A new thought experiment imagines a near future where artificial intelligence reshapes the global economy faster than institutions, businesses, and governments can adapt. Framed as a fictional memo written in June 2028, the scenario outlines what its authors call a potential “global intelligence crisis” triggered by large-scale replacement of human labor with AI systems.

The paper is authored by James Van Geelen, CEO of Citrini, and AI entrepreneur Alap Shah. Rather than presenting a formal forecast, they construct a narrative looking back at how the crisis unfolded, beginning in 2026 when companies accelerated the adoption of autonomous AI agents capable of executing tasks without human supervision.

While the scenario references real-world tech layoffs announced by companies such as Amazon, Expedia, and Pinterest, the authors acknowledge that attributing workforce reductions solely to AI efficiency gains is complex. Still, they argue that once AI systems reach a certain capability threshold, companies face strong economic incentives to automate aggressively.

The Vicious Cycle of AI Adoption

At the heart of the thought experiment is a feedback loop:

Companies invest in AI to cut costs and stay competitive
AI systems improve through scale and reinvestment
More roles become automatable
Additional layoffs follow

Individually, each corporate decision appears rational. Collectively, the authors argue, the result could be destabilizing.

In their scenario, firms most threatened by automation become its fastest adopters, accelerating workforce displacement across high-skill, white-collar sectors. By mid-2027, the US economy enters recession. By 2028, unemployment surpasses 10 percent.

The Rise of AI Agents

The 2028 memo envisions a world where AI agents operate continuously in the background of personal and enterprise devices. These systems:

Write production-level software code
Conduct multi-week research projects
Optimize personal and corporate financial decisions
Replace large portions of administrative, analytical, and technical roles

While new jobs emerge in AI safety, infrastructure, and prompt engineering, the scenario suggests they are fewer in number and lower in compensation compared to the roles they replace.

As displaced white-collar workers move into lower-paying service and trade jobs, wage pressure increases across the labor market. Household financial stress intensifies. By 2028, the authors imagine a renewed mortgage crisis fueled by reduced income, rising debt, and weakened consumer demand.

Fiscal Pressure and Social Unrest

The thought experiment also highlights a macroeconomic dilemma: governments would need to increase direct financial support to households at the same time tax revenues decline due to wage contraction.

In its most dramatic projection, the scenario foresees social movements similar to the Occupy Wall Street protests of the 2010s, including an “Occupy Silicon Valley” wave targeting major AI firms such as Anthropic and OpenAI.

The authors stress that this is not a deterministic forecast. Rather, it is a warning: AI capabilities may be scaling faster than regulatory, educational, and economic institutions can respond.

What This Means for Businesses Today

Regardless of whether such an extreme scenario unfolds, one point is clear: AI adoption is accelerating, and the strategic decisions companies make now will shape long-term economic outcomes.

For business leaders, the question is not whether AI will impact their workforce, but how:

Will AI augment human productivity or replace it?
Are organizations reskilling employees fast enough?
Is automation being implemented strategically, or reactively?
What safeguards are in place for operational and social resilience?

At Control F5 Software, we see AI not as a binary replacement for human labor, but as a productivity amplifier when implemented responsibly. The companies that will thrive are those that redesign processes, invest in workforce upskilling, and integrate AI within sustainable business models rather than chasing short-term efficiency gains.

The next few years will likely define whether AI becomes a stabilizing force for growth or a catalyst for disruption. The outcome will depend less on the technology itself and more on how organizations choose to deploy it.

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