Epic signal! Wall Street top investment banks analyze the AI endgame: a crossroads to heaven or hell. Is your $BTC a fortress of wealth or worthless paper?

When artificial general intelligence achieves full automation, economics textbooks may need to be rewritten. The boundaries between capital and labor will become completely blurred, and the value of labor may approach zero. Market analysis indicates that this is not science fiction but a serious deduction based on the classical economic framework.

The deduction depicts two extreme outcomes. The first is complete substitution. In this world, AI fully automated machines are both capital and labor. Wealth and income will be highly concentrated among a few capital owners. Ordinary people’s incomes will sharply decline, demand will shrink, and the economy will fall into a deflationary trap of “overproduction but insufficient purchasing power.” This echoes Karl Marx’s ancient concept of machines and automation and bears similarities to Elon Musk’s ultimate vision of AI.

The second outcome is a replay of history. AI serves only as an enhancement tool, and human labor is not fully replaced; new jobs will continue to emerge. Policy systems can mitigate shocks, and the economic logic will resemble that of the past few decades. Inflation, interest rates, and the stock market are more likely to rise gradually.

To understand the destructive power of the first outcome, we must trace back to the foundations of modern economics. Since Adam Smith, capital and labor have been regarded as independent factors of production, with prices determined by their relative scarcity. Past technological revolutions have conformed to this model: machines are capital, and labor operates the machines.

But fully automated AI robots break this classification. When machines can think, produce, and iterate autonomously, capital becomes equivalent to labor. The value of work may drop to zero, as may wages. Classical economic theory breaks down here, and the capitalist system itself may become outdated.

Deeper macroeconomic upheavals follow. In a world where AI fully replaces human labor, Say’s Law—supply creates demand—may fail. Automation will concentrate wealth among capital owners, whose marginal propensity to consume is far lower than that of ordinary workers.

The logic is straightforward: AI factories can produce vast quantities of goods at low cost, but all profits go to owners. Owners’ personal consumption is limited, while large numbers of unemployed people lack purchasing power. The transmission chain from supply to demand breaks down, potentially resulting in structural low labor income, deflation, and excess savings accumulation—what economists call “long-term stagnation.”

In the face of market failure, Keynesian government intervention may become an option, such as taxing AI and distributing universal basic income. However, historical research shows that policy and institutional adjustments are often slow. If technological change outpaces institutional adaptation, interventions may fail to take effect in time.

Even with rapid government response, deeper political and economic challenges remain. After full automation resolves scarcity, the meaning of property rights will become a fundamental social issue. As Keynes once asked, when survival labor is no longer necessary, what is the purpose of human existence?

For financial markets, it is essential to consider both the transition path and the outcome itself. In the scenario where AI fully replaces labor, macroeconomics will face intense deflationary pressure, with real interest rates structurally declining. Companies will see profits soar due to increased AI efficiency, but stock markets will fluctuate long-term due to “expropriation risks” (such as extreme taxation) and unresolved profit distribution issues.

In the foreign exchange market, countries that manage the transition most smoothly may benefit the most from their currencies. In the scenario where AI is merely an enabling tool, macro indicators are more likely to point to moderate rises in inflation, interest rates, and stock markets.

The purpose of this deduction is not absolute prediction but to establish an analytical framework. For investors, tracking the progress of AI’s economic impact can focus on several key milestones: whether the labor market shows signs of structural unemployment and a rapid decline in labor share; whether fiscal and antitrust policies shift toward stronger income redistribution and substantial measures against tech giants.

In an era where AI reshapes everything, the value of infrastructure for data storage and access will become increasingly prominent. This points to the decentralized physical infrastructure network track. As the native storage layer of the Sui ecosystem, it aims to provide efficient, verifiable data storage services for AI and blockchain applications, capturing underlying value in an era where data is an asset.

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