Pimco’s flagship balanced fund is making a clear call on the next phase of the artificial-intelligence trade: look beyond the most crowded U.S. megacaps and deeper into Asia’s supply chain. The $19 billion Balanced Income and Growth Fund has shifted toward companies tied to chips, data-center infrastructure and critical materials.
The move matters because the fund has outperformed 97% of its peers over the past three years, giving its positioning unusual weight with allocators watching where institutional capital may go next. Its managers argue that rising AI capital spending is making some of the best-known technology names harder to own at current valuations.
Within the first leg of the AI boom, investors were rewarded for owning platform companies and hyperscalers. The next leg, in this view, may be driven by the manufacturers, component suppliers and materials groups that provide the physical backbone of AI expansion.
Key Facts
- Pimco’s Balanced Income and Growth Fund manages about $19 billion and has outperformed 97% of peer funds over the past three years.
- The portfolio follows a 60/40 structure, with roughly 60% allocated to equities and the balance in fixed income and other holdings.
- The fund has become underweight most hyperscalers and much of the Magnificent Seven because of elevated valuations and pressure on free cash flow from AI spending.
- Its equity book added AI exposure through positions in Samsung Electronics, SK Hynix and Taiwan Semiconductor Manufacturing.
- Managers see demand spreading across semiconductor components, cooling systems, cable interconnects, optical equipment, power supplies, construction machinery and industrial metals.
Asia AI Supply Chain
The central thesis is that AI is no longer only a software or cloud story. Building the infrastructure required for training and deploying advanced models demands a huge wave of capital spending on servers, semiconductors, networking, power equipment and physical data-center capacity. That changes the opportunity set for investors.
Rather than concentrating exposure in U.S. internet and cloud giants, the fund has moved further down the supply chain. It is overweight Asia, where management sees a mix of lower valuations, stronger earnings growth and more direct exposure to the hardware and industrial inputs required for AI build-outs. Companies in Taiwan, South Korea and other Asian markets occupy critical positions in memory, foundry services, components and electronics manufacturing that remain difficult to replicate elsewhere.
This approach also reflects a valuation argument. The largest U.S. AI beneficiaries have enjoyed substantial multiple expansion as investors priced in years of growth. But AI investment cycles are expensive. If capital expenditures keep rising, balance sheets, debt issuance and free cash flow become more important to equity and credit investors. For a balanced fund with both stock and bond exposure, that combination can justify caution toward the most expensive names even when the long-term AI theme remains intact.
“You do not need to own the most expensive stocks to capture the AI theme when the physical build-out stretches across semiconductors, networking, power and materials.”
Why materials and rare earths are entering the AI trade
One of the more notable elements of the strategy is the focus on mining, materials and rare earths. AI data centers require far more than advanced chips. They need copper-intensive electrical systems, cooling equipment, specialized magnets, heavy construction inputs and resilient power infrastructure. As a result, the beneficiaries of AI spending may broaden from pure technology companies to industrial and resource producers.
That makes supply-chain security a growing market issue. Chinese companies remain highly significant in resource extraction and materials processing, including areas linked to rare earth supply. Any tightening in export controls, shipping restrictions or strategic stockpiling could affect input costs and project timelines for data-center expansion, especially in the U.S. and Europe. Investors are increasingly treating critical minerals as an AI bottleneck, not just a geopolitical side story.
Implications for Investors
For portfolio construction, the message is not that the AI boom is fading. It is that leadership may be broadening. Investors who already have heavy exposure to the Magnificent Seven may want to examine whether they are underexposed to the companies enabling AI at the hardware and infrastructure level. Semiconductor memory, foundry capacity, optical components, power systems and industrial metals now sit closer to the center of the trade.
The strategy also underscores a shift from momentum to selectivity. If AI capital spending remains enormous, revenue opportunities for suppliers could expand even as returns for some hyperscalers become more sensitive to financing costs, debt loads and the timing of monetization. That does not eliminate the case for major U.S. technology companies, but it raises the bar for valuation discipline and earnings delivery.
Risk remains substantial. Asian supply-chain plays are exposed to geopolitics, export controls, currency swings and cyclical demand shifts in semiconductors. Resource and rare-earth investments can also be volatile, especially when government policy influences pricing and trade flows. Investors considering this theme should watch capital-expenditure guidance from cloud companies, memory pricing trends, foundry utilization rates, and policy developments affecting critical minerals.
The broader takeaway is that AI investing is evolving from a narrow bet on a handful of U.S. names into a more complex global industrial story. If the next phase is defined by who supplies the chips, power, cooling and materials, Asia’s role in the AI supply chain could become increasingly hard for global investors to ignore.