Since 2000, asset values ​​have increased faster than GDP; That’s a boon for those who have assets to start with but nothing for those who are just starting out and need a broad earned income. Only about a quarter of wealth is generated from investments, the rest is mostly in paper. In addition, debt soared, with every dollar of investment generating $1.90 of debt. Wealth inequality is entrenched, with the top 1% of major economies accounting for at least 20% of the wealth. And, finally, international financial imbalances are growing, contributing to the current volatile trade and political environment.

The size and shape of the imbalance varies from place to place. But there are two commonalities. First, rapid productivity growth is the most effective counterweight to the current tilted profile. And second, artificial intelligence (AI) can help—up to a point. For AI to realize its potential, countries must not only position themselves to benefit from its capabilities in terms of technology and business, but also macro-economically. Otherwise, it’s like eating a heaping bowl of carbohydrates to fuel a workout—and then skipping the gym. The results are not pretty.

Consider the United States. It is at the forefront of AI-related innovation, investment, and adoption. To maintain positive momentum, however, it needs to save more (ie, borrow less). The national debt is, almost 120% of GDPmore than double what it was in 2000. If annual budget deficits continue to grow, potentially higher inflation, interest rates, and long-term uncertainty could devastate the economy and threaten the investment needed for continued AI development. Wealth could fall to nearly $100,000 per capita in real terms by 2033.

While AI-based development could boost fiscal revenues, there are also ways AI could exacerbate US fiscal challenges. If labor market disruptions are significant, related costs, such as unemployment insurance, may increase. Higher productivity, even if concentrated in a few sectors, pushes up wages overall; but that would translate into higher labor costs in the public sector. In addition, many social benefits are tied to income. The reason: more AI without a healthier fiscal picture can only add to the tension.

In China, the challenge is different; the economy should save less and consume more. In the wake of those long-term decline in the property marketChinese households have increased their deposit savings—on the order of nearly seven percentage points of GDP compared to their average levels in the 2010s. Deflation followed. Meanwhile, private corporate investment has slowed significantly, to 1% of GDP in a recent year, compared to 7% from 2017-21. As investment in state-owned enterprises (SOEs) increased, these entities are less productive. Overall, 23% of China’s industrial enterprises lost money, the highest figure in more than two decades. Economic growth is therefore mostly driven by net exports, which is difficult due to increasing international pressure to reduce trade and investment imbalances. The best alternative is for consumers to spend their income.

China is a recognized leader in AI. Translating that into growth requires new business models and reforms to unlock new domestic demand.

In Europe, on the other hand, the threat of a prolonged economic slowdown is real, with an economy characterized by households cutting debt, fiscal constraints, sluggish investment, weak productivity and declining interest rates. Corporate competitiveness needs to be improved. So it needs to invest more, especially in AI-driven innovation and infrastructure. That could mean being home to leading AI companies or nurturing the growth of standout companies that can use it most dynamically. Research shows that the biggest economic impact from AI is likely to come from a few companies that go “all in,” rather than many of them making small bets.

For now, however, Europe is trailing far behind China and the United States. According to a a recent McKinsey-World Economic Forum report, it is globally competitive in only four of the 14 critical technologies, and costs only four of the top 50 tech in the world companies. the McKinsey Global Institute estimates that major European companies face an investment gap of $700 billion a year in R&D and capital spending compared to their US counterparts. Corporate investment in Europe has declined relative to GDP since 2019, and delivered as well 25% lower returns than the US

What does this mean for companies? CEOs must understand the swing factors—less borrowing in the US, more investment in Europe, more consumption in China, each at a scale greater than 3% of GDP—that can drive the long-term trajectory of wealth and economic growth, and plan for each. But they are not spectators to drive fruitful results; they are the engines for the growth and widespread adoption of AI. And the actions of just one CEO can make a big difference: just a few dozen companies have driven most of the productivity growth in economies including the United States, the United Kingdom, and Germany over the past 15 years.

AI will be the disruption of the century, and a positive one, delivering vast improvements through greater productivity. But that is inevitable. If AI is to become a platform for prosperity, countries and companies must ensure that the foundations are solid.

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