Recently, there has been enormous turmoil on global stock exchanges. The values of many top companies have plummeted, with technology and finance companies suffering the most. Is this the result of new regulations coming into force? Or perhaps the aftermath of a controversial decision by one of the high-ranking CEOs? It turns out that this is not the case. The reason for such a serious decline is a fictitious report from Citrini Research, which presents a hypothetical scenario of a global economic collapse in 2028 due to the further development of artificial intelligence.
The report, entitled The 2028 Global Intelligence Crisis, reads a bit like a science fiction story and a bit like an actual financial report. The authors (AI businessman Alap Shah and the team at Citrini Research, a brokerage firm focused on researching issues at the intersection of economics and new technologies) take us to the last days of June 2028. In a rather long text, they precisely describe the development of AI in the years 2025-2028 and its impact on the American economy in particular, but also on the global economy.
It starts innocently enough. The further development of artificial intelligence means that more and more companies are integrating these tools into their daily operations. This primarily affects the IT industry. The authors describe a process that we are already seeing to some extent: instead of investing in hiring a subcontractor to create their digital product, companies prefer to use artificial intelligence, whose coding skills are improving all the time.
Of course, this phenomenon is associated with layoffs. The authors of the report claim that the first wave will begin in the early months of 2026. Ultimately, in 2028, unemployment in the United States is expected to affect 10% of citizens, more than double the current rate. What will lead to this situation?
A high-profile report by Citrini Research. Experts predict an economic collapse due to AI
Citrini Research and Shah argue that the further development of AI threatens not only those in the IT industry, but also the majority of office workers (so-called white-collar workers). This is all due to the increasing development of autonomous AI agents that will interact with each other.
An example? Food delivery apps. Instead of choosing between the two or three largest apps, you ask an AI agent to review the offers on all available platforms, then select the most advantageous one and order it. According to the authors, there may be more such apps in the future, as it will be much easier to create a ready-to-launch product of this type using artificial intelligence programming tools.
Food delivery couriers will have access to a single platform that will collect orders from different apps. They can even ask AI agents to select the most advantageous ones for them. Solutions built with the help of artificial intelligence that compete with Uber Eats or Pyszne.pl will not have to invest in marketing and defeating market giants. When AI sees that they offer lower prices and at the same time favourable earnings for couriers, their popularity will skyrocket.
All this is to happen without conscious human decision-making. Digital services will have to be geared more towards efficiency-oriented AI agents than people with different, often irrational preferences. In addition to food delivery, the AI agent revolution is also set to affect other industries, including tourism and… banking.
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Will AI replace traditional payment methods? A disturbing vision for the banking sector
It is the changes in the banking industry that may be the most severe. Currently, companies that handle cards and payment services charge a commission of between 1.7 and 2 per cent. The authors of the report calculated that if a consumer pays £100, after deducting these fees and other network commissions, the seller receives £97.50. However, this does not have to be the case.
Imagine this situation: both the buyer and the seller use AI agents to establish a transaction between themselves. There is no interaction between people, only between two instances of artificial intelligence, each of which is tasked with finding the solution that is most beneficial to the respective party. Ultimately, the two bots talking to each other decide that the best solution will be to pay not with a standard card or bank transfer, but with cryptocurrencies, such as stablecoins (which are linked in value to a traditional currency).
In the vision of Citrini Research and Shah, this situation will mean an absolute crash in the banking sector, but of course, the increasing agency of AI will affect many more industries. Ultimately, mainly manual workers will keep their jobs, but ‘intermediaries’ will suffer, as they will be replaced by interaction between autonomous AI agents. Marketing? Unnecessary. Programmers? Every programme will be written by AI. AI supervision? This is also to be done by artificial intelligence, which, according to the authors of the report, is set to become increasingly better at this.
Mass unemployment and ghost GDP
Many people are expected to lose their jobs over the next two years. Many of them will not return to their previous professions because their positions will be replaced by AI. This is where the term ‘ghost GDP’ (Ghost GPD), which is key to the report, comes in. Using artificial intelligence is obviously more cost-effective than employing people. Therefore, company profits will grow, and with them, gross domestic product. However, the income of the average household will decline.
In every respect, AI exceeded expectations, and the market was AI. But the economy was not. It should have been clear from the outset that a collection of processors somewhere in North Dakota, generating the effect of work previously attributed to 10,000 office workers in downtown Manhattan, is more of an economic pandemic than an economic panacea. The velocity of money flattened. The human-centred consumer economy, which then accounted for 70 per cent of GDP, began to wither. We could probably have understood this earlier if we had simply asked how much money machines spend on discretionary goods (hint: zero), says Alap Shah, Citrini Research.
The mechanism described above with a slight sarcasm is what Citrini and Shah believe will ultimately destroy the economy. The effect will not be immediate. A low-paid construction worker or nurse who loses their job has to start tightening their belt almost overnight. However, programmers and financiers usually have some savings. For such people, financial problems will begin several or even more than a dozen months after losing their jobs. We are talking about the top 10% of the population in terms of earnings. These people most often take out mortgages and spend a lot of money, thereby driving the economy. Suddenly, these funds will be missing from their pockets.
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The ideal borrower will cease to be solvent
A well-paid white-collar worker is theoretically an ideal borrower. A bank granting a mortgage can be sure that such a person will regularly repay subsequent instalments. But what if a large proportion of such people end up on the street, exhaust their savings after a few months and are unable to continue repaying their loan?
Such a scenario will trigger a dangerous spiral. Banks will start to incur losses, the value of collateral and property prices will fall. Everything points to a repeat of the speculative bubble burst in 2008. At that time, however, the crisis was caused by the fact that loans were granted even to those who were more ‘risky’ from the lender’s point of view. This time, the once undeniable reliability of borrowers disappeared within a few months.
Lack of new jobs. Citrini Research report predicts mass unemployment
Citrini and Shah point to the often-raised argument that every technological innovation destroys certain professions in order to create new ones. For the past two centuries, this has indeed been the case. Shoe factories killed the shoemaker’s profession, but someone still has to work in those factories. ATMs made it cheaper to run a bank branch, so more branches were opened, employing more people.
However, the examples mentioned above were characterised by the fact that each job created by innovation could be filled by a human being. In the case of the AI revolution, this was no longer so obvious. Why hire a team of a dozen or so programmers when AI can create a working application much faster and cheaper? For management boards and CEOs who looked primarily at quarterly and annual profit reports, this question is rhetorical.
Global markets react to high-profile report. Echoes can also be seen in Poland
Above, we have listed the most important conclusions of the report and briefly described the vision presented in it. However, it is worth reading the whole report, as the authors go into much more detail about the potential economic consequences of the further development of AI. They cite specific financial mechanisms that are expected to contribute to a global economic crisis within the next two years.
The report was published on Sunday, 22 February, and by Monday morning it had spread so widely across the internet that it caused turmoil on global markets at the start of the new week. IBM shares on Wall Street recorded their biggest drop in 25 years (as much as 13.1%), and the Dow Jones fell by more than 800 points. Microsoft, Oracle and Accenture shares fell by several per cent, as did payment companies such as Visa, Mastercard and American Express. Citrini and Shah explicitly mention the latter in their report as being at risk of financial transactions being taken over by AI agents.
The echoes also spread to the Warsaw Stock Exchange. On Monday, shares fell mainly in technology companies, including Compu (-4.41 per cent), iFirma (-4.09 per cent), cyber_folks (-3.87 per cent), Shopera (-2.45 per cent) Vercom (-2.36 per cent) and Asseco (-2 per cent). Tuesday confirmed the trend: Vercom and Shopera’s final declines amounted to approximately 9 per cent.
Is the stock market ruled by fear of AI?
Will the vision presented in Citrini and Shah’s text actually come true? No one really knows. At the end of their report, the authors postulate that a major AI crash in 2028 could be prevented by introducing an AI tax. Companies would have to give part of the profits generated by the implementation of artificial intelligence to the state.
However, market reactions to the text show that reports of the AI bubble bursting are causing increasing excitement among investors. Such scenarios have been discussed for several months now. Although Citrini and Shah’s analysis goes far beyond a simple collapse of an inflated industry, this does not change the fact that such catastrophic visions related to the development of AI capture the imagination of the people who shape global markets.
One thing is certain: something is in the air. Will the AI bubble actually burst? Or will the further development of artificial intelligence cause mass unemployment among white-collar workers and a collapse of the banking and real estate industries, as the authors of the report predict? Regardless of which vision comes true, those interested in global finance seem to be waiting in suspense for some kind of economic catastrophe. And the fear associated with the apocalypse can sometimes be worse than the actual end of the world.
