The Nasdaq Just Touched New Highs, and BlackRock Says the AI Trade is Back. Here's Why.

BlackRock's iShares said the AI trade remains attractive as big tech spending and earnings growth improve the outlook, with valuations in AI-exposed technology names having cheapened in March. The firm sees the theme broadening beyond U.S. megacaps into emerging markets such as South Korea and Taiwan, which are central to the AI buildout. The report reinforces bullish positioning ahead of Tesla's earnings and amid Amazon's planned up to $25 billion investment in Anthropic.

Analysis

The key market implication is not simply “AI is back,” but that capital intensity is becoming the moat. As long as hyperscalers and adjacent platforms keep turning balance-sheet capacity into incremental model capability and distribution, smaller software names face a widening relative disadvantage: they either spend into the arms race or risk being commoditized by a richer ecosystem. That should keep the winners concentrated in the few names with low cost of capital, large cash generation, and the ability to monetize AI through cloud, ads, or hardware attach.

A second-order effect is that the next leg of performance may come from the picks-and-shovels outside the U.S., especially where supply chain bottlenecks sit. Taiwan and South Korea are leverage points for the AI buildout because the market is still underpricing how much value accrues to advanced memory, foundry capacity, and power/thermal infrastructure rather than just model developers. If the theme broadens, the best risk-adjusted exposure may be the infrastructure layer, not the headline names that are already crowded and most sensitive to any guide-down on capex efficiency.

The main risk is timing mismatch: fundamentals can keep improving while sentiment rolls over if investors conclude returns on AI spending are too distant. That creates a setup where the trade works over months but can whip hard over days around earnings, capex commentary, and any sign that utilization is lagging deployment. On the other side, if one or two mega-cap reports show clear monetization acceleration, the market likely re-rates the entire complex quickly because positioning is still incomplete outside the core names.

The contrarian miss is that the market may be underestimating how much of the upside has already shifted from “AI spend” to “AI payback.” If near-term revenue conversion remains weak, the leadership could broaden, but to suppliers rather than platforms. That makes the upcoming earnings window critical: it should determine whether this is a durable second wave or just another capex-led squeeze in the most liquid names.

Key Decisions for Investors

• Go long AMZN vs. a basket of unprofitable software names over 1-3 months: the trade favors platforms that can monetize AI through distribution and capex discipline over vendors whose valuation depends on delayed adoption.
• Add a tactical long in TSM or ASML on any post-earnings AI-capex dip over the next 2-6 weeks: the risk/reward is asymmetric if hyperscaler spending remains firm, with supply-chain leverage and less multiple fragility than the mega-cap winners.
• Buy TSLA into earnings only as a defined-risk expression, such as call spreads for the next 30-60 days: if AI/robotics commentary is credible, upside can re-rate quickly, but direct stock exposure is vulnerable to any miss on spend or margin expectations.
• Consider a pair trade long BLK / short a broad equal-weight tech ETF for 1-2 quarters: if AI leadership broadens, asset managers with exposure to institutional flow and global allocation trends can benefit while crowded index winners face valuation compression.
• Use Taiwan/South Korea exposure as a hedge against U.S. AI concentration risk over the next 6 months: the payoff is not in headline momentum but in supply-chain revaluation if the market keeps rewarding the infrastructure layer.