AI Tax Debate Grows After Scare-Trade Triggers Market Selloff

A weekend research note on artificial intelligence (AI) by a little-known thematic firm sparked fresh volatility in financial markets this week, and its co-author is now urging governments to consider taxing AI-generated gains to soften the economic blow from job displacement that could accompany rapid automation.

Alap Shah, co-author of the report published by Citrini Research and chief investment officer at Lotus Technology Management, told Bloomberg TV that the disruptive effects of advanced AI warrant policy responses — including the possibility of an AI tax on incremental or windfall gains — to help cushion workers and economies from technology-driven job losses.

The warning comes amid what has been dubbed an “AI scare trade” on Wall Street, where fears about AI’s potential to replace large swaths of labour have prompted sell-offs in stocks widely perceived as vulnerable to automation. Delivery, payments and enterprise software companies bore the brunt of Monday’s declines, including names such as DoorDash, American Express and others whose businesses rely on human-based services that might be disrupted by AI systems.

From Research Scenario to Market Reaction

The report by Citrini laid out a speculative but stark scenario in which rapidly advancing AI tools sharply reduce demand for white-collar labour, with knock-on effects on consumer spending and economic stability. The note envisioned that AI — particularly so-called “agentic” systems capable of autonomously executing complex tasks — could erode employment across sectors like legal services, coding, customer service and financial analysis much faster than markets currently anticipate.

Shah highlighted that AI’s ability to absorb routine cognitive labour could lead to declines in consumer demand, since displaced workers would have less income to spend. In the United States, he suggested this could result in a reduction of white-collar employment by about 5% over the next 18 months, with broader implications for economic activity if not addressed through policy intervention.

In Shah’s view, taxing the “incremental or windfall gains” from AI — similar in spirit to windfall taxes applied in other sectors when extraordinary profits are realised — could help fund job transition programs, retraining initiatives and social safety nets to support those whose livelihoods are most affected.

Market Sell-Off and Investor Sensitivity

The report’s release and ensuing commentary led to immediate market reactions. On Monday, the broader U.S. stock market, as measured by the S&P 500, declined roughly 1%, with a software-focused ETF tumbling by nearly 5% as investors reassessed positions in sectors thought vulnerable to AI disruption. International Business Machines Corp. experienced one of its steepest daily drops in decades.

Investors are particularly sensitive to narratives that tie AI technology to fundamental economic changes because many equities — especially in technology, payments and services — are priced for growth predicated on steady consumer spending and enterprise demand. A reversal of those assumptions has heightened risk aversion and strategy shifts among traders.

Shah told Bloomberg he was “surprised” by the extent of the market reaction, noting that he expected a more modest response to the report’s scenario framing. “It was definitely larger than we expected,” he said, underlining the degree to which AI-related narratives now shape investor psychology.

AI Tax Proposal and Policy Debate

Shah argues that without government intervention, the benefits of AI may accrue disproportionately to capital owners — such as tech firms, data centres and semiconductor manufacturers — while workers face displacement and wage pressures. A policy such as an AI tax could help redistribute some of that economic value to fund public support programs and ease social adjustment.

This sort of idea has parallels to existing discussions in policy circles about how to manage technological disruption. For example, proposals in recent years have explored taxes on automation, robot usage or digital platforms as a way of financing universal basic income or expanded retraining programs. The rationale is that when technological gains concentrate wealth without corresponding employment opportunities, fiscal policy should step in to rebalance outcomes.

Critics of such measures, however, often warn that punitive taxes could dampen innovation and reduce countries’ competitiveness. Proponents counter that measured taxation on extraordinary profits — especially in a field like AI where gains may be rapid and disruptive — could provide necessary resources for societal adaptation without stifling technological progress.

Wider Economic Implications

Beyond the immediate selloff and policy suggestions, the broader economic debate focuses on whether AI will be a net creator or destroyer of jobs over time. While past technological revolutions, such as those involving computers and the internet, have ultimately created new industries and employment, the Citrini report emphasises a risk where AI’s efficiency gains could outpace new job creation, at least in the near term.

This tension between technological optimism and economic disruption forms the backdrop of today’s policy discussions. As AI continues to evolve and its adoption expands, governments, businesses and investors are grappling with how to harness its productivity benefits while mitigating short- and medium-term socioeconomic costs.

Shah’s call for an AI tax adds a new dimension to that conversation, putting forward a concrete policy idea rooted in current market anxiety and structural concerns about labour displacement — even as economists and regulators continue to debate the pace and magnitude of AI-related change.