AI Job Loss: 2028 Crisis Scenario

KOMPAS.com – Let’s imagine we are in the not too distant future, let’s say June 2028.

On television screens and monitors of world stock exchanges, a gloomy figure is clearly visible. This figure is none other than the unemployment rate which has skyrocketed sharply, reaching 10.2 percent. A higher number indicates that economic conditions are sluggish or employment opportunities are difficult.

The stock market responded with extraordinary panic. The S&P 500 index plunged 38 percent from its peak, trillions of dollars evaporated, and stockbrokers could only stand in silence looking at the red screen that continued to flash.

This is not a snippet from the script of the latest Hollywood dystopian film. This is a highly rational and detailed “thought experiment”, put together by investment research firm Citrini Research with analyst Alap Shah.

In their report entitled “The 2028 Global Intelligence Crisis“, Citrini Research presents a fictitious macroeconomic memo that appears to have been written on June 30, 2028.

The content describes a situation where AI really becomes very smart, makes productivity soar, companies become more efficient, but instead the human economy collapses in 2028.

From the start, Citrini Research emphasized that its report was not a definite prediction, let alone an AI-doomer-style doomsday narrative.

This is a thought experiment, a simulation of the extreme risks if AI actually exceeds expectations and replaces humans too quickly before the economic system has time to adapt.

Then, how could the success of AI actually backfire and destroy the world economy? The following is the anatomy of the crisis, as summarized KompasTekno from the Citrini Research page.

Wall Street debauchery and the emergence of “Ghost GDP”

It all started from a golden age full of blind euphoria. In 2026, the world economy appears to be at the peak of its success thanks to increasingly sophisticated and efficient AI.

Positive sentiment towards AI keeps stocks rising over the long term, and the technology sector is the main driver. The optimistic atmosphere is very palpable. Investors are enthusiastic, the market is full of confidence.

As of October 2026, the United States stock market is celebrating. The United States stock index shot to levels that were previously difficult to imagine.

The index of the 500 largest companies in the US, the S&P 500 is approaching 8,000. Meanwhile the Nasdaq index strolled casually through the psychological mark of 30,000.

At the same time, the first wave of layoffs (PHK) will begin to occur in early 2026.

Many companies are reducing their workforce because some functions are considered to be able to be replaced by AI systems and automation. The term circulating at that time sounded cold, namely human obsolescence where humans are considered increasingly obsolete in several lines of work.

The role of office workers is starting to be massively replaced by AI agents who are too efficient.

For shareholders, this phenomenon is an invaluable gift. Business logic works perfectly on paper. Mass layoffs mean radical cuts in operational costs.

The result? The company’s profit margins are expanding rapidly, earnings reports continue to beat expectations, and stock prices are flying into the sky.

However, these trillions of dollars in record-setting profits were not used to open new jobs for people.

These giant funds are actually turned back and injected heavily to buy more AI computing, more GPUs, more data center infrastructure.

This cycle creates the illusion that the economy is running faster, even though its basic foundation (real human consumption) is starting to erode.

On paper, nominal Gross Domestic Product (GDP) figures are indeed growing rapidly.

AI-based companies are seeing their fortunes explode as labor costs disappear. On the other hand, productivity soared. Real hourly output rose at a rate not seen since the 1950s.

This is all underpinned by AI agents never sleeping, not needing time off, not getting sick, and not demanding health insurance.

However, behind this “too good to be true” situation, there is one fundamental gap that has been overlooked. The machine doesn’t shop. AI will not spend on essential needs, let alone discretionary consumption.

Essential or basic needs include rice, electricity, water, school fees.