Hunstad: Staying Risk-On in the AI Boom

Northern Trust Asset Management's Michael Hunstad argues Wall Street is underestimating AI's economic impact, citing margin expansion, AI-powered investing, and productivity gains that could keep the Fed restrictive longer. The message is bullish for equities and the next phase of the AI trade, but it is commentary rather than a direct market event. No specific financial figures or company-level updates were disclosed.

Analysis

The market is still valuing AI as a near-term margin story, but the bigger second-order effect is regime change: if productivity lifts across software, semis, services, and capital allocation, nominal growth can stay firmer even as inflation decelerates. That makes the policy path less dovish than the consensus wants to price, which is constructive for equities with real earnings leverage but a headwind for duration-heavy assets and crowded long-rate trades.

The immediate winners are the picks-and-shovels layer with pricing power and constrained supply, but the underappreciated beneficiaries are companies that can convert labor savings into operating leverage faster than peers. That tends to widen dispersion inside the same sector: platform winners and efficient enablers outperform, while firms with large labor cost bases and weak implementation capacity get squeezed despite top-line stability.

The contrarian risk is timing. If the productivity upside arrives slower than promised, the market will have paid forward too much multiple expansion for a future earnings step-up that does not show up for 2-4 quarters. But if the data start confirming it, the Fed may have less room to ease than assumed, creating a rotation away from rate-sensitive growth and toward cash-generative compounders.

Positioning looks vulnerable to a disappointment in breadth: the trade is likely too concentrated in a handful of mega-cap AI proxies. The better setup is to own the beneficiaries of adoption and short the laggards whose cost structures will not flex, while using rates hedges against the chance that stronger productivity keeps real yields elevated for longer.

Key Decisions for Investors

• Maintain an overweight in AI infrastructure beneficiaries (SMH / NVDA / AVGO) over the next 3-6 months, but cap exposure and rebalance into pullbacks; risk/reward remains positive as long as hyperscaler capex trends hold, but upside becomes crowded if positioning gets one-way.
• Pair trade: long XLK or SMH vs short a labor-intensive, low-margin software/services basket over 2-4 quarters; the trade benefits if AI adoption drives operating leverage, with downside protection from shorting names that cannot convert automation into margin expansion.
• Reduce duration exposure via TLT puts or a tactical short in long Treasuries for 1-3 months; if productivity surprises upward, the Fed can stay restrictive longer and real yields can reprice higher.
• Buy calls on high-quality cash-generative software with clear AI monetization paths over speculative AI names; look for 6-12 month horizons where earnings revisions can compound faster than multiples.
• If AI breadth broadens, rotate part of the basket from mega-cap leaders into second-tier semiconductor equipment and datacenter power names; these often have better catch-up beta with less valuation risk than the most crowded AI winners.