A speculative macro research paper published Feb. 22 by Citrini Research and Alap Shah of LOTUS models a scenario in which unchecked AI-driven labor displacement triggers a cascading economic crisis by 2028 — with stablecoins on Solana (SOL) and Ethereum (ETH) L2s replacing card payments as AI agents route around interchange fees, and the S&P 500 crashing 38% from its highs.
What Happened: AI Crisis Scenario
The paper, framed as a fictional "macro memo" written from June 2028, traces how AI-fueled white-collar layoffs could spiral into a full-blown economic meltdown. The scenario begins with agentic coding tools reaching a capability threshold in late 2025, enabling developers to replicate mid-market SaaS products in weeks.
In the authors' model, the S&P 500 reaches 8,000 and the Nasdaq breaks 30,000 by Oct. 2026 before the unraveling begins. Corporate layoffs initially boost margins and earnings, but displaced white-collar workers — who the paper notes drive roughly 75% of discretionary consumer spending — stop spending, setting off what the authors call "the human intelligence displacement spiral."
The scenario describes AI agents taking over consumer transactions by early 2027, dismantling business models built on human friction.
Travel platforms, insurance renewals and real estate commissions all compress as AI agents optimize for price. The paper envisions agents settling transactions via stablecoins on Solana and Ethereum L2s to avoid the 2-3% card interchange fee, hitting Mastercard, Visa and card-focused banks. In the scenario, American Express is hardest hit by a combination of white-collar customer losses and interchange erosion.
Private credit markets crack next. The fictional timeline places Zendesk at the center: its $5 billion direct lending facility, led by Blackstone with Apollo, Blue Owl and HPS, defaults after AI agents replace the customer service category Zendesk had defined. The paper describes losses flowing through to insurance companies that alternative asset managers had acquired as funding vehicles, threatening household savings structured as annuities.
The scenario culminates with the U.S. mortgage market under stress.
The authors model an 11% year-over-year home price decline in San Francisco and rising delinquencies among prime borrowers with 780+ credit scores. If fears materialize, the paper suggests equities could fall to S&P 500 levels of roughly 3,500, comparable to the month before ChatGPT launched in Nov. 2022.
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Why It Matters: Structural Economic Risk
The paper's central argument is that AI disruption differs fundamentally from prior technological transitions. The authors write that every previous technology wave created new jobs requiring human labor, but "AI is now a general intelligence that improves at the very tasks humans would redeploy to."
The scenario projects labor's share of GDP dropping from 56% in 2024 to 46% by 2028, which the authors call "the sharpest decline on record."
Federal tax receipts in the model run 12% below projections as income flowing through households — and therefore the IRS — dries up. The paper frames the core tension: "the government needs to transfer more money to households at precisely the moment it is collecting less money from them in taxes."
The authors stress this is not a prediction.
"This isn't bear porn or AI doomer fan-fiction," they write. "The sole intent of this piece is modeling a scenario that's been relatively underexplored."
They close with a direct appeal to readers in Feb. 2026, noting that "the S&P is near all-time highs" and "the negative feedback loops have not begun," urging investors and policymakers to assess whether their assumptions can survive the decade.
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