Societe Generale “Super Bear” Questions the AI Bull Market: Frenzy Reminiscent of the Eve of the 1997 Asian Financial Crisis, Productivity Slowdown Masked by Capital Expenditure

According to Zhitong Finance APP, Albert Edwards, the Société Générale strategist known for his extremely pessimistic market views and even self-proclaimed “super bear,” has compared the current artificial intelligence (AI) investment boom to the economic bubble before the 1997 Asian financial crisis. He warns that massive capital expenditures may be masking weak productivity growth, casting doubt on whether the AI frenzy can deliver on investors' high expectations.

In a research report released on October 8, Edwards pointed out that US Total Factor Productivity (TFP) is slowing down. TFP measures an economy’s efficiency in utilizing labor and capital. The weakening of this indicator contrasts sharply with the surge in AI infrastructure spending and the market optimism that has driven the S&P 500 Index to record highs.

Edwards said this divergence reminds him of the boom period in East Asia during the 1990s—at that time, rapid investment and robust growth fostered widespread optimism, which was followed by a financial meltdown in the region.

The strategist cited research from Torsten Slok, Chief Economist at Apollo Global Management, noting that despite the heated AI investment craze, US TFP growth is actually declining. This indicator aims to strip out growth derived solely from more labor or equipment and instead measures pure gains in economic efficiency.

Lessons from the Asian Financial Crisis

Edwards recalled how, before the 1997 crisis erupted, economists and policymakers were full of praise for Asia’s rapid economic development. The World Bank released a report titled “The East Asian Miracle” in 1993, followed by a study on Thailand’s economic success in August 1996—yet less than a year later, Thailand fell into financial collapse.

Economist Paul Krugman challenged the prevailing optimism in his 1994 article “The Myth of Asia’s Miracle.” He argued that most of the region’s economic growth reflected increased investment and labor inputs, not genuine improvements in productivity.

Edwards said he reached a similar conclusion at the time, warning that cheap and abundant capital was being inefficiently allocated. The subsequent financial crisis exposed vulnerabilities that had been masked by rapid economic expansion.

The strategist also recalled how he once compared the late 1990s US tech bubble to the earlier investment boom in Thailand. He believes today’s confidence in AI may be ignoring similar warning signs.

AI Spending Fails to Boost Net Investment

Edwards highlighted the divergence between total corporate investment and net investment in the US.

As companies ramp up spending on AI-related equipment and infrastructure, total investment has increased. However, after deducting depreciation, the share of net corporate investment relative to GDP has remained essentially flat.

This distinction is critical, because increased spending does not necessarily translate into an equivalent rise in productive capital. Companies must continually replace aging equipment—especially in the technology sector, where assets can quickly become obsolete.

Edwards cited economist Rob Parenteau’s observation that the growth in total investment hasn’t resulted in a corresponding improvement in net investment. The report notes that in recent years, the actual ratio of total corporate investment to GDP has risen, while net investment has largely stagnated.

The strategist also questioned the composition of corporate spending. Equipment investment has accelerated in nominal terms, but the increase is not significant when adjusted for inflation.

Meanwhile, despite the ongoing expansion of data centers, nonresidential construction investment has contracted. Edwards pointed out that the contribution of corporate fixed investment to annual GDP growth remains within a historically typical range, leaving potential productivity dividends uncertain.

Edwards acknowledged that AI may ultimately deliver the productivity gains investors anticipate. The technology is still being deployed across industries, and its economic benefits may take time to appear in official statistics.

Slok also stated that it may be premature to expect AI investment to yield measurable improvements in total factor productivity.

Nonetheless, Edwards believes the reality of weak productivity growth is enough to cast doubt on the scale of the investment boom.

The analogy with the Asian financial crisis does not mean that AI investment will inevitably end in a similar crash. However, Edwards’ analysis raises the possibility that spending driven by expectations of future technological breakthroughs could exceed the eventual economic benefits realized.

The Bond Market Poses Another Risk

Edwards also warned that the ongoing global bear market for bonds remains a major concern for investors, with government borrowing costs potentially facing new upward pressures. He noted that bond investors have recently focused on France, but as they assess fiscal weaknesses in major economies, attention could shift to Japan, the UK, or the United States.

The strategist believes that as investors test governments’ ability to sustain borrowing, bond market pressures could quickly shift from one country to another.

For equity investors, the broader concern is this: record stock prices are being supported by enthusiasm for AI, even though evidence for sustained productivity booms remains limited.

Edwards’ analysis suggests that whether the AI-driven market rally can be sustained ultimately depends on whether the technology delivers measurable improvements in economic efficiency, rather than merely fueling another wave of capital expenditure.