How AI is reshaping economies and empires

A future disruption

The global job market is on the verge of a seismic shift, driven by the forces of artificial intelligence (AI), automation and branching. Layoffs in sectors such as technology, finance and manufacturing are already making headlines. Companies like Meta, Amazon and Google have cut tens of thousands of jobs, citing the need to streamline operations and improve productivity. Meanwhile, the telecommuting revolution has enabled outsourcing on an unprecedented scale, allowing businesses to tap into skilled labor markets in places like India, the Philippines and Eastern Europe at a fraction of the cost.

This disruption is exacerbating trends of worker discontent and economic inequality. According to a recent study by the Pew Research Center, the middle class – once the backbone of the US economy – continues to shrink. Many of the displaced are unable to transition into new roles, either because of skills mismatches or the rapid pace of technological change. For example, the rise of generative artificial intelligence has made many content creation and programming jobs redundant, while autonomous systems are replacing roles in logistics, transportation and customer service.

The consequences of these divisions are already appearing politically. Displaced workers and economically insecure populations are gravitating toward populist movements that promise protectionism, anti-globalization policies, and curbs on immigration. In the United States, Europe and beyond, political polarization is deepening, fueled by economic discontent and a perception that governments and corporations prioritize profits over people. If current trends continue, this discontent will only intensify, threatening social cohesion and democratic stability.

But why and how to say this? What is the basis for such a prediction and what exactly are the specific results we can expect?

Theoretical frameworks to predict the future

As research for my upcoming book, Cyber ​​Society, I spent years studying trends and building a predictive model of the future based on what I observed. To do this, I used three main frameworks and fields of study to develop an integrated framework that can process the data and provide possible contours of what we can expect from the future, barring asteroid impacts or sudden changes. fast in trajectory.

What are these frameworks and fields of study? The first consists of Moore’s Law and similar exhibits of exponential technological progress. Moore’s Law applies specifically to semiconductors, but similar laws, such as Metcalfe’s Law regarding the value of networks, are broadly applicable to many other areas of technology. The progress we’re seeing in CPUs, for example, is also being seen in solar power, as efficiency increases and costs drop significantly.

The second predictive framework is provided by Cliodynamics, a theory of social cycles and a study of the key drivers of peaks and troughs.

The third framework is the scaling laws chronicled and studied by Geoffrey West.

Exponential technologies

Laws of exponential growth, such as Moore’s law, have historically guided our understanding of technological progress. Moore’s Law—predicting that the number of transistors on a chip doubles roughly every two years—symbolizes the broader trend of accelerating innovation. Today, AI systems, robotics, and computing power are advancing at rates that outpace traditional economic and educational systems. The exponential growth means that the disruptive potential of these technologies is not linear, but complex, leading to unpredictable consequences in shorter time frames.

Cliodynamics and Historical Dynamics

Peter Turchin’s cliodynamics provides a framework for understanding social cycles through quantitative modeling of historical data. Turchin predicts periodic waves of social unrest, often fueled by economic inequality, elite overproduction, and declining social trust. His models suggest that the United States is entering a “disintegration phase,” characterized by falling living standards and increasing political instability. The rapid erosion of secure employment and wage stagnation due to AI and branching aligns with Turchin’s predictions of systemic upheaval.

Scaling laws and urban stability

Geoffrey West’s research on the laws of scaling in cities provides a lens through which to examine the economic and social stability of urban centers. Cities, according to West, are engines of innovation and productivity, but their sustainability depends on maintaining certain employment and income thresholds. Below these thresholds, cities risk rapid collapse. West’s models imply that mass unemployment driven by AI and automation could damage the fabric of urban economies, leading to major failures in infrastructure, governance and social order.

So when you combine these frameworks and use them to process the data we have now on social trust, employment, technological advancement and other related areas, what can we say about the future? Quite a lot, actually.

Some chilling predictions

Short term (0–5 years): An era of adaptation

In the near future, layoffs and job displacement will accelerate. The integration of AI into white-collar professions will render many mid-level roles, from legal assistants to financial analysts, obsolete. Companies will prioritize cost reduction, leveraging remote and offshore work to access cheaper workforces. Political strife will deepen as displaced workers demand government intervention, while populist leaders capitalize on growing discontent.

Social safety nets will be stretched thin. Existing retraining programs will prove inadequate and structural unemployment will increase. Wealth inequality will increase as the owners of capital – those who control AI – reap disproportionate profits. At the same time, consumer demand may weaken, creating deflationary pressures and stagnating economic growth.

Medium term (5–15 years): A major shift

Over the next decade, structural unemployment will become entrenched. Entire sectors, such as logistics, retail and basic programming, will be dominated by autonomous systems. Even creative fields, once thought to be immune to automation, will face disruption as AI generating tools become more sophisticated. The middle class will shrink further, leading to a dual society of high-skilled, high-income workers and low-skilled, low-income workers.

Urban centers in high-income countries may experience rapid decay, especially those dependent on automation-sensitive industries. Cities that fail to attract high-tech industries or adapt to new economic realities will face population decline and infrastructure degradation. Social unrest will become more frequent, with mass protests and political instability becoming the norm in affected regions.

Long Term (15+ Years): A New Socio-Economic Paradigm

Well before the middle of the 21st century, technological unemployment could reach unprecedented levels. Governments will face pressure to implement radical policy interventions, such as universal basic income (UBI) or wealth redistribution measures. However, these policies will face resistance from entrenched elites and politically divided societies.

Global power dynamics will shift as emerging economies use artificial intelligence and offshoring to ascend economically. High-income countries that fail to adapt to these changes may experience relative decline. Meanwhile, the ethical dilemmas surrounding the governance of AI and the immense power wielded by Big Tech and a few tech billionaires will come to the fore. All these elements risk worsening inequality and fragmentation of society.

In this period, the West in particular, may shift to a “post-work” economy, where AI and automation handle the most productive activities. In theory, this could lead to unprecedented prosperity, its achievement will require significant cultural, political and economic adaptation. Without effective governance, the future may resemble a dystopia of extreme inequality and widespread disenfranchisement rather than a utopia of shared abundance. There is also the question of human purpose; as they say, “an empty mind is the devil’s playground”.

The coming decades will test our ability to adapt to profound technological and social change. While the challenges are great, so are the opportunities to reimagine our economic and social systems. Whether we emerge stronger or broken will depend on how we react; do we cooperate internationally or vent our anger in the form of wars? Do we start living within our means or do we not regret any adjustment that will restore the budget space for development activities? Do we continue to view our global future only through the lens of security interests and military interventions or do we redirect those trillions to education, health and social progress? Our collective choices in the face of these divisions will give us the future we deserve.