AI, Healthcare, and Volatility: Positioning for 2026

In Q1 2026, I stepped into the role less of an interviewer and more of an investigator, sitting across the table from 35 portfolio management teams covering mutual funds, ETFs, and SMAs in large cap growth, large blend, and large value. Each team was asked the same eight questions — no leading prompts, no room to dodge — so the evidence was clean and comparable. As the answers piled up, patterns began to surface: repeated narratives told by different voices, subtle tells that revealed where conviction was genuine versus rehearsed. Outliers stood out like fingerprints at a crime scene — views that broke from consensus, either by design or by blind spot. By lining up these responses and weighing both what was said and what was left unsaid, I condensed the common themes driving opportunity today, while also flagging the risks lurking beneath crowded assumptions and shared beliefs. What follows is the case file.

AI, Healthcare, and Volatility: Positioning for 2026

As equity markets transition into 2026, large cap equity portfolio managers share a surprisingly consistent framework — paired with sharp disagreements on where risk and opportunity sit. A survey of large growth, value, and blend managers reveals a market shifting away from simple narratives toward selectivity, fundamentals, and manager skill.

At the center of this discussion sits artificial intelligence. Nearly every manager acknowledges AI as a long‑term structural force, yet far fewer believe it remains an easy trade. At the same time, healthcare has emerged as the most consistently cited undervalued sector across investment styles, even as managers concede it remains one of the hardest areas to execute well.

What follows is a synthesis of where managers align, where tension exists, and what these dynamics suggest for equity markets heading into 2026.

AI: A Structural Force That No Longer Guarantees Returns

AI dominates nearly every strategic conversation. Managers broadly agree it represents a multi‑year earnings driver spanning software, semiconductors, industrial automation, data infrastructure, and services. The difference now lies in execution.

The earlier phase of AI investing rewarded broad exposure. We believe that phase has largely passed. Managers increasingly emphasize real earnings, sustainable demand, customer monetization, and the durability of competitive advantage. Several indicate that portions of the AI infrastructure, semiconductors, and enabling hardware have high valuations, leaving a limited margin for error.

This shift has created three emerging camps:

  • AI beneficiaries with recurring revenue and pricing power
  • AI survivors capable of absorbing competition and margin pressure
  • Mispriced AI losers where fear has outpaced fundamental deterioration

The tension centers on portfolio sizing. Some managers remain heavily allocated, treating AI as the next secular growth engine. Others deliberately neutralize exposure, framing AI as one of the largest potential sources of downside if expectations compress.

The implication is not AI fatigue, but higher hurdles. Exposure alone no longer drives results — security selection does.

Read more: AI Wave Continues to Power Technology Earnings Boom