BlackRock’s Wei Li urges investors to focus on AI’s “scarcity” inputs, shorter-term bonds and infrastructure

BlackRock strategist Wei Li cautioned that it is still early to identify the clear winners in artificial intelligence, according to a market outlook published by Yahoo Finance on July 1, 2026. Li’s view, as presented in the article, frames AI less as a single market with uniform beneficiaries and more as a buildout that depends on scarce components, bottlenecks and capacity investments across the economy.

Rather than betting on AI as a broad theme, Li pointed investors toward so-called “scarcity” companies, which in this context refers to businesses that help supply limited inputs needed for AI systems to function. The implication is that even if AI adoption is widely discussed, the financial payoff may accrue first to firms positioned around constrained materials, capacity, infrastructure requirements, or other inputs that cannot be scaled instantly.

Li also highlighted shorter-term bonds as an approach investors may find more attractive in the current environment, emphasizing the relative value of maintaining flexibility compared with locking into longer duration. Short-term bonds, meaning debt securities with maturities that typically return principal sooner and are generally less exposed to interest-rate swings than long-dated debt, can be used by portfolio managers to reduce timing risk while still earning yield.

In addition to scarcity-linked equities and shorter-duration fixed income, Li pointed to infrastructure. Infrastructure investing typically includes assets and operators that build or maintain essential systems such as data-related networks, power delivery, transportation, and other physical platforms that support economic growth and technology deployment. In the article, infrastructure is presented as a complementary allocation where demand may be supported by multi-year capital spending cycles.

For BlackRock, the message fits its long-running emphasis on portfolio construction that balances growth and risk management. The firm manages a wide range of strategies across equities, fixed income and alternatives, and it often translates macro views into asset-class and theme guidance for clients. While the article centers on Li’s perspective, it reflects BlackRock’s broader positioning that AI investment outcomes may hinge on second-order factors such as constraints and enabling infrastructure rather than only on end-user adoption narratives.

The post did not offer company-specific stock picks, list particular “scarcity” categories, or quantify expected returns for any of the suggested areas. It also did not provide details on what maturity range Li had in mind for “shorter-term” bonds, nor did it indicate whether the infrastructure view was focused on specific sub-sectors such as energy infrastructure, telecom networks, or other infrastructure categories.

As with many strategist takes, the timing and selection risk remain. AI “winners” can change quickly as technology standards evolve, supply chains adjust and competition intensifies. Likewise, the benefit from constrained inputs depends on whether shortages persist long enough to translate into durable margins, and infrastructure outcomes can be affected by project timelines, regulation, and financing conditions. The article, however, does not disclose any assumptions behind those judgments.

Investors watching this theme shift would likely focus next on signs that AI-related constraints are actually narrowing or, conversely, deepening, along with data on fixed-income carry and how investors are repositioning across the yield curve. For BlackRock clients, the immediate question is whether the firm will expand on Li’s framework with more concrete allocation guidance or example exposures in upcoming commentary. No further details were provided in the referenced market outlook.