[Edaily Marketin KIM SUNG-SOO Reporter] “I entered the alternative investment market to diversify, but all I’m doing is investing in artificial intelligence (AI).” This is the paradox the alternative investment market has recently faced.

This is because funds are flooding into AI-related investments—ranging from private equity (PE) to private credit, real estate, and infrastructure. The alternative investment market, which was once expected to provide diversification benefits due to its low correlation with stocks and bonds, is instead becoming tied to a single theme.

Some observers point out that even though the asset classes differ, the overlap in investment targets—all centered on AI—could weaken the “diversification effect,” which was the core advantage of traditional alternative investments. Concerns have also been raised that if the AI market fails to grow as expected, far from spreading risk across different assets, the entire portfolio could suffer simultaneous losses.

Concentration of “AI Investments” in PE, Private Debt, Real Estate, and Infrastructure

According to the financial investment industry on the 20th, institutional investors (LPs) have recently assessed that the “diversification effect”—a key advantage of alternative

investments (PE

, private debt, real estate, and infrastructure)—is being diluted. This is because funds across both public and private markets are converging on the single theme of AI.

In the domestic stock market, AI-related exposure has increased as the weight of large-cap semiconductor stocks, such as Samsung Electronics and SK Hynix, has grown. In the bond market, companies like Google and Oracle are raising more capital by issuing large-scale corporate bonds to expand their AI investments.

The private market is no exception. Private equity (PE) firms are increasing their investments in AI-related companies and industries. In the private credit market, deals providing funding to AI-related companies backed by PE firms are on the rise.

In real estate, data centers required for AI computing have emerged as a prime investment target. In the infrastructure market, funds are pouring into related projects such as AI data centers and power grids.

At first glance, PE, real estate, and infrastructure appear to be distinct asset classes. However, a closer look at the underlying assets reveals that they are all connected by a common thread: AI.

Private credit, in particular, is often structurally linked to PE investments. This is because when PE firms invest in a specific industry or company, private credit typically provides financing for acquisitions and other purposes. As a result, even if limited partners (LPs) invest in different asset classes, risks can ultimately be concentrated in the same company or industry.

The Advantage of “Low Correlation” with Equities and Bonds Is Being Diluted

The scale of AI-related investments in capital markets is growing steadily. NVIDIA recently signed a memorandum of understanding (MOU) with six major Wall Street financial institutions to establish an AI infrastructure funding platform totaling $500 billion (approximately 700 trillion won).

The participating financial institutions include Apollo Global Management, BlackRock, Blackstone, Brookfield Asset Management, Goldman Sachs, and KKR. However, NVIDIA will not be investing the $500 billion directly. The structure involves raising the necessary funds for AI infrastructure through large asset management firms, private credit funds, and infrastructure funds.

The issue is that as AI investments occur simultaneously across such diverse investment entities and asset classes, the actual concentration of risk within investment portfolios may increase.

For example, suppose an institution invests in an AI-related private equity fund, a private credit fund, a data center real estate fund, and an AI infrastructure fund, respectively. While this may appear to be a diversified investment across four asset classes, if the AI industry experiences a slowdown, all four assets could be affected simultaneously.

The appeal of alternative investments lies in their ability to reduce portfolio risk by leveraging their low correlation with traditional stocks and bonds.

However, the situation changes when all asset classes ride the same growth wave. This is because alternative investments—which are meant to offset risks across asset classes—end up sharing the same risk factors.

Risk of a “Simultaneous Decline” in Overall Asset Value if AI Growth Slows

The problem could become particularly severe if the AI market’s growth and profitability fall short of market expectations. Not only would the value of AI companies decline, but demand for data center leases, infrastructure investment, and even the creditworthiness of related companies could be affected in a chain reaction.

Ultimately, this means it has become difficult to determine whether an investment is truly diversified based solely on “how many asset classes it is divided into.”

Within the investment industry, there are calls to examine not only asset classes but also the industries and sectors of the underlying assets when constructing alternative investment portfolios going forward. One proposed solution is to intentionally include “neglected sectors” that are unrelated to AI.

Specialized funds that invest in specific sectors—such as the defense industry supply chain or consumer goods—could be prime candidates.

Ultimately, analysts suggest that what will matter most in future alternative investments is not “how many asset classes one has invested in,” but rather “how much diverse risk has been incorporated.” This means going beyond simply categorizing assets into private equity, private debt, real estate, and infrastructure—investors must also manage which industries and companies fall under each asset class.

An LP official stated, “Since AI has established itself as the strongest growth theme in the investment market, it is difficult to completely exclude related assets from a portfolio,” but added, “However, avoiding the concentration of all assets in a single sector—such as AI—is emerging as a key challenge for new diversification strategies.”

He added, “We are considering measures to encourage diversification by requiring investors in blind funds to allocate capital to specific sectors.”