AI Markets Shockwave: BlackRock’s Jay Jacobs Reveals the Essential Plays

AI markets are evolving fast—and BlackRock’s Jay Jacobs says the winners stretch across data owners, model developers and lesser-known chipmakers that are integral to the ecosystem. In a wide-ranging discussion, the firm’s Head of U.S. Equity ETFs outlined how investors can pursue innovation without overconcentrating in a handful of mega-cap names.

Speaking in a recent YouTube interview, Jacobs emphasized two ideas that often get overlooked: active selection to reach the deeper layers of the AI stack, and broad diversification so portfolios are prepared for shifts in market leadership. His message comes as investors weigh new AI products, rising equity indexes and a growing menu of risk-managed ETF tools.

Jacobs highlighted BlackRock’s actively managed AI-focused fund, known as BAI, which concentrates on three pillars he views as foundational to AI markets: companies that own valuable data; developers of large language models; and a layer of under-the-radar semiconductor players that supply critical components. That approach, he argued, offers exposure to multiple profit pools rather than a single bet on a marquee software name.

While the “Magnificent Seven” have powered recent equity gains, Jacobs noted that leadership rotates across market cycles. International equities, small caps and real-economy themes—like infrastructure and reshoring—can be just as important for long-term outcomes as the flagship AI names investors know best.

What’s Integral to AI markets, According to BlackRock

Asked what distinguishes durable winners, Jacobs pointed to firms controlling proprietary datasets, model developers turning that data into utility and hardware suppliers enabling training and inference at scale. That full-stack exposure, he said, lets investors tap multiple profit pools within AI markets rather than betting on a single layer.

Three cohorts underpin AI markets right now:

• Data owners across industries such as cloud platforms, enterprise software, healthcare and industrials
• Model developers advancing large language models and specialized AI applications
• Semiconductor and component suppliers—often not household names—enabling compute, memory and networking

BAI leans into that blend with active oversight, aiming to move nimbly as the technology and revenue drivers shift. The fund has drawn attention for performance and flows discussed during the interview, underscoring how rapidly the AI theme continues to expand.

Beyond the Magnificent Seven: Diversify for a Changing Tape

Jacobs urged investors not to be “too enamored” with the largest tech stocks. He reiterated that different environments can favor small caps, international markets and targeted themes such as infrastructure—areas supported by reshoring efforts and evolving supply chains. As grids, data centers and logistics expand, they can indirectly bolster AI markets by providing the physical backbone needed for high-intensity compute.

Key diversification ideas mentioned:

• International exposure when leadership broadens beyond U.S. mega caps
• Small caps during domestic growth spurts or when rate paths clarify
• Infrastructure and industrials tied to power buildouts, roads and fabrication capacity
• Thematic allocations that complement core index holdings without dominating them

Inside BlackRock’s Active AI ETF Lens

Because the landscape shifts quickly, Jacobs favors active selection to rebalance across the ecosystem as the opportunity evolves. That can mean rotating from training-heavy suppliers toward inference leaders, balancing cloud exposure with edge compute, or emphasizing software monetization when costs decline.

An active approach can help:

• Capture lesser-known suppliers that are essential to capacity expansion
• Tilt toward segments where pricing power and margins are improving
• Manage position sizing to reflect valuation risk and liquidity
• React to regulatory changes that could affect data usage or deployment
• Keep exposure aligned with where profits are accruing within AI markets—key for long-term participation

Macro Hedges: Bitcoin, Gold and the Search for Alternatives

The conversation also touched on Bitcoin’s role amid persistent macro risks. Jacobs noted that BlackRock’s spot Bitcoin ETF (IBIT) saw rapid asset growth in its first year as investors embraced the ease of gaining exposure through traditional brokerage accounts. In parallel with strong interest in gold, he said some investors are exploring digital assets because they sit outside fiat currency systems.

He underscored, however, that Bitcoin remains a volatile asset. Position sizing, time horizon and a clear risk framework are essential. For investors who already have AI markets exposure, some are pairing it with macro hedges like Bitcoin and gold to balance risks tied to geopolitics, sticky inflation and rising government debt.

How to Allocate: “Be, Beat, Modify” Framework

To build resilient portfolios that include AI markets exposure, Jacobs outlined a three-bucket approach:

• Be the market: Core index exposure forms the foundation of most portfolios, offering broad market participation at low cost.
• Beat the market: Selective themes such as AI markets and infrastructure, plus factor strategies or active managers targeting excess return.
• Modify the market: Risk-managed overlays—like buy-write (covered call) strategies—to seek additional income or adjust payoff profiles.

This framework lets investors integrate cutting-edge themes without abandoning discipline. It also encourages clarity around what each building block is supposed to do—core beta, tactical alpha or risk modification.

Managing Risk at Highs: Buffer ETFs, Caps and Trade-Offs

With the Dow at record highs and major indexes near their peaks, some investors are adopting defined-outcome products designed to cushion drawdowns while capping upside. Jacobs pointed to a new BlackRock fund dubbed S10 (ticker: STEN), which seeks to buffer the first 10% of losses while limiting gains—an approach that can complement high-growth allocations in AI markets.

When to consider defined-outcome ETFs:

• You’re sitting on cash after a rally but want a measured on-ramp
• You want to stay invested despite near-term headline risk
• You’re pairing higher-volatility themes with a downside buffer

What to watch:

• Cap levels and reset schedules
• Index tracked and buffer size
• Liquidity and costs
• Fit with your existing equity and options exposure

These tools are not substitutes for cash or Treasuries; they are a way to fine-tune equity participation amid uncertainty. As always, the trade-off for protection is a cap on gains.

What Investors Should Watch Next in AI markets

Several catalysts could reshuffle leadership within AI markets over the next 6–12 months:

• Power build-out and data center capacity: Availability of power, networking and cooling will influence where incremental compute is deployed.
• Model breakthroughs vs. unit economics: Advances in capabilities matter, but so do the costs of training and inference. Falling costs can shift value toward software monetization.
• Inference at the edge: Demand for on-device AI could benefit specialized chips, memory and connectivity suppliers beyond the hyperscalers.
• Supply chain resilience: Lead times for advanced semiconductors and substrate materials remain a swing factor for hardware-heavy names.
• Regulation and data governance: Policy around privacy, training data and AI safety can alter addressable markets and compliance costs.
• International adoption: Enterprise and government AI spending outside the U.S. may broaden the set of winners.

Industry Reaction and Market Context

Investor interest has been strong across AI-oriented strategies as the theme matures. Active AI funds, diversified tech allocations and complementary plays—such as power infrastructure—have captured attention from both retail and advisors. At the same time, risk-managed equity products have seen inflows from investors who want to participate while acknowledging headline risk.

Within technology, leadership has rotated between software beneficiaries and hardware suppliers. That ebb and flow reflects shifting bottlenecks, pricing power and deployment phases inside AI markets. Jacobs’ comments fit a broader industry pattern: investors are seeking full-stack exposure while keeping portfolios flexible enough to adapt.

Practical Portfolio Considerations

Investors considering an AI allocation can stress-test their portfolios with a few simple questions:

• Exposure map: Do you only own the largest AI beneficiaries, or do you also hold data owners and enabling hardware suppliers?
• Concentration: Are single stocks or one subsector dominating your risk budget?
• Global reach: Is there room for international names positioned to gain from sovereign AI initiatives?
• Capital cycle: Where are we in the build-out of compute, memory and networking—and how could that affect margins?
• Risk offsets: Do you balance growth exposure with income strategies, buffers or diversifiers like gold or Bitcoin?

Answering these questions can help align AI exposure with goals, timelines and volatility tolerance.

What It Means for Long-Term Investors

Jacobs’ core message is pragmatic: innovation-led themes can be powerful drivers of returns, but they belong inside diversified, risk-aware portfolios. Full-stack exposure across data, models and hardware can broaden the opportunity set. Tools like defined-outcome ETFs or buy-write strategies can make it easier to stay invested through turbulence. And a flexible framework—be the market, try to beat it in targeted ways, or modify it for risk—keeps decision-making clear.

For investors building or refining AI positions today:

• Use core index funds as a foundation
• Add targeted exposure to AI markets through active or thematic ETFs that reach beyond obvious winners
• Pair growth allocations with risk modifiers if you need help staying invested
• Revisit assumptions as the power, cost and regulatory landscape evolves

Statements, Attribution and Updates

Jacobs’ insights were shared in a YouTube segment titled “Expert reveals what’s integral to AI markets.” The discussion covered BlackRock’s AI-focused ETF approach, diversification beyond mega caps, the rapid adoption of the spot Bitcoin ETF (IBIT) and the launch of a defined-outcome fund aiming to buffer the first 10% of declines while capping upside.

As with all investment content, this article is for information only and does not constitute investment advice. Investors should do their own research, consider costs and tax implications, and assess products’ objectives and risks before investing.

The Bottom Line

AI is reshaping sectors well beyond big tech, from data-rich enterprises to the suppliers building the power and compute backbone. BlackRock’s Jay Jacobs argues that a diversified, full-stack approach—supported by risk-managed tools—can help investors participate in that growth while staying grounded. For those refining allocations, the playbook is clear: balance core holdings with targeted exposure to AI markets, and use risk tools thoughtfully so you can remain invested as the story unfolds.

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Article Source: Fox Business