risks for young workers: “We also see automation eliminating entry-level jobs. So recent graduates, they worry, where is the job for me?”

To cushion disruption, she urged stronger education systems and social protection frameworks so displaced workers “have something to lean on for themselves and their families.”

Where does India stand

Vineet Nayar, founder Chairman and CEO of Sampark Foundation and former CEO of HCL Technologies, cautioned against assuming AI will automatically create jobs, particularly in India’s IT sector.

Speaking at AI India Summit, Nayar said: “From an employment point of view I think it is very important for us to understand that Indian companies, including Indian IT companies, are going to be profit-driven and therefore if you believe that they are going to create employment you must be dreaming.”

He argued that job creation will depend on large-scale entrepreneurship: “Therefore, the question is how do we create employment in this environment? That employment comes from mass scale startups… So, how do we create new sets of people who are trying to solve new sets of problems, not new sets of technology and if we do that we will get it right.”

Nayar also raised concerns around AI capability and data ownership: “Unfortunately, in India, we never develop products, so therefore we do not have SLMs and LLMs which are world-class.”

He warned that allowing global models to operate freely on Indian data poses strategic risks: “On one side, we have global LLM products which are coming to India and trading on our Indian data. Should we allow that or should we not allow that?”

Without incentives to build domestic AI capacity, he cautioned, India risks losing a “competitive advantage on something which is very critical for the next decade”.

What governments must decide now

The debate now extends beyond markets to fiscal policy design. If AI accelerates economic output while shrinking payrolls, governments face a structural question: how should tax systems adapt?

Shah’s proposal to tax AI windfalls introduces one possible framework — using fiscal tools to stabilise labour-market disruption before it translates into a consumption shock. As productivity gains intensify and labour-market stress signals mount, AI taxation may move from theoretical debate to active policy consideration.