Economy 5 min read By Arthur Ellington
AI investment boom rivals China's post-WTO surge, economist warns
US hyperscalers are projected to spend roughly $800bn on capital expenditure in 2026 as global AI investment approaches the scale of China's post-WTO boom, with economists warning of far-reaching consequences for labour markets, energy demand and inequality.
The artificial intelligence buildout is now comparable in scale to China's investment boom after it joined the World Trade Organization in 2001, according to analysis from Capital Group economist Jared Franz, and its consequences will extend well beyond the technology sector.
US hyperscalers — Microsoft, Amazon, Alphabet, Meta and Oracle — are projected to spend roughly $800bn on capital expenditure in 2026, an 83% increase year on year. Research firm Gartner estimates global AI spending will surpass $2 trillion this year. For hard AI capital investment — chips, data centres, power, cooling and networking — estimates cluster around $10 trillion to $15 trillion globally over the next decade. Broader AI spending, including software, services and AI-enabled products, could approach $30 trillion over the same period.
Those figures invite comparison with China's post-WTO expansion, when fixed investment rose from roughly $360bn in 2000 to $3.2 trillion by 2010. Adjusted for inflation, cumulative Chinese fixed investment over that decade totalled about $20 trillion, reshaping global trade, commodities, inflation, labour markets and politics for a generation.
On a hard-capex basis, AI is already China-scale. Under the broader definition, it could be significantly larger than China's entire 2000–2010 investment surge. The key difference is the nature of the shock: China produced a physical investment, manufacturing, trade and labour-supply shock, while AI represents a compute, power, software and cognitive labour shock.
The disinflationary channel may prove the most significant parallel. China's manufacturing buildout lowered the cost of physical goods worldwide, suppressing interest rates and compressing manufacturing margins in developed economies. AI is doing something similar by lowering the cost of cognitive work. Every task involving pattern recognition, language processing or data synthesis is now subject to the same deflationary pressure that Chinese manufacturing brought to physical goods two decades ago.
AI's physical footprint is also substantial. The International Energy Agency projects global data centre electricity use will more than double by 2030, reaching 945 terawatt hours — roughly equivalent to Japan's entire current power consumption.
There are critical differences that cut both ways. China's fixed asset investment reached roughly 50% of GDP at its peak, fuelled by state-subsidised capital. AI investment, while enormous in absolute terms, is still perhaps 2% of global GDP and driven overwhelmingly by market forces. That may mean AI diffuses faster, since it does not depend on the physical relocation of hundreds of millions of people. China's shock involved the urbanisation of roughly 15% of the world's population; AI's shock is global from day one.
The political economy risks may be more acute. The China shock accelerated inequality and contributed to the political polarisation that many democracies are still living with. AI could turbocharge that dynamic. If it functions primarily as a substitute for cognitive labour rather than a complement, the distributional consequences could be severe.
Early labour market data already hints at differentiation. In the US, job categories with high exposure to AI are deteriorating faster than low-exposure categories by roughly a quarter of a percentage point per month, and the trend appears to be accelerating.
Franz argues the AI debate should not be framed as a tech-sector cycle or a question about whether Nvidia's valuation is justified. The numbers suggest AI may constitute a macro investment regime, large enough to matter for GDP growth, power demand, capital allocation, labour markets and asset prices across every sector.
The China shock gave way to new industries and enormous wealth creation, but it also left behind displaced workers, hollowed-out communities and a populist backlash that took two decades to materialise. Whether the AI transition is managed better is, in Franz's view, the defining economic question of the next decade.
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