A widely shared report from Citrini Research titled The 2028 Global Intelligence Crisis has triggered major discussions about how artificial intelligence could reshape the global economy in the near future.
The report presents a speculative worst-case scenario in which rapid advances in AI automation lead to widespread unemployment and major financial disruption by the year 2028.
Report Warns AI Automation Could Trigger Global Economic Disruption by 2028
One of the sectors highlighted as particularly vulnerable is India’s IT services industry, especially major companies such as Tata Consultancy Services, Infosys, and Wipro.
According to the report, these companies could face serious threats because their traditional outsourcing business models may be undermined by increasingly capable AI tools.
The analysis imagines a situation where, by 2028, India’s IT services sector—which previously generated more than $200 billion in annual exports—comes to a standstill.
This disruption occurs in the scenario because companies around the world begin replacing outsourced development work with AI-powered coding agents that operate at a far lower cost.
The report explains the economic shift with the statement: “The entire model was built on one value proposition: Indian developers cost a fraction of their American counterparts. But the marginal cost of an AI coding agent had collapsed to, essentially, the cost of electricity.”
As demand for outsourced services weakens in this scenario, the report predicts a rapid decline in India’s currency value against the U.S. dollar.
It suggests that the weakening of service exports removes a key support system for India’s external financial balance.
The document describes the progression of the crisis by stating: “TCS, Infosys and Wipro saw contract cancellations accelerate through 2027.”
Report Claims Rupee Could Drop 18% as AI Disrupts India’s IT Services Exports
The report also states, “The rupee fell 18 per cent against the dollar in four months as the services surplus that had anchored India’s external accounts evaporated.”
It further claims that by the first quarter of 2028, the crisis becomes serious enough that the International Monetary Fund begins “preliminary discussions” with the Indian government.
Another major concern raised in the report is the absence of what it calls a “natural brake” that might slow the spread of AI automation.
According to the analysis, AI adoption creates a self-reinforcing economic cycle that keeps accelerating even when it harms employment and consumer spending.
The report describes this cycle with the explanation: “AI got better and cheaper. Companies laid off workers, then used the savings to buy more AI capability, which let them lay off more workers.”
It adds that displaced workers reduce their spending power, which further weakens the broader economy.
The report summarizes this dynamic by stating: “Displaced workers spent less.”
It also explains that businesses selling goods and services begin experiencing declining sales as consumers reduce their purchases.
As revenues shrink, companies respond by investing even more heavily in AI technology in order to maintain profitability.
The paper describes this reinforcing cycle with the statement: “Companies that sell things to consumers sold fewer of them, weakened, and invested more in AI to protect margins.”
It continues the explanation by noting: “AI got better and cheaper. A feedback loop with no natural brake.”
Despite the broader economic slowdown described in the scenario, the report highlights a paradox in which the companies producing AI hardware continue to thrive.
It identifies major semiconductor players such as NVIDIA and Taiwan Semiconductor Manufacturing Company as examples of firms benefiting from the AI boom.
Even while other industries struggle, these companies continue reporting strong financial performance because demand for AI infrastructure remains extremely high.
The report illustrates this contrast by stating: “NVDA was still posting record revenues.”
It also notes: “TSM was still running at 95 per cent plus utilisation.”
The document further explains that large cloud computing providers, often referred to as hyperscalers, continue investing enormous amounts of money in data center infrastructure.
Their spending is described as reaching between $150 billion and $200 billion per quarter on data center capital expenditures.
According to the report, economies that are closely tied to semiconductor manufacturing benefit greatly from this trend.
Countries such as Taiwan and South Korea are cited as examples of economies that outperform others because of their strong positions in the semiconductor industry.
The report concludes that regions heavily connected to the AI hardware supply chain could prosper even while other parts of the global economy struggle with the consequences of rapid automation.
