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How to reposition equity portfolios for recurring AI disruption

4 min read
2027-03-01
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Nanette Abuhoff Jacobson, Multi-Asset Strategist
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Andrew Heiskell, Equity Strategist
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Key points

  • The recent AI-induced sell-off across a range of industries suggests we have entered a new era of volatility where investors are increasingly likely to question the solidity of incumbents’ business models amid rapid AI advances.
  • While I don’t see this as a systemic risk, the market is debating AI in real time, which is a volatile dynamic fueled by rapid AI developments and the growing risk of near-term setbacks.
  • As this debate unfolds, markets are likely to overreact, universally penalizing certain sectors while piling into others, regardless of fundamentals. Against this backdrop, I believe there’s a case to be made for leaning into an active investment approach.

What happened with AI?

Fears that rapid advances in AI tools could undermine the business models of incumbents across a range of industries triggered a series of sell-offs, starting with technology stocks, which sold off to the tune of nearly US$1 trillion,1 before spreading to other industries deemed vulnerable to AI disruption. While the market at the time of writing has stabilized, it’s a situation worth examining more closely given its potentially recurring nature.

So, what happened? First, hyperscalers — companies investing heavily in building and expanding data centers globally — reported phenomenal fourth-quarter earnings numbers. But the market focused on the viability of some of the collective US$700 billion in capex, or long-term investment, this group of companies made in 2025.

Second, software stocks got hammered. AI safety and research company Anthropic rolled out industry‑specific AI tools for the legal, financial, and research fields, and the market panicked based on the assumption these tools would make incumbent software companies less relevant.

Other AI companies then followed suit with the announcement of further sector-specific tools offering the prospect of significant efficiency gains. In turn, this caused the market to question valuations of industries as diverse as rating agencies, wealth managers, real estate, and trucking.

What else weighed on markets?

These worries coincided with intensifying rotations in the US equity market. Momentum and high-beta factor stocks sold off, while energy, materials, consumer staples, and other lower-volatility sectors surged.

What’s more, the labor market has shown signs of softening. Job openings hit their lowest rate since 2020 and layoffs ticked up. While the latest US jobs report has allayed some of these concerns, investors are likely to keep fretting about the impact of AI on white-collar employment.

At the same time, it’s worth noting that there are macro supports in place that could act as a buffer in the face of other broad market challenges. These include room for US Federal Reserve easing, strong fiscal spending by the US and other countries, as well as robust US consumer health.

What does it mean?

Taken together, these dynamics remind us that AI’s spillover effects are accelerating. This said, I don’t see the recent AI-disruption-induced tech sell-off as a systemic risk, meaning a combination of bad fundamentals and/or too much leverage.

This time, software companies were first in the firing line with private credit managers (as providers of capital) following suit, before other sectors got caught in the crosshairs. It makes one wonder what segment of the market AI will shake up next. In effect, these sudden chain reactions show that investors have started to reassess the “terminal value” of different industries as AI is disrupting established business models. However, the risk is that the market may go too far and be too indiscriminate in its reassessment. In some cases, we think industries will benefit from AI and the players that are investing in and adapting to AI will be eventual winners.

The bottom line? AI is moving at breakneck speed, and the market is debating its power in real time with the attendant risk of knee-jerk reactions. So, volatility remains on the horizon.

What should we do?

This market sell-off serves as a reminder for investors to identify where fear overshoots fundamentals. Three ways they can do this include:

  1. Lean into active: An active approach is more likely to help investors own the long-term AI infrastructure winners and the high-quality names that are likely to benefit when the market questions AI’s near-term payoff. Despite the sell-off, in my view, there’s no need for endemic risk aversion. Take for instance, software companies. Well-run software providers that are deeply embedded in their customers’ businesses and have proprietary datasets, mission-critical workforces, and recurring revenue are likely to continue to perform longer term and will be able to harness AI to their benefit. At the same time, I think AI may deepen the divide between winners and losers. Active investors may be well-placed to identify into which category companies are likely to fit, including identifying winners in unexpected corners.
  2. Pay attention to rotations: As the debate about gargantuan spending by the hyperscalers persists, the US rotation into real-economy sectors should continue to run its course in the short term. So too should the regional rotation toward non-US equities and emerging market equities. Thoughtful diversification may help investors align with those rotations.
  3. Add some defense: Current market conditions may be tailwinds for dividend and growth-style portfolios. When markets broaden, defensives rally, and capital discipline becomes more important, these types of exposures tend to outperform. Quality equities, especially quality compounders that deliver slow but steady growth, select fixed income, and gold could also be beneficial defensive allocations.

The views expressed are those of the authors at the time of writing. Other teams may hold different views and make different investment decisions. The value of your investment may become worth more or less than at the time of original investment. While any third-party data used is considered reliable, its accuracy is not guaranteed. For professional, institutional or accredited investors only. 

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