[Edaily Marketin KIM SUNG-SOO Reporter] The “forced diversification” strategy is emerging as a new hot topic in the alternative investment market. This stems from the assessment that even when investments are spread across asset classes such as private equity (PE), private credit, real estate, and infrastructure, funds ultimately flock to a single theme—artificial intelligence (AI)—making it difficult to adequately manage risk through traditional “asset class diversification” alone.

Consequently, a solution being proposed involves incorporating funds that intentionally invest in overlooked sectors into portfolios, while also tracking the underlying assets of those funds to manage sector-specific concentration risks.

PE, Real Estate, Infrastructure, and AI… The “Diversified Investment” Formula Is Shaken

According to the financial investment industry on the 21st, institutional investors (LPs) have recently observed that as artificial intelligence (AI) has established itself as a massive investment theme permeating the entire financial market, a “forced diversification” strategy is emerging in the alternative investment market.

Until now, the key advantage of alternative investments was their low correlation with traditional assets such as stocks and bonds. The logic was that investing in different asset classes—such as private equity, private debt, real estate, and infrastructure—could mitigate the spread of shocks from a specific market to the entire portfolio.

However, cracks are recently appearing in this formula, as capital is converging on the common theme of AI, regardless of whether it is in public or private markets.

In private equity (PE), investment in AI-related companies is expanding, and AI-related deals are also on the rise in private credit. In real estate, AI data centers have emerged as key investment targets, and in the infrastructure market, AI-related power and data center projects are becoming major investment targets.

While investors may appear to be investing in different assets on the surface, in reality, a common risk—known as “AI exposure”—is accumulating throughout their portfolios.

In particular, problems could escalate if the AI market’s growth potential and profitability fail to meet market expectations. This is because there is a possibility that the value of investment assets—which were thought to be diversified across different asset classes—could decline simultaneously.

Consequently, the alternative investment market is exploring approaches that go beyond simply diversifying across asset classes and asset managers, such as intentionally including “underrepresented sectors” in investment portfolios.

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Invest

in Non-AI Assets Too”… ‘Forced Diversification’ Through Sector Funds

The most direct method being discussed is the intentional inclusion of sector-specific funds.

Previously, it was common to invest in blind funds—which invest across various industries—by spreading investments across multiple asset managers. However, if multiple general partners (GPs) all pursue AI-related investments, simply increasing the number of asset managers is unlikely to yield a meaningful diversification effect.

Therefore, the strategy is to deliberately include funds that focus intensively on specific industries in the portfolio to induce sector diversification. Prime candidates include the defense industry and consumer goods.

In the case of the defense industry, funds investing in the defense supply chain—whose growth potential has increased alongside expanding geopolitical risks—could be suitable candidates. This approach involves intentionally including industries relatively distant from AI investments to reduce the overall portfolio’s exposure to AI.

The same applies to consumer goods-focused funds. This strategy involves adding funds that concentrate on consumer goods companies—such as luxury brands—to introduce alternative sources of return into a portfolio that is heavily weighted toward AI. Ultimately, the concept of diversification is shifting from “selecting good investment opportunities” to “deliberately including different investment opportunities.”

Forced diversification goes beyond simply diversifying general partners (GPs). It involves expanding the scope of management by scrutinizing even the underlying assets of the funds into which investors have actually committed capital.

For example, even if an investor has allocated funds to multiple PE firms—such as A, B, and C—they must still examine which specific companies and industries those firms have actually invested in.

The “Fund’s Underlying Assets” Are More Important Than the Number of Managers… Focus on Underlying Assets

If Manager A invests in AI semiconductor companies, Manager B in data centers, and Manager C in AI software companies, then although the portfolio is formally diversified across three managers, it may actually be concentrated on a single theme—AI.

An investment industry official explained, “It’s important to know how much private equity was invested in which general partner (GP) and how the diversification looks from a top-down perspective,” but added, “In practice, we need to continuously review data provided by the fund managers to see how the sectors of the actual underlying assets are composed.”

This shifts the unit of management from diversification based on GPs to diversification based on underlying assets. The use of Separately Managed Accounts (SMAs) is also being discussed as a means to systematically implement such a sector diversification strategy.

Unlike general funds, which pool money from multiple investors, a Separately Managed Account (SMA) is an individual asset management account in which a single investor’s funds are set aside and entrusted to a professional asset manager for customized management. Investors retain direct ownership of the assets and can tailor their investment strategies, making this approach popular among large institutional investors.

This approach involves leveraging the vast amounts of underlying data held by global asset managers such as Steepstone and Hamilton Lane to quantitatively analyze sector-specific exposure and, based on this analysis, construct a “reference portfolio.”

For example, if the investment weighting in a specific industry becomes excessively high, it is reduced, and industries with relatively low weightings are added, gradually aligning the actual portfolio with the reference portfolio. In this sense, the SMA serves as a kind of “portfolio roadmap.”

In particular, it offers the advantage of enabling systematic sector diversification management—beyond simple qualitative judgments—by leveraging the vast amounts of underlying asset data accumulated by global asset managers.

An LP official stated, “The rise of forced diversification strategies in the alternative investment market is due to AI having established itself as a major investment theme permeating the entire financial market,” adding, “No matter how different the investment targets—such as private equity, private credit, real estate, and infrastructure—may be, if funds ultimately flow into the same industries and companies, the advantage of alternative investments—low correlation between asset classes—is bound to be diluted.”

He continued, “Going forward, ‘which industries and companies are included in those funds’ will emerge as the core criterion for portfolio management, rather than ‘how many funds one has invested in.’ This means that, just as much as riding the massive wave of AI, the true diversification effect of an alternative investment portfolio will be determined by how deliberately one includes assets that can move in a different direction from AI.”