Collision and Clarity: Understanding the Supercycle We’re Living Through

Kathryn Hamilton, CAE for Market Share Blog | March 4, 2026

The next 730 days will likely feel volatile, said Leonard Brody, an award-winning techno-economist, entrepreneur and venture capitalist, to open his I.CON West keynote address this week in Los Angeles.

He explained that financial systems are under pressure, geopolitical alliances are being tested, and artificial intelligence (AI) has moved from novelty to near-human capability. It is tempting to interpret this moment as uniquely unstable, he said, but in reality, it fits squarely within a 300-year historical pattern of supercycles – long arcs of disruption, typically lasting five years, that reset how economies operate, how technology integrates with humanity, and how prosperity is ultimately generated.

Human life changed very little in the early centuries. A person born in the year 1112 and another born in the year 1516 would have had very similar lives in terms of the structure of society, the pace of communication, and the limits of opportunity. That continuity broke during the British Industrial Revolution, which marked the beginning of a modern era defined by exponential change.

From that point forward, Brody said, technology and human systems became deeply intertwined, driving dramatic gains in life expectancy, poverty reduction, infant survival and access to democratic institutions. These improvements did not emerge gradually; they followed disruption and structural resets.

Today’s turbulence – from the COVID-19 pandemic to Russia’s war with Ukraine, banking instability and the sudden acceleration of AI – may appear disconnected; however, such events have historically clustered during periods of systemic transition.

In short: Supercycles are not random episodes of chaos. They are periods in which multiple forces converge and compel societies to rewrite their operating systems.

AI as the Current Inflection Point

Brody said that AI feels different because it does not simply enhance productivity; it mimics elements of reasoning and creativity. Yet its origins stretch back decades and for much of its history it was limited by two constraints: insufficient computing power and inadequate data. Today, both barriers have fallen.

AI’s evolution has unfolded in stages. Early systems classified and sorted information, then generative systems emerged that could create text, images and code. Today’s model involves agentic AI – systems capable of performing tasks independently.