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Bridgewater Associates believes the artificial intelligence investment boom has become one of the dominant forces driving the global economy, but warns that capturing its next phase may prove considerably more complicated for investors.
The manager estimates the historic AI capital expenditure cycle is now responsible for roughly a quarter of global economic growth, as companies race to build the computing infrastructure required by increasingly capable AI models.
Demand for inference computing continues to expand rapidly and is outstripping even the substantial increase in supply, according to Bridgewater’s latest quarterly letter to clients.
But financial markets are catching up.
The hedge fund says investors increasingly priced the exponential growth in AI capital expenditure during the second quarter, raising the hurdle for further outperformance from the most obvious beneficiaries of the build-out.
From AI winners to AI losers
That creates a potentially important distinction for portfolios.
Bridgewater argues that investors need sufficient exposure to companies benefiting from AI infrastructure spending because the technology has become such an important engine of economic growth.
But it believes some of that opportunity is now reflected in asset prices.
Potential disruption from AI adoption, by contrast, is much less fully priced, according to the firm.
The distinction shifts the investment question from simply identifying companies benefiting from AI spending towards identifying businesses whose existing economics could be undermined as the technology is adopted.
That argument has implications well beyond technology stocks.
As AFI has reported recently, alternative managers are increasingly confronting both sides of the AI boom. Blackstone, for example, has generated substantial gains from data centres, power infrastructure and other AI-related investments while simultaneously facing investor concerns about the vulnerability of software businesses financed through private credit.
Bridgewater’s analysis suggests that identifying those second-order effects could become increasingly important as the straightforward AI infrastructure trade matures.
AI collides with geopolitics
Bridgewater argues that the AI boom is colliding with another major investment trend: governments spending more to make their economies less dependent on other countries.
Both trends require many of the same scarce resources. AI data centres need huge amounts of power, semiconductors and infrastructure, while governments are simultaneously trying to secure domestic supplies of energy, technology, defence equipment and critical materials.
The result, Bridgewater argues, is unusually strong investment by both companies and governments. That spending can support economic growth, but competition for limited resources could also create shortages and increase inflationary pressure.
This is what Bridgewater calls “modern mercantilism”: countries increasingly prioritising security and self-sufficiency over the cost efficiencies of globalisation.
Real assets return to the portfolio debate
Bridgewater argues that the AI boom could also strengthen the case for real assets.
AI infrastructure and governments’ push for greater economic self-sufficiency are increasing demand for energy, commodities and physical infrastructure. Exposure to these assets could therefore benefit from rising demand while also providing some protection against resulting inflation.
Bridgewater believes investors should consequently pay particular attention to three portfolio exposures: AI, real assets and geography.
Geography presents a dilemma. Governments increasingly want to reduce their dependence on the US, but America remains at the centre of the AI economy and offers the deepest markets for gaining AI exposure.
Bridgewater sees China as a potential source of diversification, given its economic scale and development of its own AI industry.
The next stage of the AI trade
Bridgewater’s thesis does not amount to a bearish call on artificial intelligence.
Instead, it suggests the investment opportunity is becoming more complex.
The first stage rewarded exposure to the companies supplying the computing power and infrastructure behind the AI boom. As markets increasingly recognise the scale of that spending, however, future returns may depend more heavily on understanding who is disrupted, which resources become scarce and how governments respond.
That makes the next phase potentially much more suited to active investors than the first.